1. bookVolume 14 (2021): Edition 1 (January 2021)
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Performance evaluation of vertical handover in Internet of Vehicles

Publié en ligne: 28 Jun 2021
Volume & Edition: Volume 14 (2021) - Edition 1 (January 2021)
Pages: 1 - 16
Reçu: 16 Jan 2021
Détails du magazine
License
Format
Magazine
eISSN
1178-5608
Première parution
01 Jan 2008
Périodicité
1 fois par an
Langues
Anglais
<p>The goal of IoV is to allow vehicles to communicate with other vehicles, humans, pedestrians, roadside units, and other infrastructures. Such communications are classified into five categories that are referred to as V2X communication (X: vehicles, RSU, infrastructure, humans, and pedestrians). The vehicles transfer both safety and non-safety data at different data rates. Safety data as an accident, road traffic, and others, while non-safety data such as video streaming, gaming, and so on. Integration of IoV with advanced wireless communication technologies such as 5G makes it a heterogeneous network (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>). It composes of Wi-Fi, Long-Term Evolution (LTE), and others. In general, vehicle communication is supported for both safety and non-safety data transmissions. The vehicles use dedicated short-range communication (DSRC) which enables low latency communication for short-distance vehicles.</p><p>In IoV, vehicles use DSRC for communication; however, due to its shorter range and bandwidth limitations, it is not suitable for long-distance communications and bandwidth greedy applications. Hence, IoV integrates with 5G to provide high data rates for communication. However, it suffers from blockage issues as it is unable to penetrate through obstacles (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_004">Choi et al., 2018</a>). Besides, LTE also provides long-distance communication because of its coverage range, and high bandwidth features. Each radio access technology has its benefits and limitations.</p><p>Vehicles are equipped with multiple antenna terminals that enable to access different radio access network (RAN). Due to the use of different RAN in a network, a network introduces the process of vertical handover (VHO) (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_012">Sheng et al., 2018</a>). 5G comprises different radio access technologies due to the presence of different cells such as microcell, femtocell, and nanocell. Each cell will be having more than one RAN and hence, requires selection of the best network (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_007">Jubara, 2020</a>). Several multi-criteria decision-making algorithms have been proposed for network selection. In general, this type of algorithm takes into account multiple parameters and computes them for decision-making. The TOPSIS is one of the decision-making algorithms. This type of multi-criteria decision algorithms is popular in the selection of networks. IoV enables allowing data transmission of the highway and urban roadways in an autonomous vehicle (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_014">Storck and Duarte-Figueiredo, 2019</a>). If there is an increase in the vehicle density, then the number of requests from the vehicles for vertical handover will also gradually increase.</p><p>The vehicle is built with more than one antenna terminal. The support of different RAN technologies requires selecting a network when one or more RAN is present in the coverage range.</p><p>The network selection process is also performed using optimization, reinforcement learning methods, and access network discovery and selection function (ANDSF) (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>). Q-learning is an algorithm that can decide concerning the environment. In IoV, vehicles move at very high speeds with change in topology and connectivity, the data transmission relies on routing (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>). Routing is the process of transferring data from source to destination through relay vehicles (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>). In routing, the vehicles in a route are preferred by taking into account the vehicle-based metrics like traffic, vehicle capacity, reliability, mobility, and others. As per the estimation of the metrics, a route or path is identified and packet forwarding is performed in that route. The process of routing is subjected to some challenges as topology changes, time consumption in route selection, and so on. The algorithms and methods are proposed to solve these challenging issues.</p><p>The goal of this paper is to minimize the number of unnecessary handovers when there is a need for high bandwidth while the data type changes. This research builds a learning-based method to decide whether there is a need for handover and then it selects a network for handover. In this way, we can reduce the number of unnecessary handovers. Then, V2V routing is established to minimize the number of re-transmissions. A poor selection of transmission routes causes route failure that leads to an increase in the number of re-transmissions. To solve this issue, an optimization algorithm is used. The two main contributions of our proposed work are to perform handover using network selection and data transmission via the best route.</p><p>The rest of this paper is organized as follows: the second section presents the previous research works and methods, the third section gives a particular problem description, and the fourth section discusses the proposed algorithms of handover, network selection, and routing. The fifth section discusses the simulation results, and the sixth section depicts the conclusion with future research directions.</p></sec><sec id="j_ijssis-2021-012_s_002"><div>Related work</div><sec id="j_ijssis-2021-012_s_002_s_001"><div>Prior works on handover</div><p>Handover (HO) in the vehicular network is challenging to perform since the mobility of vehicles changes. Many research works have studied this issue and performed handover without any degradation in network metrics. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_003">Chang et al. (2019)</a>, a cluster-based handoff, and dynamic edge-backup node (DEBCK) is proposed where the vehicles on the road lane were clustered, and the backup node provides handoff. Here, the cluster head performs the handoff and the backup mobile edge vehicle. The three main parameters that were taken into account for handoff are storage, communication, and energy. The main drawback of this work is poor handoff performance of backup mobile edge and cluster head, and failure to perform handoff whenever there is a need. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_007">Jubara (2020)</a> a procedure for HO was proposed with the aim of minimization of delay in HO. A cross-layer protocol in an adaptive L4 HO procedure begins to estimate signal strength and if the quality of the signal was poor, then the link between user and base station disconnects. Then the Stream Control Transmission Protocol (SCTP) is assigned to the new IP and it is updated to the layers. However, the signal strength was not the only significant metric to make HO decisions. Due to the mobility of the vehicle and moving pattern on the road lane, HO of moving vehicles was proposed (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_004">Choi et al., 2018</a>). According to the idea of this work, a group of users consists of a mail leader, sub-leader, and follower. The sub-leader was selected based on the maximum number of connections. In case if more than one vehicle has similar characteristics then, a sub-leader was selected at random. Initially, the vehicle computes reference signal received power (RSRP), reference signal received quality (RSRQ), link quality, and is reported for HO decision. A decision tree was built for HO decision-making using RSRP measurement. But the vehicles HO in a group requires frequent computation in the group, as well as measurement, and hence the computation will be higher in this work. The network layer-based L2 extension HO scheme was proposed (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_009">Naeem et al., 2019</a>) and the architecture consists of an access router (AR), roadside unit (RSU), and vehicles. This work defines two HO schemes as inter-AR HO and intra-AR HO. The key goal of this scheme was to minimize latency and improve the packet delivery ratio. A fuzzy logic model and Elman Neural Network (ANN) was designed to decide along with the assurance of QoS (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_009">Naeem et al., 2019</a>). For HO decisions, the parameters that are taken into account as cost, transmission range, velocity, load, and capacity. Even though this work performs better, the time for HO decision consumes time which increases the delay in the HO that may cause packet drop and degrades packet delivery ratio. The paper (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_013">Singh et al., 2020</a>) concentrates on handover as well as routing. A handoff protocol was proposed that computes link expiration time (LET) for detecting the connectivity between vehicles. The partner selection protocols enable a selection of optimal partner nodes (PN). Initially, the route was determined from GPS information and then the partner in the routes was selected from the vehicular LET using the traffic information. The vehicle with a high LET will be selected as the optimal PN in the route. In this work, only a single metric was taken into account for selecting a route between source and destination. However, if an opposite moving vehicle with high LET cannot be selected as PN and hence it requires considering other parameters too. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_008">Leu et al. (2019)</a>, and enhanced Access Network Discovery and Selection Function (ANDSF) was presented to perform a BS selection in the network. This algorithm combines with multilayer perceptron (MLP). The parameters were load, signal strength, throughput, and delay. The traditional workflow of the ANDSF is illustrated in <a ref-type="fig" href="#j_ijssis-2021-012_fig_001">Figure 1</a>.</p><figure id="j_ijssis-2021-012_fig_001" fig-type="figure"><h2>Figure 1:</h2><figCaption><p>Workflow procedure of ANDSF (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_001.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=d7f4b1353ff7030ffd85d3549b15458d2b06c94facc2f49fc190c45685ad692e" class="mw-100"></img></figure><p>The ANDSF was equipped within the EPC which was started to be used in 3G and also on advanced radio access networks. This server was employed to discover information, manage policies, select policies, manage rules, and others. The user equipment can be a sensor, vehicle, or any other device that can access radio technology. The server first discovers the device and then performs a change in the connectivity. The procedure works by the developed set of rules and policies.</p><p>The vertical HO was performed using multi-criteria methods by taking into account the significant parameters such as QoS, delay, cost, and others (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_006">Hamurcu and Eren, 2020</a>). Due to the consideration of multiple metrics for HO decision using enhanced Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) fuzzy logic (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_005">Embus et al., 2020</a>). The working of this combination of algorithm works as per the following steps:<list id="j_ijssis-2021-012_list1" list-type="bullet"><list-item><p>Step 1: creates decision matrix using the parameters that were involved for HO decision. The computation was executed for each available network in the coverage area.</p></list-item><list-item><p>Step 2: apply the Euclidean distance formula for determining the normalized decision matrix.</p></list-item><list-item><p>Step 3: computation of weighted normalized decision matrix based on the function of the cross product.</p></list-item><list-item><p>Step 4: estimate two ideal solutions as positive and negative from the cost metric. Hereby a set of benefit-based criteria were used for positive ideal solution prediction.</p></list-item><list-item><p>Step 5: again use the Euclidean distance formula and determine the distance value for the estimated ideal solution.</p></list-item><list-item><p>Step 6: compute relative closeness using the determined ideal solution in previous steps.</p></list-item><list-item><p>Step 7: at the end, the ranking was performed from the determined closeness for each network, and based on this ranking, the best network was selected for HO.</p></list-item></list></p><p>The processing steps illustrated above for enhanced TOPSIS using fuzzy were able to overwhelm the problems in conventional RSS-based HO. Each step includes multiple criteria, these steps were not parallel, i.e. on each HO request, all the process requires to be performed and the decision was made after ranking.</p></sec><sec id="j_ijssis-2021-012_s_002_s_002"><div>Prior works on routing</div><p>The IoV environment that uses different types of radio access network due to the coverage range of each radio access. However, the vehicles have in-built DSRC for short-range data transmission, while the destination vehicle moves far from the source, then a route has to be preferred for data transmission.</p><p>Vehicles perform routing by selecting relay vehicles between the source and destination since the DSRC range was small and hence it is not able to connect longer distance vehicles. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_011">Nguyen and Jung (2020)</a>, Ant Colony Optimization (ACO) algorithm is proposed with the idea of coloring vehicles. This algorithm presents two processes as solution construction and pheromone update. The idea of coloring was to give similar colors for the vehicles that have the same destination. As per the pheromone value, the route was selected in this work. However, this work failed to consider the significant parameters of the vehicles for the computation of the pheromone value that decides the transmission route. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_001">Al-Kharasani et al. (2020)</a>, a cluster-based adept cooperative algorithm (CACA) is proposed focusing on the QoS metrics. As per this work, clustering formation is done and a cluster head was selected. This work follows Optimized Link State Routing (OLSR) protocol with the Multi-Point Relay (MPR). This selection takes into account mobility factors, distance range, and quality of path (QoP). The vehicles that satisfy these parameters were selected as MPR and then the intersection vehicles were eliminated. The selection of MPR was not efficient, since the vehicles move at high speed. A protocol design was proposed, i.e. partner selection protocol that considers Vehicle Link Expiration Time (VLET) (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>). In this work the handoff means a vehicle disconnects from a partner node and joins a new partner node (PN), the partner node enables to perform data transmission. The only measure that was used in the selection of PN was not efficient since there are other significant metrics as signal strength which was also essential in node selection. A cross-layer design was proposed (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_008">Leu et al., 2019</a>) that selects an optimal route based on the metrics forwarding probability, bandwidth, and link duration. The forwarding probability for the vehicle was formulated by considering velocity, distance, and communication range. The link duration was mathematically calculated as communication link lifetime that takes into account vehicle velocity, GPS location, and communication range. Then, the third parameter of bandwidth was calculated from link gain, noise power, and channel bandwidth.</p><p>The relay node selection was presented in the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_002">Cao et al. (2019)</a> for relay selection using the estimation of curving rate. A double direction relay node selection was involved when the request to broadcast (RTB) was 1 and then it select relay from the estimation of curving rate, delivery ratio, one-hop delay, and message dissemination speed. The curving rate was formulated from the road length and the range of the vehicle. The computation of each parameter one after the other for route selection was time consuming and it leads to higher packet drop.</p><p>Routing is also performed using optimization algorithms. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_008">Leu et al. (2019)</a>, a hybrid optimization algorithm is proposed combining monarch butterfly and gray wolf optimization for route selection. The parameters that were taken into account for route selection are different costs computed for congestion, collision, travel, and QoS. For QoS prediction, fuzzy membership functions were applied. Initially, the butterfly algorithm was involved and then the gray wolf was performed for position updates and selecting optimal paths. The traditional issue in gray wolf optimization is its poor performance, and low accuracy. Fuzzy logic was also used to select routes by estimating link quality and achievable throughput. The link quality was based on the position, direction, and expected transmission count. As per the fuzzy weight, the output of the selection of next hop relay was performed. However, this work failed to tolerate the mobility issues concerning vehicular communication.</p></sec></sec><sec id="j_ijssis-2021-012_s_003"><div>Problem definition</div><p>Issues concerning handover, network selection, and routing are discussed in this section from the previous research works. In the study of <a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al. (2020)</a>, the author proposed reinforcement learning algorithms. TOPSIS, K-Nearest Neighbor (K-NN), and AHP are proposed for handoff decisions considering bandwidth, network cost, preferences, connectivity probability, and signal to noise ratio (SNR) as the evaluation metrics.<list id="j_ijssis-2021-012_list2" list-type="bullet"><list-item><p>TOPSIS algorithm are subjected to rank reversal problem that either includes or eliminates the order of preferences. Besides this problem, it performs poorly to make vertical handover decisions.</p></list-item><list-item><p>The handover is performed by the vehicle based on the ranking results the vehicle. However, the need for handover is not evaluated. Also, if all the vehicles requests for handover then TOPSIS had to perform the handover individually since the parameters differs for each vehicle.</p></list-item><list-item><p>The use of k-NN for handover decisions was not efficient, since the k-NN algorithm gives higher accuracy in results only when the link quality was better. Also while the arrival of data was in large amount then the algorithm slows down to process and hence it takes time to make handover decisions.</p></list-item><list-item><p>The data forwarding through these two metrics is not sufficient, since there may be a blockage that causes NLOS issues. This issue was common in mmWave and hence vehicle parameters are essential to be considered while making forwarding decisions.</p></list-item><list-item><p>The use of AHP was not efficient since it requires training of the data and then it can select the best path. But here as per the current situation of the vehicles the path needs to be selected and also the movement of vehicles will not be the same in all the regions. Also, the addition of new criteria was difficult in this algorithm.</p></list-item></list></p><p>Several algorithms have been proposed for the process of routing. Dijkstra algorithm and random relay selection are proposed for routing and data forwarding (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_002">Cao et al., 2019</a>). QoS parameters are computed and estimated for the selection of routes. Since the movement of vehicles is dynamic and so, the management of the topologies is achieved by constructing the graphs.</p><p>The major problems identified in routing are as follows:<list id="j_ijssis-2021-012_list3" list-type="bullet"><list-item><p>The graph parameters are completely based on the past transmission history of the vehicles and the transmission of the vehicles depends on the channel metrics. Using these metrics, the graph was not able to predict the signal strengths with its neighboring vehicle. Consequently causing frequent handover.</p></list-item><list-item><p>The maintenance of graphs is complex due to mobility concerns, hence it needs large resource blocks and dynamic processing to manage the graph.</p></list-item><list-item><p>The random selection of radio networks with individual parameters may leads to poor performance of networks since the main constraints of QoS in this work is bandwidth or delay, i.e. it considers anyone from this, and hence the network selection is poor.</p></list-item></list></p><p>All of the above-highlighted gaps concerning handover, network selection, and routing are addressed in our proposed work.</p></sec><sec id="j_ijssis-2021-012_s_004"><div>Proposed system</div><p>This section is broken down into four sub-sections to describe the environment and expand each algorithm concerning handover, network selection, and routing in this proposed research work.</p><sec id="j_ijssis-2021-012_s_004_s_001"><div>System model</div><p>The proposed heterogeneous IoV network is designed with vehicles consisting of a 5G base station, LTE base station, RoadSide Unit (RSU), and vehicles. The entities that participates in this system are defined below.</p><p>Definition 1: Vehicle – the vehicle moves on a restricted path, i.e. on-road lane in which the path is pre-defined in a map. The moving speed of the vehicle depends on the vehicle. Vehicles have in-build GPS, using which their latitude and longitude information is gathered. The location of the vehicle and the speed of the vehicle is dynamic. Vehicles use DSRC and other advance Ran for data transmission. It transmits safety and non-safety data.</p><p>Definition 2: RSU – RSU is employed in IoV for performing communication with the infrastructure. This entity is static in the environment and also it enables DSRC for vehicles.</p><p>Definition 3: 5G mmWave base station (BS) – the BS is static and this allows to perform high speed–short-range communication. It can solve the lack of spectrum issue.</p><p>Definition 4: LTE BS – this BS is also static and it allows long-distance communication with higher bandwidth and comparatively high spectrum efficiency.</p><p>The proposed system model is depicted in <a ref-type="fig" href="#j_ijssis-2021-012_fig_002">Figure 2</a>, which composes all the above-defined entities into the system. The road lane has ‘n’ number of moving vehicles in their direction on the road. In this work, the handover is a decision that will be taken by the vehicle only when the current base station link is not good. But in case of sudden need in transmitting a safety application, it makes network selection process at that moments along with the consideration of data type as one of the parameters. Handover decision is the decision by which the need for handover is determined and it performs handover to the available network. For handover decision dynamic Q-learning in which the threshold is set as per the environment. If the handover has to be performed, it then selects a network from fuzzy-convolution neural network (F-CNN). For network selection, the fuzzy rules are defined and used in CNN. Then routing takes place by using an optimization algorithm called jellyfish algorithm that selects V2V pairs between source to destination and so, it is called V2V chain routing.</p><figure id="j_ijssis-2021-012_fig_002" fig-type="figure"><h2>Figure 2:</h2><figCaption><p>Proposed system model.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_002.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=7c8e1b2b5904d103545e0a04963db98c313496900499931f6daabcce70b1809b" class="mw-100"></img></figure></sec><sec id="j_ijssis-2021-012_s_004_s_002"><div>Handover decision</div><p>Handover decision by dynamic Q-learning, the dynamic means to use threshold concerning the available network. Dynamic Q-learning algorithm determines the need for handover by evaluating vehicle speed and signal strength. We set the threshold for signal strength using Shannon entropy rule as shown in the following equation: <disp-formula id="j_ijssis-2021-012_eq_001"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_001.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(1)</mtext></mtd><mtd><mi>S</mi><mrow><mo stretchy="false">(</mo><mrow><mi>s</mi><mi>s</mi></mrow><mo stretchy="false">)</mo></mrow><mo>=</mo><mi>E</mi><mrow><mo stretchy="false">[</mo><mrow><mo>−</mo><mspace width=".25em"/><mi>log</mi><mrow><mo stretchy="false">(</mo><mrow><mi>P</mi><mrow><mo stretchy="false">(</mo><mrow><mi>s</mi><mi>s</mi></mrow><mo stretchy="false">)</mo></mrow></mrow><mo stretchy="false">)</mo></mrow></mrow><mo stretchy="false">]</mo></mrow></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula>(1)where <italic>S</italic>(<italic>ss</italic>) denotes the Shannon entropy for signal strength that composes of <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_001.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi mathvariant="italic">ss</mi></math><tex-math/></alternatives></inline-formula> values for DSRC, mmWave, and LTE that range between (‒30 to ‒70 dBm). <italic>P</italic>(<italic>ss</italic>) denotes the probability of the signal strength (<a ref-type="fig" href="#j_ijssis-2021-012_fig_003">Figure 3</a>).</p><figure id="j_ijssis-2021-012_fig_003" fig-type="figure"><h2>Figure 3:</h2><figCaption><p>Workflow of dynamic Q-learning.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_003.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=7343cb6b31b0e31544f4f0cd228cea5dd72b2e6a5e79d9ebeb6c161b4f959ec0" class="mw-100"></img></figure><p>Let <italic>Q</italic>(<italic>S,A</italic>) represent state <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_002.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>S</mi></math><tex-math/></alternatives></inline-formula> and action <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_003.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>A</mi></math><tex-math/></alternatives></inline-formula> based on the <italic>Q</italic>-values. Each state <italic>S</italic> will have two parameters and this <italic>Q</italic>(<italic>S,A</italic>) is determined and updated in the rule. The temporal difference update rule is as follows: <disp-formula id="j_ijssis-2021-012_eq_002"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_002.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(2)</mtext></mtd><mtd><mi>Q</mi><mrow><mo stretchy="false">(</mo><mrow><mi>S</mi><mo>,</mo><mi>A</mi></mrow><mo stretchy="false">)</mo></mrow><mo>+</mo><mi>α</mi><mrow><mo stretchy="false">(</mo><mrow><mi>R</mi><mo>+</mo><mi>γ</mi><mi>Q</mi><mrow><mo stretchy="false">(</mo><mrow><mrow><mi>S</mi><mo>′</mo></mrow><mo>,</mo><mrow><mi>A</mi><mo>′</mo></mrow></mrow><mo stretchy="false">)</mo></mrow><mo>−</mo><mi>Q</mi><mrow><mo stretchy="false">(</mo><mrow><mi>S</mi><mo>,</mo><mi>A</mi></mrow><mo stretchy="false">)</mo></mrow></mrow><mo stretchy="false">)</mo></mrow><mo>→</mo><mi>Q</mi><mrow><mo stretchy="false">(</mo><mrow><mi>S</mi><mo>,</mo><mi>A</mi></mrow><mo stretchy="false">)</mo></mrow></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>The term <italic>Q</italic>(<italic>S</italic><sup><italic>΄</italic></sup><italic>,A</italic><sup><italic>΄</italic></sup>) defines next state and action <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_004.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>R</mi></math><tex-math/></alternatives></inline-formula> is the reward given by the agent, <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_005.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>γ</mi></math><tex-math/></alternatives></inline-formula> is the discount factor that is [0–1], then <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_006.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>α</mi></math><tex-math/></alternatives></inline-formula> is the learning rate [0–1], i.e. it denotes the step length to estimate the (<italic>S,A</italic>). The action is taken using <italic>ϵ-</italic>greedy policy where <italic>ϵ</italic> represents epsilon. The pseudo-code for dynamic Q-learning is given below to decide the decision for handover:</p><figure id="j_ijssis-2021-012_unfig_001" fig-type="figure"><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_unfig_001.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=007b7cb6f8dc5dc92c34cf0a8e193ec40fcd496ffda4727cc93cbb39fa03cf8a" class="mw-100"></img></figure></sec><sec id="j_ijssis-2021-012_s_004_s_003"><div>Network selection</div><p>Network selection is the process of selecting a network from the available RANs. F-CNN algorithm is applied for network selection. The CNN is designed with layers of convolution, max-pooling, and fully connected layers. The layers are employed with fuzzy rules that are defined from the metrics signal strength, the distance between BS and vehicle, vehicle density in serving BS, data type (safety or non-safety), and line of sight. The definition for each metric is depicted below.</p><p>Definition 1: Signal strength – signal strength defines the SNR which gives the number of signals. A channel will compose noise as well as signal, the high the noise, the channel is unfit for transmission. The SNR (<italic>S</italic><sub><italic>r</italic></sub>) is determined from signal power <italic>P</italic><sub><italic>s</italic></sub>, and noise <italic>P</italic><sub><italic>N</italic></sub> respectively. The formulation is: <disp-formula id="j_ijssis-2021-012_eq_003"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_003.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(3)</mtext></mtd><mtd><msub><mrow><mi>S</mi></mrow><mrow><mi>r</mi></mrow></msub><mo>=</mo><mfrac><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>s</mi></mrow></msub></mrow><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>n</mi></mrow></msub></mrow></mfrac></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>Definition 2: Distance between BS and vehicle – the distance between BS and a vehicle is estimated using Euclidean distance. This measure defines the stability of the link, as the distance increases the link will be unstable and when the distance decreases the link will be stronger. Euclidean distance is computed using the following equation: <disp-formula id="j_ijssis-2021-012_eq_004"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_004.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(4)</mtext></mtd><mtd><msub><mrow><mi>D</mi></mrow><mrow><mo stretchy="false">(</mo><msub><mrow><mi>L</mi></mrow><mrow><mi>B</mi><mi>S</mi><mo>,</mo></mrow></msub><msub><mrow><mi>L</mi></mrow><mrow><mi>V</mi></mrow></msub><mo stretchy="false">)</mo></mrow></msub><mo>=</mo><msqrt><mrow><msup><mrow><mo stretchy="false">(</mo><mrow><mi>x</mi><mo>−</mo><msub><mrow><mi>x</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow><mo stretchy="false">)</mo></mrow><mn>2</mn></msup><mo>+</mo><msup><mrow><mo stretchy="false">(</mo><mrow><mi>y</mi><mo>−</mo><msub><mrow><mi>y</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow><mo stretchy="false">)</mo></mrow><mn>2</mn></msup></mrow></msqrt></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>For computing distance, the coordinate points of the BS and vehicle is used. Distance <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_007.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><msub><mrow><mi>D</mi></mrow><mrow><mo stretchy="false">(</mo><msub><mrow><mi>L</mi></mrow><mrow><mi>B</mi><mi>S</mi></mrow></msub><msub><mrow><mi>L</mi></mrow><mrow><mi>V</mi></mrow></msub><mo stretchy="false">)</mo></mrow></msub></math><tex-math/></alternatives></inline-formula> is determined from the BS location coordinates of (<italic>x,y</italic>), and vehicle location coordinates of (<italic>x</italic><sub>1</sub><italic>,y</italic><sub>1</sub>), respectively. The location of BS is fixed and so it requires to know only the vehicle coordinate for distance estimation.</p><p>Definition 3: Vehicle density – the density of vehicle <italic>V</italic><sub><italic>D</italic></sub> denotes the number of vehicles that are connected with that particular BS. <disp-formula id="j_ijssis-2021-012_eq_005"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_005.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(5)</mtext></mtd><mtd><msub><mrow><mi>V</mi></mrow><mrow><mi>D</mi></mrow></msub><mo>=</mo><mo>∑</mo><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mi>C</mi><mi>L</mi></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mi>N</mi><mi>L</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula>(5)where <italic>N</italic><sub><italic>CL</italic></sub> and <italic>N</italic><sub><italic>NL</italic></sub> represents the number of connected links and number of new links.</p><p>Definition 4: Data type – the data type in vehicles are two, they are safety and non-safety. In this work, safety is denoted as 0 and non-safety as 1. The safety messages will be of traffic information, high-speed vehicle information. This type of data has a higher priority in transmission than the non-safety data.</p><p>Definition 5: LoS – line of sight defines the direct contact between the vehicle and BS without any obstacles that block the signals. For transmission, LoS is only preferred and the signals in Non-LoS are not preferred.</p><p>The above five metrics involve the development of fuzzy rules. The fuzzy logic deals with the decision-making by the defined rules as shown in <a ref-type="table" href="#j_ijssis-2021-012_tab_001">Table 1</a>. The mmWave signals will be chosen for any type of traffic, but only when the LoS is present since blockage of mmWave leads to poor performance, in case of blockage the vehicle selection will be 4G LTE.</p><table-wrap id="j_ijssis-2021-012_tab_001" position="float"><label>Table 1.</label><caption><p>Fuzzy rules.</p></caption><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1"/><th align="center" rowspan="1" colspan="5">Input</th><th align="left" rowspan="1" colspan="1"/></tr><tr><th align="left" rowspan="1" colspan="1">Rule number</th><th align="left" rowspan="1" colspan="1"><italic>S</italic><sub><italic>r</italic></sub></th><th align="left" rowspan="1" colspan="1">Distance</th><th align="left" rowspan="1" colspan="1"><italic>V</italic><sub><italic>D</italic></sub></th><th align="left" rowspan="1" colspan="1">Data type</th><th align="left" rowspan="1" colspan="1">LoS</th><th align="left" rowspan="1" colspan="1">Output</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">R1</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R2</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R3</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R4</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R5</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R6</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R7</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R8</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R9</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R10</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R11</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R12</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R13</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R14</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R15</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R16</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R17</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R18</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R19</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R20</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R21</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R22</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R23</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R24</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R25</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R26</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R27</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R28</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R29</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R30</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R31</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R32</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr></tbody></table></table-wrap><p>The fuzzy logic method operates with the IF-THEN rules in the interference engine. The input is in crisp values that are converted into a fuzzy set. As per the fuzzy rule, the interference engine constructs membership function between [0,1]. The fuzzy logic operations are built into CNN. <a ref-type="fig" href="#j_ijssis-2021-012_fig_004">Figure 4</a> depicts the constructed fuzzy logic with CNN. The output high (H), medium (M), and low (L) denotes as follows: <disp-formula id="j_ijssis-2021-012_eq_006"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_006.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mrow><mo stretchy="false">(</mo><mrow><mi>H</mi><mo>,</mo><mi>M</mi><mo>,</mo><mi>L</mi></mrow><mo stretchy="false">)</mo></mrow><mo>→</mo><mrow><mo stretchy="false">(</mo><mrow><mi mathvariant="normal">mmWave</mi><mo>,</mo><mspace width=".25em"/><mi mathvariant="normal">LTE</mi><mo>,</mo><mspace width=".25em"/><mi mathvariant="normal">DSRC</mi></mrow><mo stretchy="false">)</mo></mrow></math><tex-math/></alternatives></disp-formula></p><figure id="j_ijssis-2021-012_fig_004" fig-type="figure"><h2>Figure 4:</h2><figCaption><p>Fuzzy-convolutional neural network.</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_004.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=dd1de1b23b1402cf8df6d99161a6253bb07b75b28cde35656d232b19feac4e8f" class="mw-100"></img></figure><p>A pseudo-code below is illustrated based on the workflow of this fuzzy-CNN algorithm:</p><figure id="j_ijssis-2021-012_unfig_002" fig-type="figure"><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_unfig_002.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=29c2f59577776976b5bd1faa22634c6ad37cf80d7160d34fb96213f414613d7d" class="mw-100"></img></figure><p>The use of CNN will give results for multiple vehicles at the same time by parallel processing. The proposed fuzzy-CNN is composed of 32 rules, which are defined from five parameters. Since the CNN can process in parallel, the 32 rules will be processed in the convolution layer. According to the selected network, the requested vehicle will handover from the current network to the target network.</p></sec><sec id="j_ijssis-2021-012_s_004_s_004"><div>Optimized routing using jelly fish optimization algorithm</div><p>The process of routing is carried out using jellyfish optimization algorithm where the vehicles are formed like V2V pairs, hence the name V2V chain routing. The routes are selected by computing the objective function using channel metrics (SNR (<italic>s</italic><sub><italic>r</italic></sub>), link quality (<italic>l</italic><sub><italic>q</italic></sub>)), vehicle metrics (Speed (<italic>s</italic><sub><italic>p</italic></sub>), Relative direction (<italic>R</italic><sub><italic>d</italic></sub>)), and vehicle performance metrics (Delay (<italic>D</italic><sub><italic>l</italic></sub>), throughput (<italic>T</italic><sub><italic>p</italic></sub>)).</p><p>A time control mechanism is used to switch between active or passive movements in this algorithm. The time control <italic>c</italic>(<italic>t</italic>) is formulated and computed using the following equations: <disp-formula id="j_ijssis-2021-012_eq_007"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_007.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(6)</mtext></mtd><mtd><mi>c</mi><mrow><mo stretchy="false">(</mo><mi>t</mi><mo stretchy="false">)</mo></mrow><mo>=</mo><mo>|</mo><mrow><mo stretchy="false">(</mo><mrow><mn>1</mn><mo>‒</mo><mfrac><mi>t</mi><mrow><msub><mrow><mi mathvariant="normal">Max</mi></mrow><mrow><mi>i</mi><mi>t</mi><mi>e</mi></mrow></msub></mrow></mfrac></mrow><mo stretchy="false">)</mo></mrow><mo>×</mo><mrow><mo stretchy="false">(</mo><mrow><mn>2</mn><mo>×</mo><mi mathvariant="normal">rand</mi><mrow><mo stretchy="false">(</mo><mrow><mn>0</mn><mo>,</mo><mn>1</mn></mrow><mo stretchy="false">)</mo></mrow><mo>‒</mo><mn>1</mn></mrow><mo stretchy="false">)</mo></mrow><mo>|</mo></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>when rand(0,1) > (1‒<italic>c</italic>(<italic>t</italic>)), then passive motion: <disp-formula id="j_ijssis-2021-012_eq_008"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_008.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(7)</mtext></mtd><mtd><mi mathvariant="normal">rand</mi><mspace width=".25em"/><mrow><mo stretchy="false">(</mo><mrow><mn>0</mn><mo>,</mo><mn>1</mn></mrow><mo stretchy="false">)</mo></mrow><mo><</mo><mrow><mo stretchy="false">(</mo><mrow><mn>1</mn><mo>‒</mo><mi>c</mi><mrow><mo stretchy="false">(</mo><mi>t</mi><mo stretchy="false">)</mo></mrow></mrow><mo stretchy="false">)</mo></mrow><mspace width=".25em"/><mi mathvariant="normal">then</mi><mspace width=".25em"/><mi mathvariant="normal">active</mi><mspace width=".25em"/><mi mathvariant="normal">motion</mi></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>Here the jellyfish are assumed as vehicles and the ocean is assumed as road lane where the vehicle moves in different speed.</p><p>The ocean current direction represented as <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_008.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mover accent="true"><mrow><mi>O</mi><mi>C</mi></mrow><mrow><mo stretchy="true">→</mo></mrow></mover></math><tex-math/></alternatives></inline-formula> and it is mathematically given as below:</p><p>Let: <disp-formula id="j_ijssis-2021-012_eq_009"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_009.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(8)</mtext></mtd><mtd><mover accent="true"><mrow><mi>O</mi><mi>C</mi></mrow><mrow><mo stretchy="true">→</mo></mrow></mover><mo>=</mo><mfrac><mn>1</mn><mrow><msub><mrow><mi>V</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow></mfrac><mo>=</mo><msup><mrow><mi>X</mi></mrow><mo>*</mo></msup><mo>‒</mo><msub><mrow><mi>e</mi></mrow><mrow><mi>c</mi></mrow></msub><mi>μ</mi></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>Then: <disp-formula id="j_ijssis-2021-012_eq_010"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_010.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(9)</mtext></mtd><mtd><mover accent="true"><mrow><mi>O</mi><mi>C</mi></mrow><mrow><mo stretchy="true">→</mo></mrow></mover><mo>=</mo><msup><mrow><mi>X</mi></mrow><mo>*</mo></msup><mo>‒</mo><msub><mrow><mi>d</mi></mrow><mrow><mi>f</mi><mi>f</mi></mrow></msub></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula>(9)where ‘<italic>V</italic><sub><italic>p</italic></sub>’ is the vehicle density. <italic>X</italic><sup>*</sup> denotes the best location, <italic>μ</italic> is the mean location, and <italic>e</italic><sub><italic>c</italic></sub> is the attraction factor, here the attraction of on destination. Then, the objective function is defined to select a best route. This function OF is formulated as follows: <disp-formula id="j_ijssis-2021-012_eq_011"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_011.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(10)</mtext></mtd><mtd><mi mathvariant="normal">OF</mi><mrow><mo stretchy="false">(</mo><mrow><mi>M</mi><mi>s</mi></mrow><mo stretchy="false">)</mo></mrow><mo>=</mo><mo>∑</mo><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>s</mi></mrow><mrow><mi>r</mi></mrow></msub><mo>,</mo><msub><mrow><mi>l</mi></mrow><mrow><mi>q</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>s</mi></mrow><mrow><mi>p</mi></mrow></msub><mo>,</mo><msub><mrow><mi>R</mi></mrow><mrow><mi>d</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>D</mi></mrow><mrow><mi>l</mi></mrow></msub><mo>,</mo><msub><mrow><mi>T</mi></mrow><mrow><mi>p</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p><italic>Ms</italic> represents a set of parameters in which the delay and speed must be minimum and all the other parameters can be a maximum value for the selection of the routes. Here the OF is applied for the complete route, since this work selects an optimal route from the available routes. The metrics are estimated from the channel: <disp-formula id="j_ijssis-2021-012_eq_012"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_012.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(11)</mtext></mtd><mtd><msub><mrow><mi>l</mi></mrow><mrow><mi>q</mi></mrow></msub><mo>=</mo><mfrac><mn>1</mn><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>f</mi></mrow></msub><mo>×</mo><msub><mrow><mi>P</mi></mrow><mrow><mi>r</mi></mrow></msub></mrow></mfrac></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula>(11) <disp-formula id="j_ijssis-2021-012_eq_013"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_013.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(12)</mtext></mtd><mtd><msub><mrow><mi>R</mi></mrow><mrow><mi>d</mi></mrow></msub><mo>=</mo><mn>2</mn><mi>r</mi><mspace width=".25em"/><mi>sin</mi><mspace width=".25em"/><msqrt><mrow><msup><mrow><mi>sin</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mrow><mfrac><mrow><msub><mrow><mi>Δ</mi></mrow><mrow><mi>l</mi><mi>a</mi></mrow></msub></mrow><mn>2</mn></mfrac></mrow><mo stretchy="false">)</mo></mrow></mrow></msqrt><mo>+</mo><mspace width=".25em"/><mi>cos</mi><mrow><mo stretchy="false">(</mo><mrow><mi>l</mi><msub><mrow><mi>a</mi></mrow><mrow><mi>v</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow><mo>×</mo><mspace width=".25em"/><mi>cos</mi><mrow><mo stretchy="false">(</mo><mrow><mi>l</mi><msub><mrow><mi>a</mi></mrow><mrow><mi>n</mi><msub><mrow><mi>p</mi></mrow><mrow><mi>i</mi></mrow></msub></mrow></msub></mrow><mo stretchy="false">)</mo></mrow><mo>×</mo><msup><mrow><mi>sin</mi></mrow><mn>2</mn></msup><mrow><mo stretchy="false">(</mo><mrow><mfrac><mrow><msub><mrow><mi>Δ</mi></mrow><mrow><mi>ln</mi></mrow></msub></mrow><mn>2</mn></mfrac></mrow><mo stretchy="false">)</mo></mrow></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula>(12) <disp-formula id="j_ijssis-2021-012_eq_014"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_014.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(13)</mtext></mtd><mtd><msub><mrow><mi>D</mi></mrow><mrow><mi>l</mi></mrow></msub><mo>=</mo><mfrac><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>L</mi></mrow></msub></mrow><mi>b</mi></mfrac></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula>(13)where <italic>P</italic><sub><italic>f</italic></sub><italic>P</italic><sub><italic>r</italic></sub> represents the number of transmitted and the received packets in the same link between two vehicles, (<italic>la</italic>,<italic>ln</italic>) represents the latitude and longitude, (<italic>la</italic><sub><italic>v</italic></sub>,<italic>ln</italic><sub><italic>v</italic></sub>) represents the vehicle location, and (<italic>la</italic><sub><italic>np</italic></sub>, <italic>ln</italic><sub><italic>np</italic></sub>) represents the next hop location and r is the radius. <italic>P</italic><sub><italic>L</italic></sub>, <italic>b</italic> represents packet length and bit rate, i.e. transmission speed in bits per second that are used to compute the delay estimation.</p><p><a ref-type="disp-formula" href="#j_ijssis-2021-012_eq_011">Equation 10</a> defines the objective function through which the optimal route is selected using jellyfish optimization algorithm.</p><p>The performance of the proposed HO, network selection, and routing algorithms are evaluated in the next section.</p></sec></sec><sec id="j_ijssis-2021-012_s_005"><div>Simulation results</div><p>The section is split into three parts as simulation setup and specifications, comparative analysis, and result discussion. The simulation details and the parameters are discussed in detail in this section.</p><sec id="j_ijssis-2021-012_s_005_s_001"><div>Simulation setup and specifications</div><p>The proposed work is simulated using OMNeT++. <a ref-type="table" href="#j_ijssis-2021-012_tab_002">Table 2</a> shows the simulation parameters assumed in our proposed work.</p><table-wrap id="j_ijssis-2021-012_tab_002" position="float"><label>Table 2.</label><caption><p>Simulation specifications.</p></caption><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Parameter</th><th align="center" rowspan="1" colspan="1">Range/Value</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Simulation area</td><td align="center" rowspan="1" colspan="1">2,500 m × 2,500 m</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of vehicles</td><td align="center" rowspan="1" colspan="1">100</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of 5G mmWave BSs</td><td align="center" rowspan="1" colspan="1">2</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of 4G LTE BSs</td><td align="center" rowspan="1" colspan="1">2</td></tr><tr><td align="left" rowspan="1" colspan="1">Vehicle mobility type</td><td align="center" rowspan="1" colspan="1">Linear mobility</td></tr><tr><td align="left" rowspan="1" colspan="1">Vehicle speed</td><td align="center" rowspan="1" colspan="1">10-40 m/s</td></tr><tr><td align="left" rowspan="1" colspan="2">Transmission range</td></tr><tr><td align="left" rowspan="1" colspan="1"> DSRC</td><td align="center" rowspan="1" colspan="1">300 m (Max)</td></tr><tr><td align="left" rowspan="1" colspan="1"> mmWave</td><td align="center" rowspan="1" colspan="1">~500 m</td></tr><tr><td align="left" rowspan="1" colspan="1"> LTE</td><td align="center" rowspan="1" colspan="1">100 km (Max)</td></tr><tr><td align="left" rowspan="1" colspan="1">Transmission rate</td><td align="center" rowspan="1" colspan="1">3-5 packets per second</td></tr><tr><td align="left" rowspan="1" colspan="1">Packet size</td><td align="center" rowspan="1" colspan="1">512 bytes</td></tr><tr><td align="left" rowspan="1" colspan="1">Simulation time</td><td align="center" rowspan="1" colspan="1">1,000 sec</td></tr></tbody></table></table-wrap></sec><sec id="j_ijssis-2021-012_s_005_s_002"><div>Comparative results</div><p>The comparative analysis gives the obtained results in comparative graphs. The proposed work is compared with previous works that use conventional RSS-based selection, TOPSIS, ANDSF, and V2I-MoloHA methods relating to handover, network selection, and routing issues. It is a multi-criteria decision-making algorithm that processes with more than one criterion. The parameters that are considered for the evaluation are mean handover, handover failure, throughput, and delay.</p><sec id="j_ijssis-2021-012_s_005_s_002_s_001"><div>Mean handover and handover failure</div><p>The mean handover is the number of successful handovers of a vehicle from one network to another. Handover failure is defined as the number of unsuccessful handovers that happen due to poor decision-making.</p><p>The lesser mean handover denotes the better performance of the proposed algorithm as it has minimized the number of unnecessary handovers in the network. In previous work of TOPSIS, it was used for the selection of network that fails to perform proper ranking. Similarly, the use of parameters for the selection of network was either based on vehicle characteristic or environmental characteristic which leads to select the best target network that eventually increases mean handover along with the increase in the handover failure.</p><p>The proposed dynamic Q-learning algorithm can learn the vehicle environment in a particular surrounding. The prediction of handover requirement from the vehicle speed and signal strength is efficient. Further to the prediction, we perform a selection of networks using the F-CNN algorithm for selecting a network by analyzing the metrics of the particular vehicle. The process of prediction and network selection in this work tends to improve the performance of the handover-based metrics.</p><p><a ref-type="fig" href="#j_ijssis-2021-012_fig_005">Figures 5</a> and <a ref-type="fig" href="#j_ijssis-2021-012_fig_006">6</a> illustrate the mean handover and handover failure concerning the increase in vehicle speed. The improvement in the performances of HO failure rate and mean handover is due to the handover decisions made by dynamic Q-learning algorithm and appropriate selection of networks due to fuzzy-CNN. The mean handover in the proposed work decreases with the increase in vehicle speed and hence, suitable for large-scale environments. Besides, the decrease in mean handover reduces the HO failure counts. In general with the increase in vehicle speed, the handover failure occurs but as the proposed work uses Q-learning for predicting the requirement of handover before that of the network selection it can take an absolute decision at the increase of vehicle speed. The main reasons behind the degradation of handover are illustrated below.</p><figure id="j_ijssis-2021-012_fig_005" fig-type="figure"><h2>Figure 5:</h2><figCaption><p>Comparison of mean handover (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>; <a ref-type="bibr" href="#j_ijssis-2021-012_ref_012">Sheng et al., 2018</a>).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_005.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=3e5c8fda9455086f35cf5bdb7f32631a948797d41c755dfa6c51e5edcab42ac5" class="mw-100"></img></figure><figure id="j_ijssis-2021-012_fig_006" fig-type="figure"><h2>Figure 6:</h2><figCaption><p>Comparison of HO failure (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>; <a ref-type="bibr" href="#j_ijssis-2021-012_ref_012">Sheng et al., 2018</a>).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_006.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=055e08cf21dda6ba730cf94a1888636b00b7aa3af0e07ae95f1a9e1562f5ca00" class="mw-100"></img></figure><p>Selection of parameters to select the suitable network which requires considering vehicle metrics as well as the BS metrics:<list id="j_ijssis-2021-012_list4" list-type="bullet"><list-item><p>The number of handovers increases due to the absence of prediction of the vehicle regarding the need for handover. This leads to an increase the number of unnecessary handovers which also requires large resource blocks for performing the computations.</p></list-item></list></p><p>The handover failure rate HO<sub><italic>FR</italic></sub> is computed mathematically based on the below equation: <disp-formula id="j_ijssis-2021-012_eq_015"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_015.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(14)</mtext></mtd><mtd><msub><mrow><mi mathvariant="normal">HO</mi></mrow><mrow><mi>F</mi><mi>R</mi></mrow></msub><mo>=</mo><mfrac><mrow><msub><mrow><mi mathvariant="normal">HO</mi></mrow><mrow><mi>F</mi></mrow></msub></mrow><mrow><msub><mrow><mi mathvariant="normal">HO</mi></mrow><mrow><mi>S</mi></mrow></msub><mo>+</mo><msub><mrow><mi mathvariant="normal">HO</mi></mrow><mrow><mi>F</mi></mrow></msub></mrow></mfrac></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>The terms<italic>HO<sub>F</sub></italic> and <italic>HO<sub>S</sub></italic> represents the number of handover failure and handover success, respectively. According to the count of these measurements, the handover failure rate is determined. The handover failure is caused because of the poor handover decision; hereby the proposed work first predicts the handover requirement from the vehicle request by learning the environment and then if the decision is to perform handover, it selects a target network. From the comparative graph, the average value of failure rate in proposed is 0.015, while the previous work achieves 0.13, 0.04, 0.07, and 0.03 in conventional, TOPSIS, ANDSF-HO, and V2I-MoLoHA, respectively. The minimization of handover failure reflects on absolute handover decision. Similarly, the reduction in the number of handover shows that the unnecessary handover is reduced by efficient prediction and network selection in proposed.</p><p><a ref-type="table" href="#j_ijssis-2021-012_tab_003">Table 3</a> gives a comparison on the average values estimated from the performance of conventional method, TOPSIS, ANDSF-HO, and V2I-MoLoHA in terms of number of handover and handover failure. Then the improvement percentage of handover efficiency is depicted in the above table. The handover efficiency impact on other network parameters that enhances overall network efficiency.</p><table-wrap id="j_ijssis-2021-012_tab_003" position="float"><label>Table 3.</label><caption><p>Comparison of HO efficiency.</p></caption><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Method</th><th align="center" rowspan="1" colspan="1">Average number of HO</th><th align="center" rowspan="1" colspan="1">Better efficiency</th><th align="center" rowspan="1" colspan="1">Average HO<sub><italic>FR</italic></sub></th><th align="center" rowspan="1" colspan="1">Better efficiency</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Conventional</td><td align="center" rowspan="1" colspan="1">5.51</td><td align="center" rowspan="1" colspan="1">55%</td><td align="center" rowspan="1" colspan="1">0.133</td><td align="center" rowspan="1" colspan="1">90%</td></tr><tr><td align="left" rowspan="1" colspan="1">TOPSIS</td><td align="center" rowspan="1" colspan="1">2.15</td><td align="center" rowspan="1" colspan="1">20%</td><td align="center" rowspan="1" colspan="1">0.041</td><td align="center" rowspan="1" colspan="1">40%</td></tr><tr><td align="left" rowspan="1" colspan="1">ANDSF-HO</td><td align="center" rowspan="1" colspan="1">3.57</td><td align="center" rowspan="1" colspan="1">30%</td><td align="center" rowspan="1" colspan="1">0.069</td><td align="center" rowspan="1" colspan="1">60%</td></tr><tr><td align="left" rowspan="1" colspan="1">V2I-MoLoHA</td><td align="center" rowspan="1" colspan="1">3.03</td><td align="center" rowspan="1" colspan="1">25%</td><td align="center" rowspan="1" colspan="1">0.029</td><td align="center" rowspan="1" colspan="1">20%</td></tr><tr><td align="left" rowspan="1" colspan="1">Proposed</td><td align="center" rowspan="1" colspan="1">1.30</td><td align="center" rowspan="1" colspan="1">–</td><td align="center" rowspan="1" colspan="1">0.01</td><td align="center" rowspan="1" colspan="1">–</td></tr></tbody></table></table-wrap></sec><sec id="j_ijssis-2021-012_s_005_s_002_s_002"><div>Throughput, delay and packet loss</div><p>Throughput is one of the significant performances metric in a network and it is mathematically computed using the formula as follows: <disp-formula id="j_ijssis-2021-012_eq_016"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_016.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(15)</mtext></mtd><mtd><mi>T</mi><mo>=</mo><mfrac><mrow><msub><mrow><mi>P</mi></mrow><mrow><mi>s</mi><mi>z</mi></mrow></msub></mrow><mrow><msub><mrow><mi>R</mi></mrow><mrow><mi>t</mi><mi>t</mi></mrow></msub></mrow></mfrac><mo>×</mo><mfrac><mrow><mn>1.2</mn></mrow><mrow><mi>P</mi><msup><mrow><mi>L</mi></mrow><mrow><mn>0.5</mn></mrow></msup></mrow></mfrac></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><p>The throughput <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_009.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>T</mi></math><tex-math/></alternatives></inline-formula> is estimated from the packet size <italic>P</italic><sub><italic>SZ</italic></sub>, round trip time <italic>R</italic><sub><italic>tt</italic></sub> and packet loss <italic>PL</italic>.</p><p><a ref-type="fig" href="#j_ijssis-2021-012_fig_007">Figures 7</a> and <a ref-type="fig" href="#j_ijssis-2021-012_fig_008">8</a> show the graphs for throughput, and delay. From <a ref-type="fig" href="#j_ijssis-2021-012_fig_007">Figures 7</a> and <a ref-type="fig" href="#j_ijssis-2021-012_fig_008">8</a>, there is an increase in the throughput and decrease in delay when compared to the existing techniques. This is due to the optimal selection of routes using jellyfish optimization algorithm. The graph shows little increase, and drops in the delay. The end-to-end delay is determined in terms of transmission delay between the relay vehicles from the source vehicle to the destination vehicle. The end-to-end delay (<italic>EE</italic><sub><italic>D</italic></sub>) is determined as follows: <disp-formula id="j_ijssis-2021-012_eq_017"><label>()</label><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_eq_017.png"></graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="block"><mtable><mlabeledtr><mtd><mtext>(16)</mtext></mtd><mtd><mi>E</mi><msub><mrow><mi>E</mi></mrow><mrow><mi>D</mi></mrow></msub><mo>=</mo><mfrac><mrow><mi>N</mi><mi>b</mi><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mrow><mrow><mi>R</mi><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mrow></mfrac><mo>+</mo><mfrac><mrow><mi>N</mi><mi>b</mi><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mrow><mrow><mi>R</mi><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mrow></mfrac><mo>+</mo><mo>⋯</mo><mi>…</mi><mo>+</mo><mfrac><mrow><mi>N</mi><mi>b</mi><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mi>m</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mrow><mrow><mi>R</mi><mrow><mo stretchy="false">(</mo><mrow><msub><mrow><mi>N</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>,</mo><msub><mrow><mi>N</mi></mrow><mrow><mi>m</mi></mrow></msub></mrow><mo stretchy="false">)</mo></mrow></mrow></mfrac></mtd></mlabeledtr></mtable></math><tex-math/></alternatives></disp-formula></p><figure id="j_ijssis-2021-012_fig_007" fig-type="figure"><h2>Figure 7:</h2><figCaption><p>Comparison of throughput (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>; <a ref-type="bibr" href="#j_ijssis-2021-012_ref_012">Sheng et al., 2018</a>).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_007.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=08567be3e13fa07225c15570ac6a28b13ce573313174e97d12ce9706261c0e82" class="mw-100"></img></figure><figure id="j_ijssis-2021-012_fig_008" fig-type="figure"><h2>Figure 8:</h2><figCaption><p>Comparison of end-to-end delay (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>; <a ref-type="bibr" href="#j_ijssis-2021-012_ref_012">Sheng et al., 2018</a>).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_008.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_008.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=37df6a93aea33af2bafc280bfc1445624f78c5b86ce281b1b78ed6da7020ee3a" class="mw-100"></img></figure><p>Let the vehicles in a route be represented as <italic>N</italic><sub>0</sub>, <italic>N</italic><sub>1</sub>, <italic>N</italic><sub>2, </sub>…, <italic>N</italic><sub><italic>n</italic></sub>, <italic>N</italic><sub><italic>m</italic></sub> for which the number of bits in each node is denoted as <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_010.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi mathvariant="italic">Nb</mi></math><tex-math/></alternatives></inline-formula> and the rate of transmission is <italic>R</italic>. The <italic>N</italic><sub>0</sub> is the source vehicle node, <italic>N</italic><sub><italic>m</italic></sub> is the destination vehicle node, while the nodes are the relay. In accordance to the estimation of the delay a better efficiency in the route selection is analyzed. In a route, the delay occur between every pair of vehicle due to the use of signal strength and hence the delay is predicted for each pair and end-to-end delay from the source to destination is determined.</p><p>The comparative results depict that proposed work is better than the previous conventional method, TOPSIS, ANDSF-HO, and V2I-MoLoHA. Among all the previous work, the conventional method of using only signal strength results in poor performance due to the growth of multiple challenges in data transmission of vehicles. <a ref-type="table" href="#j_ijssis-2021-012_tab_004">Table 4</a> illustrates the mean value determined for each work in the performance of throughput and delay. Based on the mean throughput and delay, the percentage of improvement is proposed than the existing works. As per the comparison, a minimum of 23% and a maximum of 46% is better performance than the previous methods in this network (<a ref-type="table" href="#j_ijssis-2021-012_tab_005">Table 5</a>).</p><table-wrap id="j_ijssis-2021-012_tab_004" position="float"><label>Table 4.</label><caption><p>Comparison of throughput and delay.</p></caption><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Method</th><th align="center" rowspan="1" colspan="1">Mean <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_011.png"></inline-graphic><math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mi>T</mi></math><tex-math/></alternatives></inline-formula> (kbps)</th><th align="center" rowspan="1" colspan="1">Better efficiency</th><th align="center" rowspan="1" colspan="1">Average delay (ms)</th><th align="center" rowspan="1" colspan="1">Better efficiency</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Conventional</td><td align="center" rowspan="1" colspan="1">13.7</td><td align="center" rowspan="1" colspan="1">46%</td><td align="center" rowspan="1" colspan="1">39</td><td align="center" rowspan="1" colspan="1">21%</td></tr><tr><td align="left" rowspan="1" colspan="1">TOPSIS</td><td align="center" rowspan="1" colspan="1">35.96</td><td align="center" rowspan="1" colspan="1">23%</td><td align="center" rowspan="1" colspan="1">30</td><td align="center" rowspan="1" colspan="1">12%</td></tr><tr><td align="left" rowspan="1" colspan="1">ANDSF-HO</td><td align="center" rowspan="1" colspan="1">25</td><td align="center" rowspan="1" colspan="1">34%</td><td align="center" rowspan="1" colspan="1">37</td><td align="center" rowspan="1" colspan="1">19%</td></tr><tr><td align="left" rowspan="1" colspan="1">V2I-MoLoHA</td><td align="center" rowspan="1" colspan="1">31.89</td><td align="center" rowspan="1" colspan="1">27%</td><td align="center" rowspan="1" colspan="1">34</td><td align="center" rowspan="1" colspan="1">16%</td></tr><tr><td align="left" rowspan="1" colspan="1">Proposed</td><td align="center" rowspan="1" colspan="1">58.89</td><td align="center" rowspan="1" colspan="1">–</td><td align="center" rowspan="1" colspan="1">18</td><td align="center" rowspan="1" colspan="1">–</td></tr></tbody></table></table-wrap><table-wrap id="j_ijssis-2021-012_tab_005" position="float"><label>Table 5.</label><caption><p>Comparison of packet loss.</p></caption><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Method</th><th align="center" rowspan="1" colspan="1">Packet loss (%)</th><th align="center" rowspan="1" colspan="1">Better efficiency</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Conventional</td><td align="center" rowspan="1" colspan="1">48</td><td align="center" rowspan="1" colspan="1">21%</td></tr><tr><td align="left" rowspan="1" colspan="1">TOPSIS</td><td align="center" rowspan="1" colspan="1">32.4</td><td align="center" rowspan="1" colspan="1">12%</td></tr><tr><td align="left" rowspan="1" colspan="1">ANDSF-HO</td><td align="center" rowspan="1" colspan="1">24</td><td align="center" rowspan="1" colspan="1">19%</td></tr><tr><td align="left" rowspan="1" colspan="1">V2I-MoLoHA</td><td align="center" rowspan="1" colspan="1">18.8</td><td align="center" rowspan="1" colspan="1">16%</td></tr><tr><td align="left" rowspan="1" colspan="1">Proposed</td><td align="center" rowspan="1" colspan="1">12</td><td align="center" rowspan="1" colspan="1">–</td></tr></tbody></table></table-wrap><p>One of the major reasons for the increase in packet losses is due to the link degradation problems which occur mainly due to high vehicle density, poor signal quality. In our work, we have proposed a jellyfish optimization algorithm for the selection of routes taking into account vehicle metrics, channel metrics, and transmission metrics. <a ref-type="fig" href="#j_ijssis-2021-012_fig_009">Figure 9</a> shows the graphical plots where there is a decrease in the packet loss concerning the vehicle density due to consideration of multiple metrics for selecting the shortest path. From the figure, when there is an increase in the vehicle density, there are possibilities of an increase in data transmission due to which the packet loss can increase. However, in our work, the packet losses are minimized due to the selection of optimized routes. The previous works of TOPSIS, ANDSF-HO, and V2I-MoLoHA fails to select the best route among the available route between source and destination. Therefore, the deployment of an algorithm for selecting the best route minimizes packet loss. Even the vehicle density increases there is a reduction in packet loss since not all vehicles will use the route for transmission. That is to say, the vehicles nearby will not require data transmission. Due to this reason, the packet loss in the proposed work does not increase suddenly with the increase in the number of vehicles.</p><figure id="j_ijssis-2021-012_fig_009" fig-type="figure"><h2>Figure 9:</h2><figCaption><p>Comparison on packet loss (<a ref-type="bibr" href="#j_ijssis-2021-012_ref_010">Ndashimye et al., 2020</a>; <a ref-type="bibr" href="#j_ijssis-2021-012_ref_012">Sheng et al., 2018</a>).</p></figCaption><img xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_fig_009.jpg" src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_009.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=1439d9dead49c156ab3acbc1c1230896fd05f7a75067574d0981beee475cfea4" class="mw-100"></img></figure></sec></sec></sec><sec id="j_ijssis-2021-012_s_006"><div>Result discussion</div><p>In this section, the obtained results are discussed concerning the evaluation metrics used in this work. The handover-based metrics and data transmission-based metrics are discussed.</p><p>First, number of handover and handover failure: handover is the process of changing the RAN connectivity from one network to another. In general, 5G is a heterogeneous network that has support for all short-range and long-range data transmissions. Due to the presence of a variety of RAN, the process of network selection is significant in the 5G environment. On the other hand, the vehicles move at a different speeds, so the concept of handover is incorporated. This work proposes handover prediction and selection of networks, which was not performed in previous work.</p><p>In the existing study of the TOPSIS algorithm, ANDSF, and V2I-MoLoHA methods, the network was selected from the computation of one or more metrics once it receives the request from the vehicle. While in the proposed work, on receiving a vehicle request, it predicts the requirement of handover, and then it selects a network only if needed. The prediction process using dynamic Q-learning leads to minimizing unnecessary handover and then F-CNN leads to improve optimal network selection. Hereby 45 to 50% of the performance of handover is improved than the existing algorithms.</p><p>Second, throughput and delay: throughput and end-to-end delay are the important parameters that are used to measure the performance of the proposed work with the previous algorithms. The selection of routes using an optimization algorithm with vehicle metrics can identify an optimal route. As a result, 40 to 45% of the throughput is improved than the previous methods. The improvement in throughput will also impact other network parameters. Then the end-to-end delay is 10 to 15% improved than the previous algorithms.</p><p>The proposed algorithms for handover decision, network selection, and routing have a major impact on the performances of the network. This work takes into account the most essential metrics for making a decision and network selection. As a result, the proposed work achieves better performance when compared with previous work of handover.</p></sec><sec id="j_ijssis-2021-012_s_007"><div>Conclusion</div><p>We have proposed three algorithms for making handover, network selection, and routing in the IoV environment due to the presence of multiple radio access networks. The data transmission requirement depends on each data type. Dynamic Q-learning algorithm is used for making handovers by computing the dynamic thresholds using Shannon entropy rule, and also determines the need for handover. It is clear from the results that using the dynamic Q-learning algorithm, there is a reduction in unnecessary handovers. Appropriate selection of network is achieved using fuzzy-CNN that processes multiple requests simultaneously and enables to considerate multiple parameters to select the network. Besides, a routing algorithm is proposed that forms V2V pairs and selects the best route using a jellyfish optimization algorithm to reduce end-to-end delay, and packet losses. The objective function is defined using vehicle metrics, channel metrics, and performance metrics. The simulation results have shown the superiority of the proposed work considering mean HO, HO failure rate, throughput, delay, and packet loss as the evaluation metrics. The evaluation of switching delays between multiple RAT is the future scope of our work.</p></sec></div></div></div></div><div id="pane-3" class="SeriesTab_card__26XnC SeriesTab_tab-pane__3pc7y card tab-pane" role="tabpanel" aria-labelledby="tab-3"><div class="SeriesTab_card-header__1DTAS card-header d-md-none pl-0" role="tab" id="heading-3"><h4 class="mb-0"><a data-toggle="collapse" href="#collapse-3" data-parent="#content" aria-expanded="false" aria-controls="collapse-3" style="padding:24px 0">Figures et tableaux<svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="chevron-down" class="svg-inline--fa fa-chevron-down fa-w-14 " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></a></h4></div><div id="collapse-3" class="SeriesTab_seriesTabCollapse__2csiF collapse" role="tabpanel" aria-labelledby="heading-3" data-parent="#content"><div class="SeriesTab_series-tab-body__1tZ1H SeriesTab_card-body__31JEh card-body Article_figures-tables__2SC5X"><figure><h4 class="mb-4">Figure 1:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=d7f4b1353ff7030ffd85d3549b15458d2b06c94facc2f49fc190c45685ad692e" alt="Workflow procedure of ANDSF (Ndashimye et al., 2020)." class="mw-100"/><figcaption class="fw-500">Workflow procedure of ANDSF (Ndashimye et al., 2020).</figcaption></figure><figure><h4 class="mb-4">Figure 2:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=7c8e1b2b5904d103545e0a04963db98c313496900499931f6daabcce70b1809b" alt="Proposed system model." class="mw-100"/><figcaption class="fw-500">Proposed system model.</figcaption></figure><figure><h4 class="mb-4">Figure 3:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=7343cb6b31b0e31544f4f0cd228cea5dd72b2e6a5e79d9ebeb6c161b4f959ec0" alt="Workflow of dynamic Q-learning." class="mw-100"/><figcaption class="fw-500">Workflow of dynamic Q-learning.</figcaption></figure><figure><h4 class="mb-4"></h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=007b7cb6f8dc5dc92c34cf0a8e193ec40fcd496ffda4727cc93cbb39fa03cf8a" class="mw-100"/><figcaption class="fw-500"></figcaption></figure><figure><h4 class="mb-4">Figure 4:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=dd1de1b23b1402cf8df6d99161a6253bb07b75b28cde35656d232b19feac4e8f" alt="Fuzzy-convolutional neural network." class="mw-100"/><figcaption class="fw-500">Fuzzy-convolutional neural network.</figcaption></figure><figure><h4 class="mb-4"></h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=29c2f59577776976b5bd1faa22634c6ad37cf80d7160d34fb96213f414613d7d" class="mw-100"/><figcaption class="fw-500"></figcaption></figure><figure><h4 class="mb-4">Figure 5:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=3e5c8fda9455086f35cf5bdb7f32631a948797d41c755dfa6c51e5edcab42ac5" alt="Comparison of mean handover (Ndashimye et al., 2020; Sheng et al., 2018)." class="mw-100"/><figcaption class="fw-500">Comparison of mean handover (Ndashimye et al., 2020; Sheng et al., 2018).</figcaption></figure><figure><h4 class="mb-4">Figure 6:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=055e08cf21dda6ba730cf94a1888636b00b7aa3af0e07ae95f1a9e1562f5ca00" alt="Comparison of HO failure (Ndashimye et al., 2020; Sheng et al., 2018)." class="mw-100"/><figcaption class="fw-500">Comparison of HO failure (Ndashimye et al., 2020; Sheng et al., 2018).</figcaption></figure><figure><h4 class="mb-4">Figure 7:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=08567be3e13fa07225c15570ac6a28b13ce573313174e97d12ce9706261c0e82" alt="Comparison of throughput (Ndashimye et al., 2020; Sheng et al., 2018)." class="mw-100"/><figcaption class="fw-500">Comparison of throughput (Ndashimye et al., 2020; Sheng et al., 2018).</figcaption></figure><figure><h4 class="mb-4">Figure 8:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_008.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=37df6a93aea33af2bafc280bfc1445624f78c5b86ce281b1b78ed6da7020ee3a" alt="Comparison of end-to-end delay (Ndashimye et al., 2020; Sheng et al., 2018)." class="mw-100"/><figcaption class="fw-500">Comparison of end-to-end delay (Ndashimye et al., 2020; Sheng et al., 2018).</figcaption></figure><figure><h4 class="mb-4">Figure 9:</h4><img src="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_009.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20230203T065859Z&X-Amz-SignedHeaders=host&X-Amz-Expires=18000&X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Signature=1439d9dead49c156ab3acbc1c1230896fd05f7a75067574d0981beee475cfea4" alt="Comparison on packet loss (Ndashimye et al., 2020; Sheng et al., 2018)." class="mw-100"/><figcaption class="fw-500">Comparison on packet loss (Ndashimye et al., 2020; Sheng et al., 2018).</figcaption></figure><h4 class="mb-4 mt-4">Comparison of HO efficiency.</h4><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Method</th><th align="center" rowspan="1" colspan="1">Average number of HO</th><th align="center" rowspan="1" colspan="1">Better efficiency</th><th align="center" rowspan="1" colspan="1">Average HO<sub><italic>FR</italic></sub></th><th align="center" rowspan="1" colspan="1">Better efficiency</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Conventional</td><td align="center" rowspan="1" colspan="1">5.51</td><td align="center" rowspan="1" colspan="1">55%</td><td align="center" rowspan="1" colspan="1">0.133</td><td align="center" rowspan="1" colspan="1">90%</td></tr><tr><td align="left" rowspan="1" colspan="1">TOPSIS</td><td align="center" rowspan="1" colspan="1">2.15</td><td align="center" rowspan="1" colspan="1">20%</td><td align="center" rowspan="1" colspan="1">0.041</td><td align="center" rowspan="1" colspan="1">40%</td></tr><tr><td align="left" rowspan="1" colspan="1">ANDSF-HO</td><td align="center" rowspan="1" colspan="1">3.57</td><td align="center" rowspan="1" colspan="1">30%</td><td align="center" rowspan="1" colspan="1">0.069</td><td align="center" rowspan="1" colspan="1">60%</td></tr><tr><td align="left" rowspan="1" colspan="1">V2I-MoLoHA</td><td align="center" rowspan="1" colspan="1">3.03</td><td align="center" rowspan="1" colspan="1">25%</td><td align="center" rowspan="1" colspan="1">0.029</td><td align="center" rowspan="1" colspan="1">20%</td></tr><tr><td align="left" rowspan="1" colspan="1">Proposed</td><td align="center" rowspan="1" colspan="1">1.30</td><td align="center" rowspan="1" colspan="1">–</td><td align="center" rowspan="1" colspan="1">0.01</td><td align="center" rowspan="1" colspan="1">–</td></tr></tbody></table><h4 class="mb-4 mt-4">Fuzzy rules.</h4><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1"/><th align="center" rowspan="1" colspan="5">Input</th><th align="left" rowspan="1" colspan="1"/></tr><tr><th align="left" rowspan="1" colspan="1">Rule number</th><th align="left" rowspan="1" colspan="1"><italic>S</italic><sub><italic>r</italic></sub></th><th align="left" rowspan="1" colspan="1">Distance</th><th align="left" rowspan="1" colspan="1"><italic>V</italic><sub><italic>D</italic></sub></th><th align="left" rowspan="1" colspan="1">Data type</th><th align="left" rowspan="1" colspan="1">LoS</th><th align="left" rowspan="1" colspan="1">Output</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">R1</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R2</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R3</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R4</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R5</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R6</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R7</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R8</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R9</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R10</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R11</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R12</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R13</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R14</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R15</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R16</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R17</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R18</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R19</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R20</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R21</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R22</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R23</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R24</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R25</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td></tr><tr><td align="left" rowspan="1" colspan="1">R26</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R27</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R28</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R29</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R30</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">M</td></tr><tr><td align="left" rowspan="1" colspan="1">R31</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">H</td><td align="left" rowspan="1" colspan="1">L</td></tr><tr><td align="left" rowspan="1" colspan="1">R32</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td><td align="left" rowspan="1" colspan="1">L</td></tr></tbody></table><h4 class="mb-4 mt-4">Simulation specifications.</h4><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Parameter</th><th align="center" rowspan="1" colspan="1">Range/Value</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Simulation area</td><td align="center" rowspan="1" colspan="1">2,500 m × 2,500 m</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of vehicles</td><td align="center" rowspan="1" colspan="1">100</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of 5G mmWave BSs</td><td align="center" rowspan="1" colspan="1">2</td></tr><tr><td align="left" rowspan="1" colspan="1">Number of 4G LTE BSs</td><td align="center" rowspan="1" colspan="1">2</td></tr><tr><td align="left" rowspan="1" colspan="1">Vehicle mobility type</td><td align="center" rowspan="1" colspan="1">Linear mobility</td></tr><tr><td align="left" rowspan="1" colspan="1">Vehicle speed</td><td align="center" rowspan="1" colspan="1">10-40 m/s</td></tr><tr><td align="left" rowspan="1" colspan="2">Transmission range</td></tr><tr><td align="left" rowspan="1" colspan="1"> DSRC</td><td align="center" rowspan="1" colspan="1">300 m (Max)</td></tr><tr><td align="left" rowspan="1" colspan="1"> mmWave</td><td align="center" rowspan="1" colspan="1">~500 m</td></tr><tr><td align="left" rowspan="1" colspan="1"> LTE</td><td align="center" rowspan="1" colspan="1">100 km (Max)</td></tr><tr><td align="left" rowspan="1" colspan="1">Transmission rate</td><td align="center" rowspan="1" colspan="1">3-5 packets per second</td></tr><tr><td align="left" rowspan="1" colspan="1">Packet size</td><td align="center" rowspan="1" colspan="1">512 bytes</td></tr><tr><td align="left" rowspan="1" colspan="1">Simulation time</td><td align="center" rowspan="1" colspan="1">1,000 sec</td></tr></tbody></table><h4 class="mb-4 mt-4">Comparison of throughput and delay.</h4><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Method</th><th align="center" rowspan="1" colspan="1">Mean <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_ijssis-2021-012_ieq_011.png"/><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>T</mml:mi></mml:math><tex-math/></alternatives></inline-formula> (kbps)</th><th align="center" rowspan="1" colspan="1">Better efficiency</th><th align="center" rowspan="1" colspan="1">Average delay (ms)</th><th align="center" rowspan="1" colspan="1">Better efficiency</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Conventional</td><td align="center" rowspan="1" colspan="1">13.7</td><td align="center" rowspan="1" colspan="1">46%</td><td align="center" rowspan="1" colspan="1">39</td><td align="center" rowspan="1" colspan="1">21%</td></tr><tr><td align="left" rowspan="1" colspan="1">TOPSIS</td><td align="center" rowspan="1" colspan="1">35.96</td><td align="center" rowspan="1" colspan="1">23%</td><td align="center" rowspan="1" colspan="1">30</td><td align="center" rowspan="1" colspan="1">12%</td></tr><tr><td align="left" rowspan="1" colspan="1">ANDSF-HO</td><td align="center" rowspan="1" colspan="1">25</td><td align="center" rowspan="1" colspan="1">34%</td><td align="center" rowspan="1" colspan="1">37</td><td align="center" rowspan="1" colspan="1">19%</td></tr><tr><td align="left" rowspan="1" colspan="1">V2I-MoLoHA</td><td align="center" rowspan="1" colspan="1">31.89</td><td align="center" rowspan="1" colspan="1">27%</td><td align="center" rowspan="1" colspan="1">34</td><td align="center" rowspan="1" colspan="1">16%</td></tr><tr><td align="left" rowspan="1" colspan="1">Proposed</td><td align="center" rowspan="1" colspan="1">58.89</td><td align="center" rowspan="1" colspan="1">–</td><td align="center" rowspan="1" colspan="1">18</td><td align="center" rowspan="1" colspan="1">–</td></tr></tbody></table><h4 class="mb-4 mt-4">Comparison of packet loss.</h4><table frame="hsides"><colgroup span="1"><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/><col align="left" width="1*" span="1"/></colgroup><thead><tr><th align="left" rowspan="1" colspan="1">Method</th><th align="center" rowspan="1" colspan="1">Packet loss (%)</th><th align="center" rowspan="1" colspan="1">Better efficiency</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Conventional</td><td align="center" rowspan="1" colspan="1">48</td><td align="center" rowspan="1" colspan="1">21%</td></tr><tr><td align="left" rowspan="1" colspan="1">TOPSIS</td><td align="center" rowspan="1" colspan="1">32.4</td><td align="center" rowspan="1" colspan="1">12%</td></tr><tr><td align="left" rowspan="1" colspan="1">ANDSF-HO</td><td align="center" rowspan="1" colspan="1">24</td><td align="center" rowspan="1" colspan="1">19%</td></tr><tr><td align="left" rowspan="1" colspan="1">V2I-MoLoHA</td><td align="center" rowspan="1" colspan="1">18.8</td><td align="center" rowspan="1" colspan="1">16%</td></tr><tr><td align="left" rowspan="1" colspan="1">Proposed</td><td align="center" rowspan="1" colspan="1">12</td><td align="center" rowspan="1" colspan="1">–</td></tr></tbody></table></div></div></div><div id="reference" class="SeriesTab_card__26XnC SeriesTab_tab-pane__3pc7y card tab-pane" role="tabpanel" aria-labelledby="tab-4"><div class="SeriesTab_card-header__1DTAS card-header d-md-none pl-0" role="tab" id="heading-4"><h4 class="mb-0"><a data-toggle="collapse" href="#collapse-4" data-parent="#content" aria-expanded="false" aria-controls="collapse-4" style="padding:24px 0">Références<svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="chevron-down" class="svg-inline--fa fa-chevron-down fa-w-14 " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M207.029 381.476L12.686 187.132c-9.373-9.373-9.373-24.569 0-33.941l22.667-22.667c9.357-9.357 24.522-9.375 33.901-.04L224 284.505l154.745-154.021c9.379-9.335 24.544-9.317 33.901.04l22.667 22.667c9.373 9.373 9.373 24.569 0 33.941L240.971 381.476c-9.373 9.372-24.569 9.372-33.942 0z"></path></svg></a></h4></div><div id="collapse-4" class="SeriesTab_seriesTabCollapse__2csiF collapse" role="tabpanel" aria-labelledby="heading-4" data-parent="#content"><div class="SeriesTab_series-tab-body__1tZ1H SeriesTab_card-body__31JEh card-body"><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_001"><mixed-citation>Al-Kharasani, N. M., Ahmad Zukarnain, Z., Subramaniam, S. K. and Mohd Hanapi, Z. 2020. An adaptive relay selection scheme for enhancing network stability in VANETs. IEEE Access 8: 128757–128765.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Al-Kharasani</surname><given-names>N. M.</given-names></name><name><surname>Ahmad Zukarnain</surname><given-names>Z.</given-names></name><name><surname>Subramaniam</surname><given-names>S. K.</given-names></name><name><surname>Mohd Hanapi</surname><given-names>Z.</given-names></name></person-group><year>2020</year><article-title>An adaptive relay selection scheme for enhancing network stability in VANETs</article-title><source>IEEE Access</source><volume>8</volume><fpage>128757</fpage><lpage>128765</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/ACCESS.2020.2974105</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Al-Kharasani, N. M., Ahmad Zukarnain, Z., Subramaniam, S. K. and Mohd Hanapi, Z. 2020. An adaptive relay selection scheme for enhancing network stability in VANETs. IEEE Access 8: 128757–128765." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_002"><mixed-citation>Cao, D., Liu, Y., Ma, X., Wang, J., Baofeng, J., Feng, C. and Si, J. 2019. A relay-node selection on curve road in vehicular networks. IEEE Access 7: 12714–12728.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Cao</surname><given-names>D.</given-names></name><name><surname>Liu</surname><given-names>Y.</given-names></name><name><surname>Ma</surname><given-names>X.</given-names></name><name><surname>Wang</surname><given-names>J.</given-names></name><name><surname>Baofeng</surname><given-names>J.</given-names></name><name><surname>Feng</surname><given-names>C.</given-names></name><name><surname>Si</surname><given-names>J.</given-names></name></person-group><year>2019</year><article-title>A relay-node selection on curve road in vehicular networks</article-title><source>IEEE Access</source><volume>7</volume><fpage>12714</fpage><lpage>12728</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/ACCESS.2019.2892979</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Cao, D., Liu, Y., Ma, X., Wang, J., Baofeng, J., Feng, C. and Si, J. 2019. A relay-node selection on curve road in vehicular networks. IEEE Access 7: 12714–12728." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_003"><mixed-citation>Chang, Y. -H., Liu, H. -H. and Wei, H. -Y. 2019. “Group-based sidelink communication for seamless vehicular handover”, IEEE Access 7: 56431–56442.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Chang</surname><given-names>Y. -H.</given-names></name><name><surname>Liu</surname><given-names>H. -H.</given-names></name><name><surname>Wei</surname><given-names>H. -Y.</given-names></name></person-group><year>2019</year><article-title>“Group-based sidelink communication for seamless vehicular handover”</article-title><source>IEEE Access</source><volume>7</volume><fpage>56431</fpage><lpage>56442</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/ACCESS.2019.2913462</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Chang, Y. -H., Liu, H. -H. and Wei, H. -Y. 2019. “Group-based sidelink communication for seamless vehicular handover”, IEEE Access 7: 56431–56442." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_004"><mixed-citation>Choi, J. -H., Han, Y. -H. and Min, S. -G. 2018. A network-based seamless handover scheme for VANETs. IEEE Access 6: 56311–56322.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Choi</surname><given-names>J. -H.</given-names></name><name><surname>Han</surname><given-names>Y. -H.</given-names></name><name><surname>Min</surname><given-names>S. -G.</given-names></name></person-group><year>2018</year><article-title>A network-based seamless handover scheme for VANETs</article-title><source>IEEE Access</source><volume>6</volume><fpage>56311</fpage><lpage>56322</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/ACCESS.2018.2872795</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Choi, J. -H., Han, Y. -H. and Min, S. -G. 2018. A network-based seamless handover scheme for VANETs. IEEE Access 6: 56311–56322." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_005"><mixed-citation>Embus, D. A., Castillo, A. J., Vivas, F. Y., Caicedo, O. M. and Ordóñez, A. 2020. NetSel-RF: a moel for network selection based on multi-criteria and supervised leaning. Applied Sciences 10: 12.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Embus</surname><given-names>D. A.</given-names></name><name><surname>Castillo</surname><given-names>A. J.</given-names></name><name><surname>Vivas</surname><given-names>F. Y.</given-names></name><name><surname>Caicedo</surname><given-names>O. M.</given-names></name><name><surname>Ordóñez</surname><given-names>A.</given-names></name></person-group><year>2020</year><article-title>NetSel-RF: a moel for network selection based on multi-criteria and supervised leaning</article-title><source>Applied Sciences</source><volume>10</volume><fpage>12</fpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.3390/app10124382</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Embus, D. A., Castillo, A. J., Vivas, F. Y., Caicedo, O. M. and Ordóñez, A. 2020. NetSel-RF: a moel for network selection based on multi-criteria and supervised leaning. Applied Sciences 10: 12." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_006"><mixed-citation>Hamurcu, M. and Eren, T. 2020. Strategic planning based on sustainability for urban transportation: an application to decision-making. Sustainability 12(9): 1–24.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Hamurcu</surname><given-names>M.</given-names></name><name><surname>Eren</surname><given-names>T.</given-names></name></person-group><year>2020</year><article-title>Strategic planning based on sustainability for urban transportation: an application to decision-making</article-title><source>Sustainability</source><volume>12</volume><issue>(9):</issue><fpage>1</fpage><lpage>24</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.3390/su12093589</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Hamurcu, M. and Eren, T. 2020. Strategic planning based on sustainability for urban transportation: an application to decision-making. Sustainability 12(9): 1–24." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_007"><mixed-citation>Jubara, H. E. I. 2020. An efficient handover procedure in vehicular communication. 2nd International Conference on Computer and Information Sciences (ICCIS).</mixed-citation><element-citation publication-type="other" publication-format="print"><person-group person-group-type="author"><name><surname>Jubara</surname><given-names>H. E. I.</given-names></name></person-group><year>2020</year><article-title>An efficient handover procedure in vehicular communication</article-title><source>2nd International Conference on Computer and Information Sciences (ICCIS)</source><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/ICCIS49240.2020.9257665</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Jubara, H. E. I. 2020. An efficient handover procedure in vehicular communication. 2nd International Conference on Computer and Information Sciences (ICCIS)." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_008"><mixed-citation>Leu, F. -Y., Tsai, K. -L. and Lin, S. -Y. 2019. E-ANDSF-based base station selection by using MLP in untrusted environments. IEEE Transactions on Industrial Informatics 15(10): 5708–5714.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Leu</surname><given-names>F. -Y.</given-names></name><name><surname>Tsai</surname><given-names>K. -L.</given-names></name><name><surname>Lin</surname><given-names>S. -Y.</given-names></name></person-group><year>2019</year><article-title>E-ANDSF-based base station selection by using MLP in untrusted environments</article-title><source>IEEE Transactions on Industrial Informatics</source><volume>15</volume><issue>(10):</issue><fpage>5708</fpage><lpage>5714</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/TII.2019.2916335</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Leu, F. -Y., Tsai, K. -L. and Lin, S. -Y. 2019. E-ANDSF-based base station selection by using MLP in untrusted environments. IEEE Transactions on Industrial Informatics 15(10): 5708–5714." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_009"><mixed-citation>Naeem, B., Ngah, R. and Mohd Hashim, S. Z. 2019. Reduction in ping-pong effect in heterogeneous networks using fuzzy logic. Soft Computing 23: 269–283.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Naeem</surname><given-names>B.</given-names></name><name><surname>Ngah</surname><given-names>R.</given-names></name><name><surname>Mohd Hashim</surname><given-names>S. Z.</given-names></name></person-group><year>2019</year><article-title>Reduction in ping-pong effect in heterogeneous networks using fuzzy logic</article-title><source>Soft Computing</source><volume>23</volume><fpage>269</fpage><lpage>283</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1007/s00500-018-3246-2</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Naeem, B., Ngah, R. and Mohd Hashim, S. Z. 2019. Reduction in ping-pong effect in heterogeneous networks using fuzzy logic. Soft Computing 23: 269–283." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_010"><mixed-citation>Ndashimye, E., Sarkar, N. I. and Ray, S. K. 2020. A network selection method for handover in vehicle-to-infrastructure communications in multi-tier networks. Wireless Networks 2018: 1–15.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Ndashimye</surname><given-names>E.</given-names></name><name><surname>Sarkar</surname><given-names>N. I.</given-names></name><name><surname>Ray</surname><given-names>S. K.</given-names></name></person-group><year>2020</year><article-title>A network selection method for handover in vehicle-to-infrastructure communications in multi-tier networks</article-title><source>Wireless Networks</source><volume>2018</volume><fpage>1</fpage><lpage>15</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1007/s11276-018-1817-x</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Ndashimye, E., Sarkar, N. I. and Ray, S. K. 2020. A network selection method for handover in vehicle-to-infrastructure communications in multi-tier networks. Wireless Networks 2018: 1–15." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_011"><mixed-citation>Nguyen, T. -H. and Jung, J. J. 2020. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. 16th International Conference on Intelligent Environments.</mixed-citation><element-citation publication-type="other" publication-format="print"><person-group person-group-type="author"><name><surname>Nguyen</surname><given-names>T. -H.</given-names></name><name><surname>Jung</surname><given-names>J. J.</given-names></name></person-group><year>2020</year><article-title>ACO-based Approach on Dynamic MSMD Routing in IoV Environment</article-title><source>16th International Conference on Intelligent Environments</source><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/IE49459.2020.9154927</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Nguyen, T. -H. and Jung, J. J. 2020. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. 16th International Conference on Intelligent Environments." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_012"><mixed-citation>Sheng, Z., Pressas, A., Ocheri, V., Ali, F., Rudd, R. and Nekovee, M. 2018. Intelligent 5G Vehicular Networks: An Integration of DSRC and mmWave Communications. International Conference on Information and Communication Technology Convergence (ICTC), IEEE.</mixed-citation><element-citation publication-type="other" publication-format="print"><person-group person-group-type="author"><name><surname>Sheng</surname><given-names>Z.</given-names></name><name><surname>Pressas</surname><given-names>A.</given-names></name><name><surname>Ocheri</surname><given-names>V.</given-names></name><name><surname>Ali</surname><given-names>F.</given-names></name><name><surname>Rudd</surname><given-names>R.</given-names></name><name><surname>Nekovee</surname><given-names>M.</given-names></name></person-group><year>2018</year><article-title>Intelligent 5G Vehicular Networks: An Integration of DSRC and mmWave Communications</article-title><source>International Conference on Information and Communication Technology Convergence (ICTC), IEEE</source><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.1109/ICTC.2018.8539687</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Sheng, Z., Pressas, A., Ocheri, V., Ali, F., Rudd, R. and Nekovee, M. 2018. Intelligent 5G Vehicular Networks: An Integration of DSRC and mmWave Communications. International Conference on Information and Communication Technology Convergence (ICTC), IEEE." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_013"><mixed-citation>Singh, A., Budakoti, J. and Lung, C. -H. 2020. Vertical handover decision for mobile IoT edge gateway using multi-criteria and fuzzy logic techniques. Advances in Internet of Things 10: 57–93.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Singh</surname><given-names>A.</given-names></name><name><surname>Budakoti</surname><given-names>J.</given-names></name><name><surname>Lung</surname><given-names>C. -H.</given-names></name></person-group><year>2020</year><article-title>Vertical handover decision for mobile IoT edge gateway using multi-criteria and fuzzy logic techniques</article-title><source>Advances in Internet of Things</source><volume>10</volume><fpage>57</fpage><lpage>93</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.4236/ait.2020.104005</dgdoi:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Singh, A., Budakoti, J. and Lung, C. -H. 2020. Vertical handover decision for mobile IoT edge gateway using multi-criteria and fuzzy logic techniques. Advances in Internet of Things 10: 57–93." target="_blank">Search in Google Scholar</a></span></p><p class="Article_refData__1fofs"><span class="Article_d-block__2MPqH"><ref id="j_ijssis-2021-012_ref_014"><mixed-citation>Storck, C. R. and Duarte-Figueiredo, F. 2019. A 5G V2X ecosystem providing internet of vehicles. Sensors 19: 1–20.</mixed-citation><element-citation publication-type="journal" publication-format="print"><person-group person-group-type="author"><name><surname>Storck</surname><given-names>C. R.</given-names></name><name><surname>Duarte-Figueiredo</surname><given-names>F.</given-names></name></person-group><year>2019</year><article-title>A 5G V2X ecosystem providing internet of vehicles</article-title><source>Sensors</source><volume>19</volume><fpage>1</fpage><lpage>20</lpage><dgdoi:pub-id xmlns:dgdoi="http://degruyter.com/resources/doi-from-crossref" pub-id-type="doi">10.3390/s19030550</dgdoi:pub-id><dgpm:pub-id xmlns:dgpm="http://degruyter.com/resources/fetched-pubmed-id" pub-id-type="pmcid">6386933</dgpm:pub-id><dgpm:pub-id xmlns:dgpm="http://degruyter.com/resources/fetched-pubmed-id" pub-id-type="pmid">30699926</dgpm:pub-id></element-citation></ref></span><span class="refLinks"><a href="https://scholar.google.com/scholar?q=Storck, C. R. and Duarte-Figueiredo, F. 2019. A 5G V2X ecosystem providing internet of vehicles. 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Please read \u003cA href=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/IJSSIS/Guidelines_and_Manuscript_Preparation.pdf\"\u003eGuidelines and Manuscript Preparation\u003c/A\u003e to find out more.\u003cA href=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/IJSSIS/Open_Access_Agreement.pdf\"\u003e\u003c/A\u003e \u003c/P\u003e"},{"type":"editorial","language":"English","textformat":null,"content":"\u003cP\u003e\u003cSTRONG\u003eEditor-in-Chief\u003c/STRONG\u003e\u003cBR\u003eDr. Subhas Chandra Mukhopadhyay - Macquarie University, Sydney, Australia \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eAssociate Editors\u003c/STRONG\u003e\u003cBR\u003eEshrat E. Alahi - Chinese University of Sciences, Shenzhen, China\u003cBR\u003eCesare Alippi - Politecnico Di Milano, Italy\u003cBR\u003eFrancisco J. Arregui - Public University of Navarre, Spain\u003cBR\u003eMohsen Asadnia - Macquarie University, Australia\u003cBR\u003eTakehito Azuma - Utsunomiya University, Japan\u003cBR\u003eThierry Bosch - Institut National Polytechnique de Toulouse, France\u003cBR\u003eGraham Brooker - University of Sydney, Australia\u003cBR\u003eGoutam Chakraborty - Iwate Prefectural University, Japan\u003cBR\u003eBasabi Chakraborty - Pattern Recognition \u0026amp; Machine Learning Laboratory, Faculty of Software and Information Science, Iwate Prefectural University, Japan\u003cBR\u003eGoutam Chattopadhyay - JPL, CALTECH, USA\u003cBR\u003eSuming Chen - National Taiwan University, Taiwan\u003cBR\u003eBhaskar Choubey - Oxford University, United Kingdom\u003cBR\u003ePau-Choo Chung - National Cheng Kung University, Taiwan\u003cBR\u003eWan-Young Chung - Pukyong National University, Korea\u003cBR\u003eYeon-Ho Chung - Pukyong National University, Korea\u003cBR\u003eAndrea Cusano - University of Sannio, Italy\u003cBR\u003eKourtiche Djilali - French National Centre for Scientific Research · Institut Jean Lamour · Nanomaterials, Electronics and Living Matter, France\u003cBR\u003eAnton Fuchs - Graz University of Technology, Austria\u003cBR\u003eElena Gaura - Coventry University, United Kingdom\u003cBR\u003eBoby George - Indian Institute of Technology Madras, India\u003cBR\u003eBoris Ginzburg - Soreq NRC, Israel\u003cBR\u003eChinthaka Gooneratne - Sensors and Instrumentation, EXPEC Advanced Research Center, Saudi Arabia\u003cBR\u003eNgo Ha-Duong - Microsystems Engineering, University of Applied Sciences Berlin and Group Leader Microsensors Technologies at Fraunhofer Institute IZM, Germany\u003cBR\u003eMaki Habib - The American University in Cairo, Egypt\u003cBR\u003eMichael J. Haji-Sheikh - Northern Illinois University, USA\u003cBR\u003eTarikul Islam - Jamia Islami University, India\u003cBR\u003eWisnu Jatmiko - Universitas Indonesia, Indonesia\u003cBR\u003eK.P. Jayasundera - Massey University, New Zealand\u003cBR\u003eNemai Karmakar - Monash University, Australia\u003cBR\u003eFakhri Karray - University of Waterloo, Canada\u003cBR\u003eJohn V Kennedy - National Isotope Centre, GNS Science, New Zealand\u003cBR\u003eTan Kok Kiong - National University of Singapore, Singapore\u003cBR\u003eJürgen Kosel - King Abdullah University of Science, Saudi Arabia\u003cBR\u003eJoyanta Kumar Roy - MCKV Institute of Engineering, Liluah, India\u003cBR\u003eIvan Laktionov - SHEE 'Donetsk National Technical University', Ukraine\u003cBR\u003eAimé Lay-Ekuakille - Università del Salento, Italy\u003cBR\u003eWarren Huang-Chen Lee - National Chung Cheng University, Taiwan\u003cBR\u003eHenry Leung - University of Calgary, Canada\u003cBR\u003eElfed Lewis - University of Limerick, Ireland\u003cBR\u003eZhi Liu - Shandong University, China\u003cBR\u003eAndreas Loizos - National Technical University of Athens(NTUA), Greece\u003cBR\u003eIliana Marinova - Technical University of Sofia, Bulgaria\u003cBR\u003eLuiz de Siqueira Martins-Filho - Universidade federal do ABC-UFABC, Brazil\u003cBR\u003eIgnacio Matias - Professor, Universidad Pública de Navarra, Spain\u003cBR\u003eRosario Morello - University Mediterranea of Reggio Calabria, Italy\u003cBR\u003eMustapha Nadi - Université de Lorraine, France\u003cBR\u003eAndrew Nafalski - University of South Australia, Adelaide, Australia\u003cBR\u003eAnindya Nag - King Abdullah University of Science, Saudi Arabia\u003cBR\u003eVisconti Paolo - University of Salento, Italy\u003cBR\u003eOctavian Postolache - Instituto de Telecomunicações, Lisboa/IT, Portugal\u003cBR\u003eD. M. G. Preethichandra - Central Queensland University, Australia\u003cBR\u003eKonandur Rajanna - IISc, Bangalore, India\u003cBR\u003ePavel Ripka - Czech Technical University, Czech Republic\u003cBR\u003eAbed El Saddik - University of Ottawa, Canada\u003cBR\u003eYahaya Md. Sam - University Technology of Malaysia, Malaysia\u003cBR\u003eFrode Eika Sandnes - Oslo University, Norway\u003cBR\u003eNorbert Schwesinger - Technische Universität München, Germany\u003cBR\u003eSiddhartha Sen - IIT, Kharagpur, India\u003cBR\u003eSMN Arosha Senanayake - Brueni Darusalem University, Brunei\u003cBR\u003eLakmal Seneviratne - Kings College, London, United Kingdom\u003cBR\u003eMohamed Serry - Princeton University, USA\u003cBR\u003eNitinipun Sharma - BITS, Pilani, India\u003cBR\u003eLei Shu - Osaka University, Japan\u003cBR\u003eValery Anatolevitch Sklyarov - University of Aveiro, Portugal\u003cBR\u003eQingquan Sun - Oakland University, USA\u003cBR\u003eNagender Kumar Suryadevara - Geethanjali College of Engineering and Technology, India\u003cBR\u003eKay Chen Tan - National University of Singapore, Singapore\u003cBR\u003eGui Yun Tian - University of Newcastle upon Tyne, United Kingdom\u003cBR\u003eAthanasios Vasilakos - National Technical University of Athens, Greece\u003cBR\u003eJoseph Walsh - Institute of Technology, Tralee, Ireland\u003cBR\u003eYuhao Wang - Nanchang University, China\u003cBR\u003eYoke-San Wong - National University of Singapore, Singapore\u003cBR\u003eWanqing Wu - Shenzhen Institute of Advanced Technology, Chinese Academcy of Sciences, China\u003cBR\u003ePeter Xu - The University of Auckland, New Zealand\u003cBR\u003eSotoshi Yamada - Kanazawa University, Japan\u003cBR\u003eRuqiang Yan - Southeast University, China\u003cBR\u003eJize Yan - University of Southampton, United Kingdom\u003cBR\u003eJar-Ferr Yang - National Cheng Kung University, Taiwan\u003cBR\u003eAndrew Yeh - National Tsing Hua University, Taiwan\u003cBR\u003eWuliang Yin - The University of Manchester, United Kingdom\u003cBR\u003eMehmet Yuce - Monash University, Australia\u003cBR\u003eHeye Zhang - Sun Yat-Sen University, China\u003cBR\u003eArcady Zhukov - Basque Country University, UPV/EHU, Spain \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eHonorary Editor\u003c/STRONG\u003e\u003cBR\u003eToshio Fukuda - Nagoya University, Japan\u003cBR\u003eEmil Petriu - University of Ottawa, Canada\u003cBR\u003ePhilip Sallis - Auckland University of Technology, New Zealand\u003cBR\u003eMel Siegel - Carnegie Mellon University, USA\u003cBR\u003eShoogo Ueno - Tokyo University, Japan \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eDeputy Editor\u003c/STRONG\u003e\u003cBR\u003eRay (Yuef-Min) Huang - National Cheng-Kung University, Taiwan \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eManaging Editor\u003c/STRONG\u003e\u003cBR\u003eKevin Yen-Hung Kuo - Fusions360, Taiwan\u003cBR\u003eLisa Lightband - Massey University, New Zealand \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eContact\u003c/STRONG\u003e\u003cBR\u003e\u003cA href=\"mailto:Subhas.Mukhopadhyay@mq.edu.au\"\u003eSubhas.Mukhopadhyay@mq.edu.au\u003c/A\u003e \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003ePublisher\u003c/STRONG\u003e\u003cBR\u003eDe Gruyter Poland\u003cBR\u003eBogumiła Zuga 32A Str.\u003cBR\u003e01-811 Warsaw, Poland\u003cBR\u003eT: +48 22 701 50 15 \u003c/P\u003e"},{"type":"advantages","language":"English","textformat":null,"content":"\u003cP\u003e\u003cSTRONG\u003e\u003cEM\u003eThe International Journal on Smart Sensing and Intelligent Systems (S2IS)\u003c/EM\u003e\u003c/STRONG\u003e is an on-line journal to be available to everybody at no cost. From volume 2018 the journal is published in a \u003cU\u003econtinous format\u003c/U\u003e. \u003c/P\u003e \u003cP\u003eThe journal publishes refereed papers quarterly on any topic in the fields of Smart Sensing, Intelligent Sensing, Smart Systems, and/or Intelligent Systems. \u003c/P\u003e \u003cP\u003eResearchers working on any areas of sensing, sensors and systems which they consider as Smart and/or Intelligent may consider submitting their manuscript for possible publication in the journal. The submitted papers will go through a double-blind peer review process and authors will be notified of the outcome in the shortest possible time. \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eAims and Scope\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eInternational Journal on Smart Sensing and Intelligent Systems (S2IS)\u003c/STRONG\u003e is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: \u003c/P\u003e \u003cUL\u003e \u003cLI\u003eAmbient Intelligence and Smart Environment \u003c/LI\u003e \u003cLI\u003eAnalysis, Evaluation, and Test of Smart Sensors \u003c/LI\u003e \u003cLI\u003eIntelligent Management of Sensors \u003c/LI\u003e \u003cLI\u003eFundamentals of Smart Sensing Principles and Mechanisms \u003c/LI\u003e \u003cLI\u003eMaterials and its Applications for Smart Sensors \u003c/LI\u003e \u003cLI\u003eSmart Sensing Applications, Hardware, Software, Systems, and Technologies \u003c/LI\u003e \u003cLI\u003eSmart Sensors in Multidisciplinary Domains and Problems \u003c/LI\u003e \u003cLI\u003eSmart Sensors in Science and Engineering \u003c/LI\u003e \u003cLI\u003eSmart Sensors in Social Science and Humanity \u003c/LI\u003e\u003c/UL\u003e \u003cP\u003e\u003cSTRONG\u003eRejection rate\u003c/STRONG\u003e: 50% \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eOpen Access Policy\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003eThis journal provides immediate open access to its content under the \u003cA href=\"https://creativecommons.org/licenses/by-nc-nd/4.0/\"\u003eCreative Commons CC BY-NC-ND 4.0 license\u003c/A\u003e on the principle that making research freely available to the public supports a greater global exchange of knowledge. Under the \u003cA href=\"https://creativecommons.org/licenses/by-nc-nd/4.0/\"\u003eCC BY-NC-ND 4.0 license\u003c/A\u003e users are free to share the work (copy and redistribute the material in any medium or format), if the contribution is properly attributed and used for non-commercial purposes. The material published in the journal may not be altered or build upon. \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eABOUT SOCIETY\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eInternational Journal on Smart Sensing and Intelligent Systems\u003c/STRONG\u003e was created and is lead by \u003cSTRONG\u003e\u003cEM\u003eProfessor Subhas Chandra Mukhopadhyay\u003c/EM\u003e\u003c/STRONG\u003e. \u003c/P\u003e \u003cP\u003eProfessor Subhas Chandra Mukhopadhyay is Professor f Mechanical and Electronics Engineering affiliated with FIEEE (USA), FIEE (UK), FIETE (India), Distinguished Lecturer, IEEE Sensors Council. \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003eArea of research interest:\u003c/STRONG\u003e \u003c/P\u003e \u003cUL\u003e \u003cLI\u003eSmart Sensors \u003c/LI\u003e \u003cLI\u003eSensing Technology \u003c/LI\u003e \u003cLI\u003eWireless Sensor Networks \u003c/LI\u003e \u003cLI\u003eInternet of Things \u003c/LI\u003e \u003cLI\u003ePower Electronics \u003c/LI\u003e \u003cLI\u003eMotor Drives \u003c/LI\u003e \u003cLI\u003eMagnetic Bearing \u003c/LI\u003e \u003cLI\u003eElectrical and Electronics Engineering \u003c/LI\u003e \u003cLI\u003eMechatronics \u003c/LI\u003e\u003c/UL\u003e \u003cP\u003e\u003cSTRONG\u003eArchiving\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003eSciendo archives the contents of this journal in \u003cA href=\"https://www.portico.org/\"\u003ePortico\u003c/A\u003e - digital long-term preservation service of scholarly books, journals and collections. \u003c/P\u003e \u003cP\u003e\u003cSTRONG\u003ePlagiarism Policy\u003c/STRONG\u003e \u003c/P\u003e \u003cP\u003eThe editorial board is participating in a growing community of \u003cA href=\"https://www.crossref.org/services/similarity-check/\"\u003eSimilarity Check System's\u003c/A\u003e users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.\u003c/P\u003e"}]}],"metrics":"","pricing":null,"publicationFrequency":{"frequency":"1","period":"YEAR"},"permissions":null,"contributors":"","serial":null,"publishMonth":"1","publishYear":"2021","tableCount":null,"figureCount":null,"refCount":null,"keywords":[],"figures":null,"tables":null,"planPubDates":[],"epubLink":null,"pdfLink":null,"coverImage":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/cover-image.jpg","coverImageOriginal":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/cover-image-original.jpg","pdfFiles":[],"parentObjectId":"62242a2c0d198124537c32f6","isParentConference":false,"relatedTitles":null,"forAuthors":null,"nextPackageId":"62249ace0d198124537c4568","prevPackageId":"62249acd0d198124537c4566","parentName":"Volume 14 (2021): Issue 1 (January 2021)","grandParentId":"61df788b1792e62a88ea438a","grandParentName":"International Journal on Smart Sensing and Intelligent Systems","isGrandParentConference":false,"publisherName":"Sciendo","publisherLocation":null,"nextMap":{"id":{"timestamp":1646566094,"date":"2022-03-06T11:28:14.000+00:00"},"doi":"10.21307/ijssis-2021-013"},"prevMap":{"id":{"timestamp":1646566093,"date":"2022-03-06T11:28:13.000+00:00"},"doi":"10.21307/ijssis-2021-011"},"counter":0,"apaString":"Hussain,S.,Yusof,K.,Hussain,S.[Shaik Ashfaq]. \u0026 Asuncion,R.(2021).\u003carticle-title\u003ePerformance evaluation of vertical handover in Internet of Vehicles\u003c/article-title\u003e. 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M., Ahmad Zukarnain, Z., Subramaniam, S. K. and Mohd Hanapi, Z. 2020. An adaptive relay selection scheme for enhancing network stability in VANETs. IEEE Access 8: 128757–128765.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_001\"\u003e\u003cmixed-citation\u003eAl-Kharasani, N. M., Ahmad Zukarnain, Z., Subramaniam, S. K. and Mohd Hanapi, Z. 2020. An adaptive relay selection scheme for enhancing network stability in VANETs. IEEE Access 8: 128757–128765.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eAl-Kharasani\u003c/surname\u003e\u003cgiven-names\u003eN. M.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eAhmad Zukarnain\u003c/surname\u003e\u003cgiven-names\u003eZ.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eSubramaniam\u003c/surname\u003e\u003cgiven-names\u003eS. K.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eMohd Hanapi\u003c/surname\u003e\u003cgiven-names\u003eZ.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eAn adaptive relay selection scheme for enhancing network stability in VANETs\u003c/article-title\u003e\u003csource\u003eIEEE Access\u003c/source\u003e\u003cvolume\u003e8\u003c/volume\u003e\u003cfpage\u003e128757\u003c/fpage\u003e\u003clpage\u003e128765\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/ACCESS.2020.2974105\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_002","citeString":"Cao, D., Liu, Y., Ma, X., Wang, J., Baofeng, J., Feng, C. and Si, J. 2019. A relay-node selection on curve road in vehicular networks. IEEE Access 7: 12714–12728.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_002\"\u003e\u003cmixed-citation\u003eCao, D., Liu, Y., Ma, X., Wang, J., Baofeng, J., Feng, C. and Si, J. 2019. A relay-node selection on curve road in vehicular networks. IEEE Access 7: 12714–12728.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eCao\u003c/surname\u003e\u003cgiven-names\u003eD.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eLiu\u003c/surname\u003e\u003cgiven-names\u003eY.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eMa\u003c/surname\u003e\u003cgiven-names\u003eX.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eWang\u003c/surname\u003e\u003cgiven-names\u003eJ.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eBaofeng\u003c/surname\u003e\u003cgiven-names\u003eJ.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eFeng\u003c/surname\u003e\u003cgiven-names\u003eC.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eSi\u003c/surname\u003e\u003cgiven-names\u003eJ.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2019\u003c/year\u003e\u003carticle-title\u003eA relay-node selection on curve road in vehicular networks\u003c/article-title\u003e\u003csource\u003eIEEE Access\u003c/source\u003e\u003cvolume\u003e7\u003c/volume\u003e\u003cfpage\u003e12714\u003c/fpage\u003e\u003clpage\u003e12728\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/ACCESS.2019.2892979\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_003","citeString":"Chang, Y. -H., Liu, H. -H. and Wei, H. -Y. 2019. “Group-based sidelink communication for seamless vehicular handover”, IEEE Access 7: 56431–56442.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_003\"\u003e\u003cmixed-citation\u003eChang, Y. -H., Liu, H. -H. and Wei, H. -Y. 2019. “Group-based sidelink communication for seamless vehicular handover”, IEEE Access 7: 56431–56442.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eChang\u003c/surname\u003e\u003cgiven-names\u003eY. -H.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eLiu\u003c/surname\u003e\u003cgiven-names\u003eH. -H.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eWei\u003c/surname\u003e\u003cgiven-names\u003eH. -Y.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2019\u003c/year\u003e\u003carticle-title\u003e“Group-based sidelink communication for seamless vehicular handover”\u003c/article-title\u003e\u003csource\u003eIEEE Access\u003c/source\u003e\u003cvolume\u003e7\u003c/volume\u003e\u003cfpage\u003e56431\u003c/fpage\u003e\u003clpage\u003e56442\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/ACCESS.2019.2913462\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_004","citeString":"Choi, J. -H., Han, Y. -H. and Min, S. -G. 2018. A network-based seamless handover scheme for VANETs. IEEE Access 6: 56311–56322.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_004\"\u003e\u003cmixed-citation\u003eChoi, J. -H., Han, Y. -H. and Min, S. -G. 2018. A network-based seamless handover scheme for VANETs. IEEE Access 6: 56311–56322.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eChoi\u003c/surname\u003e\u003cgiven-names\u003eJ. -H.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eHan\u003c/surname\u003e\u003cgiven-names\u003eY. -H.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eMin\u003c/surname\u003e\u003cgiven-names\u003eS. -G.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2018\u003c/year\u003e\u003carticle-title\u003eA network-based seamless handover scheme for VANETs\u003c/article-title\u003e\u003csource\u003eIEEE Access\u003c/source\u003e\u003cvolume\u003e6\u003c/volume\u003e\u003cfpage\u003e56311\u003c/fpage\u003e\u003clpage\u003e56322\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/ACCESS.2018.2872795\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_005","citeString":"Embus, D. A., Castillo, A. J., Vivas, F. Y., Caicedo, O. M. and Ordóñez, A. 2020. NetSel-RF: a moel for network selection based on multi-criteria and supervised leaning. Applied Sciences 10: 12.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_005\"\u003e\u003cmixed-citation\u003eEmbus, D. A., Castillo, A. J., Vivas, F. Y., Caicedo, O. M. and Ordóñez, A. 2020. NetSel-RF: a moel for network selection based on multi-criteria and supervised leaning. Applied Sciences 10: 12.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eEmbus\u003c/surname\u003e\u003cgiven-names\u003eD. A.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eCastillo\u003c/surname\u003e\u003cgiven-names\u003eA. J.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eVivas\u003c/surname\u003e\u003cgiven-names\u003eF. Y.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eCaicedo\u003c/surname\u003e\u003cgiven-names\u003eO. M.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eOrdóñez\u003c/surname\u003e\u003cgiven-names\u003eA.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eNetSel-RF: a moel for network selection based on multi-criteria and supervised leaning\u003c/article-title\u003e\u003csource\u003eApplied Sciences\u003c/source\u003e\u003cvolume\u003e10\u003c/volume\u003e\u003cfpage\u003e12\u003c/fpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.3390/app10124382\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_006","citeString":"Hamurcu, M. and Eren, T. 2020. Strategic planning based on sustainability for urban transportation: an application to decision-making. Sustainability 12(9): 1–24.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_006\"\u003e\u003cmixed-citation\u003eHamurcu, M. and Eren, T. 2020. Strategic planning based on sustainability for urban transportation: an application to decision-making. Sustainability 12(9): 1–24.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eHamurcu\u003c/surname\u003e\u003cgiven-names\u003eM.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eEren\u003c/surname\u003e\u003cgiven-names\u003eT.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eStrategic planning based on sustainability for urban transportation: an application to decision-making\u003c/article-title\u003e\u003csource\u003eSustainability\u003c/source\u003e\u003cvolume\u003e12\u003c/volume\u003e\u003cissue\u003e(9):\u003c/issue\u003e\u003cfpage\u003e1\u003c/fpage\u003e\u003clpage\u003e24\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.3390/su12093589\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_007","citeString":"Jubara, H. E. I. 2020. An efficient handover procedure in vehicular communication. 2nd International Conference on Computer and Information Sciences (ICCIS).","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_007\"\u003e\u003cmixed-citation\u003eJubara, H. E. I. 2020. An efficient handover procedure in vehicular communication. 2nd International Conference on Computer and Information Sciences (ICCIS).\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"other\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eJubara\u003c/surname\u003e\u003cgiven-names\u003eH. E. I.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eAn efficient handover procedure in vehicular communication\u003c/article-title\u003e\u003csource\u003e2nd International Conference on Computer and Information Sciences (ICCIS)\u003c/source\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/ICCIS49240.2020.9257665\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_008","citeString":"Leu, F. -Y., Tsai, K. -L. and Lin, S. -Y. 2019. E-ANDSF-based base station selection by using MLP in untrusted environments. IEEE Transactions on Industrial Informatics 15(10): 5708–5714.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_008\"\u003e\u003cmixed-citation\u003eLeu, F. -Y., Tsai, K. -L. and Lin, S. -Y. 2019. E-ANDSF-based base station selection by using MLP in untrusted environments. IEEE Transactions on Industrial Informatics 15(10): 5708–5714.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eLeu\u003c/surname\u003e\u003cgiven-names\u003eF. -Y.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eTsai\u003c/surname\u003e\u003cgiven-names\u003eK. -L.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eLin\u003c/surname\u003e\u003cgiven-names\u003eS. -Y.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2019\u003c/year\u003e\u003carticle-title\u003eE-ANDSF-based base station selection by using MLP in untrusted environments\u003c/article-title\u003e\u003csource\u003eIEEE Transactions on Industrial Informatics\u003c/source\u003e\u003cvolume\u003e15\u003c/volume\u003e\u003cissue\u003e(10):\u003c/issue\u003e\u003cfpage\u003e5708\u003c/fpage\u003e\u003clpage\u003e5714\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/TII.2019.2916335\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_009","citeString":"Naeem, B., Ngah, R. and Mohd Hashim, S. Z. 2019. Reduction in ping-pong effect in heterogeneous networks using fuzzy logic. Soft Computing 23: 269–283.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_009\"\u003e\u003cmixed-citation\u003eNaeem, B., Ngah, R. and Mohd Hashim, S. Z. 2019. Reduction in ping-pong effect in heterogeneous networks using fuzzy logic. Soft Computing 23: 269–283.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eNaeem\u003c/surname\u003e\u003cgiven-names\u003eB.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eNgah\u003c/surname\u003e\u003cgiven-names\u003eR.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eMohd Hashim\u003c/surname\u003e\u003cgiven-names\u003eS. Z.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2019\u003c/year\u003e\u003carticle-title\u003eReduction in ping-pong effect in heterogeneous networks using fuzzy logic\u003c/article-title\u003e\u003csource\u003eSoft Computing\u003c/source\u003e\u003cvolume\u003e23\u003c/volume\u003e\u003cfpage\u003e269\u003c/fpage\u003e\u003clpage\u003e283\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1007/s00500-018-3246-2\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_010","citeString":"Ndashimye, E., Sarkar, N. I. and Ray, S. K. 2020. A network selection method for handover in vehicle-to-infrastructure communications in multi-tier networks. Wireless Networks 2018: 1–15.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_010\"\u003e\u003cmixed-citation\u003eNdashimye, E., Sarkar, N. I. and Ray, S. K. 2020. A network selection method for handover in vehicle-to-infrastructure communications in multi-tier networks. Wireless Networks 2018: 1–15.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eNdashimye\u003c/surname\u003e\u003cgiven-names\u003eE.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eSarkar\u003c/surname\u003e\u003cgiven-names\u003eN. I.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eRay\u003c/surname\u003e\u003cgiven-names\u003eS. K.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eA network selection method for handover in vehicle-to-infrastructure communications in multi-tier networks\u003c/article-title\u003e\u003csource\u003eWireless Networks\u003c/source\u003e\u003cvolume\u003e2018\u003c/volume\u003e\u003cfpage\u003e1\u003c/fpage\u003e\u003clpage\u003e15\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1007/s11276-018-1817-x\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_011","citeString":"Nguyen, T. -H. and Jung, J. J. 2020. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. 16th International Conference on Intelligent Environments.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_011\"\u003e\u003cmixed-citation\u003eNguyen, T. -H. and Jung, J. J. 2020. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. 16th International Conference on Intelligent Environments.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"other\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eNguyen\u003c/surname\u003e\u003cgiven-names\u003eT. -H.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eJung\u003c/surname\u003e\u003cgiven-names\u003eJ. J.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eACO-based Approach on Dynamic MSMD Routing in IoV Environment\u003c/article-title\u003e\u003csource\u003e16th International Conference on Intelligent Environments\u003c/source\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/IE49459.2020.9154927\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_012","citeString":"Sheng, Z., Pressas, A., Ocheri, V., Ali, F., Rudd, R. and Nekovee, M. 2018. Intelligent 5G Vehicular Networks: An Integration of DSRC and mmWave Communications. International Conference on Information and Communication Technology Convergence (ICTC), IEEE.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_012\"\u003e\u003cmixed-citation\u003eSheng, Z., Pressas, A., Ocheri, V., Ali, F., Rudd, R. and Nekovee, M. 2018. Intelligent 5G Vehicular Networks: An Integration of DSRC and mmWave Communications. International Conference on Information and Communication Technology Convergence (ICTC), IEEE.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"other\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eSheng\u003c/surname\u003e\u003cgiven-names\u003eZ.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003ePressas\u003c/surname\u003e\u003cgiven-names\u003eA.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eOcheri\u003c/surname\u003e\u003cgiven-names\u003eV.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eAli\u003c/surname\u003e\u003cgiven-names\u003eF.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eRudd\u003c/surname\u003e\u003cgiven-names\u003eR.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eNekovee\u003c/surname\u003e\u003cgiven-names\u003eM.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2018\u003c/year\u003e\u003carticle-title\u003eIntelligent 5G Vehicular Networks: An Integration of DSRC and mmWave Communications\u003c/article-title\u003e\u003csource\u003eInternational Conference on Information and Communication Technology Convergence (ICTC), IEEE\u003c/source\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.1109/ICTC.2018.8539687\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_013","citeString":"Singh, A., Budakoti, J. and Lung, C. -H. 2020. Vertical handover decision for mobile IoT edge gateway using multi-criteria and fuzzy logic techniques. Advances in Internet of Things 10: 57–93.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_013\"\u003e\u003cmixed-citation\u003eSingh, A., Budakoti, J. and Lung, C. -H. 2020. Vertical handover decision for mobile IoT edge gateway using multi-criteria and fuzzy logic techniques. Advances in Internet of Things 10: 57–93.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eSingh\u003c/surname\u003e\u003cgiven-names\u003eA.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eBudakoti\u003c/surname\u003e\u003cgiven-names\u003eJ.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eLung\u003c/surname\u003e\u003cgiven-names\u003eC. -H.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2020\u003c/year\u003e\u003carticle-title\u003eVertical handover decision for mobile IoT edge gateway using multi-criteria and fuzzy logic techniques\u003c/article-title\u003e\u003csource\u003eAdvances in Internet of Things\u003c/source\u003e\u003cvolume\u003e10\u003c/volume\u003e\u003cfpage\u003e57\u003c/fpage\u003e\u003clpage\u003e93\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.4236/ait.2020.104005\u003c/dgdoi:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"},{"refId":"j_ijssis-2021-012_ref_014","citeString":"Storck, C. R. and Duarte-Figueiredo, F. 2019. A 5G V2X ecosystem providing internet of vehicles. Sensors 19: 1–20.","doi":null,"mixed-citation":"\u003cref id=\"j_ijssis-2021-012_ref_014\"\u003e\u003cmixed-citation\u003eStorck, C. R. and Duarte-Figueiredo, F. 2019. A 5G V2X ecosystem providing internet of vehicles. Sensors 19: 1–20.\u003c/mixed-citation\u003e\u003celement-citation publication-type=\"journal\" publication-format=\"print\"\u003e\u003cperson-group person-group-type=\"author\"\u003e\u003cname\u003e\u003csurname\u003eStorck\u003c/surname\u003e\u003cgiven-names\u003eC. R.\u003c/given-names\u003e\u003c/name\u003e\u003cname\u003e\u003csurname\u003eDuarte-Figueiredo\u003c/surname\u003e\u003cgiven-names\u003eF.\u003c/given-names\u003e\u003c/name\u003e\u003c/person-group\u003e\u003cyear\u003e2019\u003c/year\u003e\u003carticle-title\u003eA 5G V2X ecosystem providing internet of vehicles\u003c/article-title\u003e\u003csource\u003eSensors\u003c/source\u003e\u003cvolume\u003e19\u003c/volume\u003e\u003cfpage\u003e1\u003c/fpage\u003e\u003clpage\u003e20\u003c/lpage\u003e\u003cdgdoi:pub-id xmlns:dgdoi=\"http://degruyter.com/resources/doi-from-crossref\" pub-id-type=\"doi\"\u003e10.3390/s19030550\u003c/dgdoi:pub-id\u003e\u003cdgpm:pub-id xmlns:dgpm=\"http://degruyter.com/resources/fetched-pubmed-id\" pub-id-type=\"pmcid\"\u003e6386933\u003c/dgpm:pub-id\u003e\u003cdgpm:pub-id xmlns:dgpm=\"http://degruyter.com/resources/fetched-pubmed-id\" pub-id-type=\"pmid\"\u003e30699926\u003c/dgpm:pub-id\u003e\u003c/element-citation\u003e\u003c/ref\u003e"}],"pdfUrl":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/10.21307_ijssis-2021-012.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=b4d763618aecd8452ebcf71b4a2502627c0bb0d375013274d152643841980034","authorNotes":"{\"fn\":{\"p\":\"This paper was edited by Subhas Chandra Mukhopadhyay.\"}}","publishMonth":"06","publishYear":"2021","receivedDate":"2021-01-16T00:00:00.000+00:00","acceptedDate":null,"ePubDate":"2021-06-28T00:00:00.000+00:00","ePubDateText":"28 June 2021","pPubDate":"2021-01-01T00:00:00.000+00:00","pPubDateText":"01 January 2021","issueDate":null,"coverDate":"2021-01-01T00:00:00.000+00:00","tableCount":null,"figureCount":null,"refCount":null,"articleCategories":"","titleGroup":"{\"alt-title\":{\"alt-title-type\":\"running-head\",\"italic\":\"Hussain et al.\",\"content\":\"Vertical Handover (VHO) in Internet of Vehicles (IoV):\"},\"article-title\":\"Performance evaluation of vertical handover in Internet of Vehicles\"}","fundingGroup":null,"abstractContent":[{"title":"Abstract","language":"English","content":"\u003cabstract\u003e\u003ctitle style='display:none'\u003eAbstract\u003c/title\u003e\u003cp\u003eInternet of Vehicles (IoV) is developed by integrating the intelligent transportation system (ITS) and the Internet of Things (IoT). The goal of IoV is to allow vehicles to communicate with other vehicles, humans, pedestrians, roadside units, and other infrastructures. Two potential technologies of V2X communication are dedicated short-range communication (DSRC) and cellular network technologies. Each of these has its benefits and limitations. DSRC has low latency but it limits coverage area and lacks spectrum availability. Whereas 4G LTE offers high bandwidth, wider cell coverage range, but the drawback is its high transmission time intervals. 5G offers enormous benefits to the present wireless communication technology by providing higher data rates and very low latencies for transmissions but is prone to blockages because of its inability to penetrate through the objects. Hence, considering the above issues, single technology will not fully accommodate the V2X requirements which subsequently jeopardize the effectiveness of safety applications. Therefore, for efficient V2X communication, it is required to interwork with DSRC and cellular network technologies. One open research challenge that has gained the attention of the research community over the past few years is the appropriate selection of networks for handover in a heterogeneous IoV environment. Existing solutions have addressed the issues related to handover and network selection but they have failed to address the need for handover while selecting the network. Previous studies have only mentioned that the network is being selected directly for handover or it was connected to the available radio access. Due to this, the occurrence of handover had to take place frequently. Hence, in this research, the integration of DSRC, LTE, and mmWave 5G is incorporated with handover decision, network selection, and routing algorithms. The handover decision is to ensure whether there is a need for vertical handover by using a dynamic Q-learning algorithm. Then, the network selection is based on a fuzzy-convolution neural network that creates fuzzy rules from signal strength, distance, vehicle density, data type, and line of sight. V2V chain routing is proposed to select V2V pairs using a jellyfish optimization algorithm that takes into account the channel, vehicle characteristics, and transmission metrics. This system is developed in an OMNeT++ simulator and the performances are evaluated in terms of mean handover, handover failure, mean throughput, delay, and packet loss.\u003c/p\u003e\u003c/abstract\u003e"}],"figures":[{"label":"Figure 1:","caption":"Workflow procedure of ANDSF (Ndashimye et al., 2020).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=d7f4b1353ff7030ffd85d3549b15458d2b06c94facc2f49fc190c45685ad692e"},{"label":"Figure 2:","caption":"Proposed system model.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=7c8e1b2b5904d103545e0a04963db98c313496900499931f6daabcce70b1809b"},{"label":"Figure 3:","caption":"Workflow of dynamic Q-learning.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=7343cb6b31b0e31544f4f0cd228cea5dd72b2e6a5e79d9ebeb6c161b4f959ec0"},{"label":null,"caption":null,"imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=007b7cb6f8dc5dc92c34cf0a8e193ec40fcd496ffda4727cc93cbb39fa03cf8a"},{"label":"Figure 4:","caption":"Fuzzy-convolutional neural network.","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=dd1de1b23b1402cf8df6d99161a6253bb07b75b28cde35656d232b19feac4e8f"},{"label":null,"caption":null,"imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=29c2f59577776976b5bd1faa22634c6ad37cf80d7160d34fb96213f414613d7d"},{"label":"Figure 5:","caption":"Comparison of mean handover (Ndashimye et al., 2020; Sheng et al., 2018).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=3e5c8fda9455086f35cf5bdb7f32631a948797d41c755dfa6c51e5edcab42ac5"},{"label":"Figure 6:","caption":"Comparison of HO failure (Ndashimye et al., 2020; Sheng et al., 2018).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=055e08cf21dda6ba730cf94a1888636b00b7aa3af0e07ae95f1a9e1562f5ca00"},{"label":"Figure 7:","caption":"Comparison of throughput (Ndashimye et al., 2020; Sheng et al., 2018).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=08567be3e13fa07225c15570ac6a28b13ce573313174e97d12ce9706261c0e82"},{"label":"Figure 8:","caption":"Comparison of end-to-end delay (Ndashimye et al., 2020; Sheng et al., 2018).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_008.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=37df6a93aea33af2bafc280bfc1445624f78c5b86ce281b1b78ed6da7020ee3a"},{"label":"Figure 9:","caption":"Comparison on packet loss (Ndashimye et al., 2020; Sheng et al., 2018).","imageLink":"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_009.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026X-Amz-Date=20230203T065859Z\u0026X-Amz-SignedHeaders=host\u0026X-Amz-Expires=18000\u0026X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026X-Amz-Signature=1439d9dead49c156ab3acbc1c1230896fd05f7a75067574d0981beee475cfea4"}],"tableContent":{"Comparison of HO efficiency.":"\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eMethod\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eAverage number of HO\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eAverage HO\u003csub\u003e\u003citalic\u003eFR\u003c/italic\u003e\u003c/sub\u003e\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eConventional\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e5.51\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e55%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.133\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e90%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTOPSIS\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2.15\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e20%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.041\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e40%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eANDSF-HO\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e3.57\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e30%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.069\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e60%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eV2I-MoLoHA\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e3.03\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e25%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.029\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e20%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eProposed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e1.30\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.01\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e","Fuzzy rules.":"\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"/\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"5\"\u003eInput\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eRule number\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e\u003citalic\u003eS\u003c/italic\u003e\u003csub\u003e\u003citalic\u003er\u003c/italic\u003e\u003c/sub\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eDistance\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e\u003citalic\u003eV\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eD\u003c/italic\u003e\u003c/sub\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eData type\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eLoS\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eOutput\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR1\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR2\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR3\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR4\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR5\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR6\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR7\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR8\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR9\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR10\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR11\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR12\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR13\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR14\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR15\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR16\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR17\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR18\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR19\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR20\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR21\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR22\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR23\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR24\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR25\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR26\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR27\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR28\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR29\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR30\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR31\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR32\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e","Simulation specifications.":"\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eParameter\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eRange/Value\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eSimulation area\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2,500 m × 2,500 m\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eNumber of vehicles\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e100\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eNumber of 5G mmWave BSs\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eNumber of 4G LTE BSs\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eVehicle mobility type\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eLinear mobility\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eVehicle speed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e10-40 m/s\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"2\"\u003eTransmission range\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e DSRC\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e300 m (Max)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e mmWave\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e~500 m\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e LTE\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e100 km (Max)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTransmission rate\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e3-5 packets per second\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003ePacket size\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e512 bytes\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eSimulation time\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e1,000 sec\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e","Comparison of throughput and delay.":"\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eMethod\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eMean \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_011.png\"/\u003e\u003cmml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmml:mi\u003eT\u003c/mml:mi\u003e\u003c/mml:math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e (kbps)\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eAverage delay (ms)\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eConventional\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e13.7\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e46%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e39\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e21%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTOPSIS\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e35.96\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e23%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e30\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e12%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eANDSF-HO\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e25\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e34%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e37\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e19%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eV2I-MoLoHA\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e31.89\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e27%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e34\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e16%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eProposed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e58.89\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e18\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e","Comparison of packet loss.":"\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eMethod\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003ePacket loss (%)\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eConventional\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e48\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e21%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTOPSIS\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e32.4\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e12%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eANDSF-HO\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e24\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e19%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eV2I-MoLoHA\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e18.8\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e16%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eProposed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e12\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e"},"tables":null,"articleContent":"\n\u003cdiv\u003e\u003csec id=\"j_ijssis-2021-012_s_001\"\u003e\u003ctitle/\u003e\u003cp\u003eThe goal of IoV is to allow vehicles to communicate with other vehicles, humans, pedestrians, roadside units, and other infrastructures. Such communications are classified into five categories that are referred to as V2X communication (X: vehicles, RSU, infrastructure, humans, and pedestrians). The vehicles transfer both safety and non-safety data at different data rates. Safety data as an accident, road traffic, and others, while non-safety data such as video streaming, gaming, and so on. Integration of IoV with advanced wireless communication technologies such as 5G makes it a heterogeneous network (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e). It composes of Wi-Fi, Long-Term Evolution (LTE), and others. In general, vehicle communication is supported for both safety and non-safety data transmissions. The vehicles use dedicated short-range communication (DSRC) which enables low latency communication for short-distance vehicles.\u003c/p\u003e\u003cp\u003eIn IoV, vehicles use DSRC for communication; however, due to its shorter range and bandwidth limitations, it is not suitable for long-distance communications and bandwidth greedy applications. Hence, IoV integrates with 5G to provide high data rates for communication. However, it suffers from blockage issues as it is unable to penetrate through obstacles (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_004\"\u003eChoi et al., 2018\u003c/a\u003e). Besides, LTE also provides long-distance communication because of its coverage range, and high bandwidth features. Each radio access technology has its benefits and limitations.\u003c/p\u003e\u003cp\u003eVehicles are equipped with multiple antenna terminals that enable to access different radio access network (RAN). Due to the use of different RAN in a network, a network introduces the process of vertical handover (VHO) (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_012\"\u003eSheng et al., 2018\u003c/a\u003e). 5G comprises different radio access technologies due to the presence of different cells such as microcell, femtocell, and nanocell. Each cell will be having more than one RAN and hence, requires selection of the best network (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_007\"\u003eJubara, 2020\u003c/a\u003e). Several multi-criteria decision-making algorithms have been proposed for network selection. In general, this type of algorithm takes into account multiple parameters and computes them for decision-making. The TOPSIS is one of the decision-making algorithms. This type of multi-criteria decision algorithms is popular in the selection of networks. IoV enables allowing data transmission of the highway and urban roadways in an autonomous vehicle (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_014\"\u003eStorck and Duarte-Figueiredo, 2019\u003c/a\u003e). If there is an increase in the vehicle density, then the number of requests from the vehicles for vertical handover will also gradually increase.\u003c/p\u003e\u003cp\u003eThe vehicle is built with more than one antenna terminal. The support of different RAN technologies requires selecting a network when one or more RAN is present in the coverage range.\u003c/p\u003e\u003cp\u003eThe network selection process is also performed using optimization, reinforcement learning methods, and access network discovery and selection function (ANDSF) (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e). Q-learning is an algorithm that can decide concerning the environment. In IoV, vehicles move at very high speeds with change in topology and connectivity, the data transmission relies on routing (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e). Routing is the process of transferring data from source to destination through relay vehicles (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e). In routing, the vehicles in a route are preferred by taking into account the vehicle-based metrics like traffic, vehicle capacity, reliability, mobility, and others. As per the estimation of the metrics, a route or path is identified and packet forwarding is performed in that route. The process of routing is subjected to some challenges as topology changes, time consumption in route selection, and so on. The algorithms and methods are proposed to solve these challenging issues.\u003c/p\u003e\u003cp\u003eThe goal of this paper is to minimize the number of unnecessary handovers when there is a need for high bandwidth while the data type changes. This research builds a learning-based method to decide whether there is a need for handover and then it selects a network for handover. In this way, we can reduce the number of unnecessary handovers. Then, V2V routing is established to minimize the number of re-transmissions. A poor selection of transmission routes causes route failure that leads to an increase in the number of re-transmissions. To solve this issue, an optimization algorithm is used. The two main contributions of our proposed work are to perform handover using network selection and data transmission via the best route.\u003c/p\u003e\u003cp\u003eThe rest of this paper is organized as follows: the second section presents the previous research works and methods, the third section gives a particular problem description, and the fourth section discusses the proposed algorithms of handover, network selection, and routing. The fifth section discusses the simulation results, and the sixth section depicts the conclusion with future research directions.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_002\"\u003e\u003cdiv\u003eRelated work\u003c/div\u003e\u003csec id=\"j_ijssis-2021-012_s_002_s_001\"\u003e\u003cdiv\u003ePrior works on handover\u003c/div\u003e\u003cp\u003eHandover (HO) in the vehicular network is challenging to perform since the mobility of vehicles changes. Many research works have studied this issue and performed handover without any degradation in network metrics. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_003\"\u003eChang et al. (2019)\u003c/a\u003e, a cluster-based handoff, and dynamic edge-backup node (DEBCK) is proposed where the vehicles on the road lane were clustered, and the backup node provides handoff. Here, the cluster head performs the handoff and the backup mobile edge vehicle. The three main parameters that were taken into account for handoff are storage, communication, and energy. The main drawback of this work is poor handoff performance of backup mobile edge and cluster head, and failure to perform handoff whenever there is a need. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_007\"\u003eJubara (2020)\u003c/a\u003e a procedure for HO was proposed with the aim of minimization of delay in HO. A cross-layer protocol in an adaptive L4 HO procedure begins to estimate signal strength and if the quality of the signal was poor, then the link between user and base station disconnects. Then the Stream Control Transmission Protocol (SCTP) is assigned to the new IP and it is updated to the layers. However, the signal strength was not the only significant metric to make HO decisions. Due to the mobility of the vehicle and moving pattern on the road lane, HO of moving vehicles was proposed (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_004\"\u003eChoi et al., 2018\u003c/a\u003e). According to the idea of this work, a group of users consists of a mail leader, sub-leader, and follower. The sub-leader was selected based on the maximum number of connections. In case if more than one vehicle has similar characteristics then, a sub-leader was selected at random. Initially, the vehicle computes reference signal received power (RSRP), reference signal received quality (RSRQ), link quality, and is reported for HO decision. A decision tree was built for HO decision-making using RSRP measurement. But the vehicles HO in a group requires frequent computation in the group, as well as measurement, and hence the computation will be higher in this work. The network layer-based L2 extension HO scheme was proposed (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_009\"\u003eNaeem et al., 2019\u003c/a\u003e) and the architecture consists of an access router (AR), roadside unit (RSU), and vehicles. This work defines two HO schemes as inter-AR HO and intra-AR HO. The key goal of this scheme was to minimize latency and improve the packet delivery ratio. A fuzzy logic model and Elman Neural Network (ANN) was designed to decide along with the assurance of QoS (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_009\"\u003eNaeem et al., 2019\u003c/a\u003e). For HO decisions, the parameters that are taken into account as cost, transmission range, velocity, load, and capacity. Even though this work performs better, the time for HO decision consumes time which increases the delay in the HO that may cause packet drop and degrades packet delivery ratio. The paper (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_013\"\u003eSingh et al., 2020\u003c/a\u003e) concentrates on handover as well as routing. A handoff protocol was proposed that computes link expiration time (LET) for detecting the connectivity between vehicles. The partner selection protocols enable a selection of optimal partner nodes (PN). Initially, the route was determined from GPS information and then the partner in the routes was selected from the vehicular LET using the traffic information. The vehicle with a high LET will be selected as the optimal PN in the route. In this work, only a single metric was taken into account for selecting a route between source and destination. However, if an opposite moving vehicle with high LET cannot be selected as PN and hence it requires considering other parameters too. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_008\"\u003eLeu et al. (2019)\u003c/a\u003e, and enhanced Access Network Discovery and Selection Function (ANDSF) was presented to perform a BS selection in the network. This algorithm combines with multilayer perceptron (MLP). The parameters were load, signal strength, throughput, and delay. The traditional workflow of the ANDSF is illustrated in \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_001\"\u003eFigure 1\u003c/a\u003e.\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_001\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 1:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eWorkflow procedure of ANDSF (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_001.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=d7f4b1353ff7030ffd85d3549b15458d2b06c94facc2f49fc190c45685ad692e\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eThe ANDSF was equipped within the EPC which was started to be used in 3G and also on advanced radio access networks. This server was employed to discover information, manage policies, select policies, manage rules, and others. The user equipment can be a sensor, vehicle, or any other device that can access radio technology. The server first discovers the device and then performs a change in the connectivity. The procedure works by the developed set of rules and policies.\u003c/p\u003e\u003cp\u003eThe vertical HO was performed using multi-criteria methods by taking into account the significant parameters such as QoS, delay, cost, and others (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_006\"\u003eHamurcu and Eren, 2020\u003c/a\u003e). Due to the consideration of multiple metrics for HO decision using enhanced Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) fuzzy logic (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_005\"\u003eEmbus et al., 2020\u003c/a\u003e). The working of this combination of algorithm works as per the following steps:\u003clist id=\"j_ijssis-2021-012_list1\" list-type=\"bullet\"\u003e\u003clist-item\u003e\u003cp\u003eStep 1: creates decision matrix using the parameters that were involved for HO decision. The computation was executed for each available network in the coverage area.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eStep 2: apply the Euclidean distance formula for determining the normalized decision matrix.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eStep 3: computation of weighted normalized decision matrix based on the function of the cross product.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eStep 4: estimate two ideal solutions as positive and negative from the cost metric. Hereby a set of benefit-based criteria were used for positive ideal solution prediction.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eStep 5: again use the Euclidean distance formula and determine the distance value for the estimated ideal solution.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eStep 6: compute relative closeness using the determined ideal solution in previous steps.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eStep 7: at the end, the ranking was performed from the determined closeness for each network, and based on this ranking, the best network was selected for HO.\u003c/p\u003e\u003c/list-item\u003e\u003c/list\u003e\u003c/p\u003e\u003cp\u003eThe processing steps illustrated above for enhanced TOPSIS using fuzzy were able to overwhelm the problems in conventional RSS-based HO. Each step includes multiple criteria, these steps were not parallel, i.e. on each HO request, all the process requires to be performed and the decision was made after ranking.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_002_s_002\"\u003e\u003cdiv\u003ePrior works on routing\u003c/div\u003e\u003cp\u003eThe IoV environment that uses different types of radio access network due to the coverage range of each radio access. However, the vehicles have in-built DSRC for short-range data transmission, while the destination vehicle moves far from the source, then a route has to be preferred for data transmission.\u003c/p\u003e\u003cp\u003eVehicles perform routing by selecting relay vehicles between the source and destination since the DSRC range was small and hence it is not able to connect longer distance vehicles. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_011\"\u003eNguyen and Jung (2020)\u003c/a\u003e, Ant Colony Optimization (ACO) algorithm is proposed with the idea of coloring vehicles. This algorithm presents two processes as solution construction and pheromone update. The idea of coloring was to give similar colors for the vehicles that have the same destination. As per the pheromone value, the route was selected in this work. However, this work failed to consider the significant parameters of the vehicles for the computation of the pheromone value that decides the transmission route. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_001\"\u003eAl-Kharasani et al. (2020)\u003c/a\u003e, a cluster-based adept cooperative algorithm (CACA) is proposed focusing on the QoS metrics. As per this work, clustering formation is done and a cluster head was selected. This work follows Optimized Link State Routing (OLSR) protocol with the Multi-Point Relay (MPR). This selection takes into account mobility factors, distance range, and quality of path (QoP). The vehicles that satisfy these parameters were selected as MPR and then the intersection vehicles were eliminated. The selection of MPR was not efficient, since the vehicles move at high speed. A protocol design was proposed, i.e. partner selection protocol that considers Vehicle Link Expiration Time (VLET) (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e). In this work the handoff means a vehicle disconnects from a partner node and joins a new partner node (PN), the partner node enables to perform data transmission. The only measure that was used in the selection of PN was not efficient since there are other significant metrics as signal strength which was also essential in node selection. A cross-layer design was proposed (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_008\"\u003eLeu et al., 2019\u003c/a\u003e) that selects an optimal route based on the metrics forwarding probability, bandwidth, and link duration. The forwarding probability for the vehicle was formulated by considering velocity, distance, and communication range. The link duration was mathematically calculated as communication link lifetime that takes into account vehicle velocity, GPS location, and communication range. Then, the third parameter of bandwidth was calculated from link gain, noise power, and channel bandwidth.\u003c/p\u003e\u003cp\u003eThe relay node selection was presented in the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_002\"\u003eCao et al. (2019)\u003c/a\u003e for relay selection using the estimation of curving rate. A double direction relay node selection was involved when the request to broadcast (RTB) was 1 and then it select relay from the estimation of curving rate, delivery ratio, one-hop delay, and message dissemination speed. The curving rate was formulated from the road length and the range of the vehicle. The computation of each parameter one after the other for route selection was time consuming and it leads to higher packet drop.\u003c/p\u003e\u003cp\u003eRouting is also performed using optimization algorithms. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_008\"\u003eLeu et al. (2019)\u003c/a\u003e, a hybrid optimization algorithm is proposed combining monarch butterfly and gray wolf optimization for route selection. The parameters that were taken into account for route selection are different costs computed for congestion, collision, travel, and QoS. For QoS prediction, fuzzy membership functions were applied. Initially, the butterfly algorithm was involved and then the gray wolf was performed for position updates and selecting optimal paths. The traditional issue in gray wolf optimization is its poor performance, and low accuracy. Fuzzy logic was also used to select routes by estimating link quality and achievable throughput. The link quality was based on the position, direction, and expected transmission count. As per the fuzzy weight, the output of the selection of next hop relay was performed. However, this work failed to tolerate the mobility issues concerning vehicular communication.\u003c/p\u003e\u003c/sec\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_003\"\u003e\u003cdiv\u003eProblem definition\u003c/div\u003e\u003cp\u003eIssues concerning handover, network selection, and routing are discussed in this section from the previous research works. In the study of \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al. (2020)\u003c/a\u003e, the author proposed reinforcement learning algorithms. TOPSIS, K-Nearest Neighbor (K-NN), and AHP are proposed for handoff decisions considering bandwidth, network cost, preferences, connectivity probability, and signal to noise ratio (SNR) as the evaluation metrics.\u003clist id=\"j_ijssis-2021-012_list2\" list-type=\"bullet\"\u003e\u003clist-item\u003e\u003cp\u003eTOPSIS algorithm are subjected to rank reversal problem that either includes or eliminates the order of preferences. Besides this problem, it performs poorly to make vertical handover decisions.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eThe handover is performed by the vehicle based on the ranking results the vehicle. However, the need for handover is not evaluated. Also, if all the vehicles requests for handover then TOPSIS had to perform the handover individually since the parameters differs for each vehicle.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eThe use of k-NN for handover decisions was not efficient, since the k-NN algorithm gives higher accuracy in results only when the link quality was better. Also while the arrival of data was in large amount then the algorithm slows down to process and hence it takes time to make handover decisions.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eThe data forwarding through these two metrics is not sufficient, since there may be a blockage that causes NLOS issues. This issue was common in mmWave and hence vehicle parameters are essential to be considered while making forwarding decisions.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eThe use of AHP was not efficient since it requires training of the data and then it can select the best path. But here as per the current situation of the vehicles the path needs to be selected and also the movement of vehicles will not be the same in all the regions. Also, the addition of new criteria was difficult in this algorithm.\u003c/p\u003e\u003c/list-item\u003e\u003c/list\u003e\u003c/p\u003e\u003cp\u003eSeveral algorithms have been proposed for the process of routing. Dijkstra algorithm and random relay selection are proposed for routing and data forwarding (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_002\"\u003eCao et al., 2019\u003c/a\u003e). QoS parameters are computed and estimated for the selection of routes. Since the movement of vehicles is dynamic and so, the management of the topologies is achieved by constructing the graphs.\u003c/p\u003e\u003cp\u003eThe major problems identified in routing are as follows:\u003clist id=\"j_ijssis-2021-012_list3\" list-type=\"bullet\"\u003e\u003clist-item\u003e\u003cp\u003eThe graph parameters are completely based on the past transmission history of the vehicles and the transmission of the vehicles depends on the channel metrics. Using these metrics, the graph was not able to predict the signal strengths with its neighboring vehicle. Consequently causing frequent handover.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eThe maintenance of graphs is complex due to mobility concerns, hence it needs large resource blocks and dynamic processing to manage the graph.\u003c/p\u003e\u003c/list-item\u003e\u003clist-item\u003e\u003cp\u003eThe random selection of radio networks with individual parameters may leads to poor performance of networks since the main constraints of QoS in this work is bandwidth or delay, i.e. it considers anyone from this, and hence the network selection is poor.\u003c/p\u003e\u003c/list-item\u003e\u003c/list\u003e\u003c/p\u003e\u003cp\u003eAll of the above-highlighted gaps concerning handover, network selection, and routing are addressed in our proposed work.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_004\"\u003e\u003cdiv\u003eProposed system\u003c/div\u003e\u003cp\u003eThis section is broken down into four sub-sections to describe the environment and expand each algorithm concerning handover, network selection, and routing in this proposed research work.\u003c/p\u003e\u003csec id=\"j_ijssis-2021-012_s_004_s_001\"\u003e\u003cdiv\u003eSystem model\u003c/div\u003e\u003cp\u003eThe proposed heterogeneous IoV network is designed with vehicles consisting of a 5G base station, LTE base station, RoadSide Unit (RSU), and vehicles. The entities that participates in this system are defined below.\u003c/p\u003e\u003cp\u003eDefinition 1: Vehicle – the vehicle moves on a restricted path, i.e. on-road lane in which the path is pre-defined in a map. The moving speed of the vehicle depends on the vehicle. Vehicles have in-build GPS, using which their latitude and longitude information is gathered. The location of the vehicle and the speed of the vehicle is dynamic. Vehicles use DSRC and other advance Ran for data transmission. It transmits safety and non-safety data.\u003c/p\u003e\u003cp\u003eDefinition 2: RSU – RSU is employed in IoV for performing communication with the infrastructure. This entity is static in the environment and also it enables DSRC for vehicles.\u003c/p\u003e\u003cp\u003eDefinition 3: 5G mmWave base station (BS) – the BS is static and this allows to perform high speed–short-range communication. It can solve the lack of spectrum issue.\u003c/p\u003e\u003cp\u003eDefinition 4: LTE BS – this BS is also static and it allows long-distance communication with higher bandwidth and comparatively high spectrum efficiency.\u003c/p\u003e\u003cp\u003eThe proposed system model is depicted in \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_002\"\u003eFigure 2\u003c/a\u003e, which composes all the above-defined entities into the system. The road lane has ‘n’ number of moving vehicles in their direction on the road. In this work, the handover is a decision that will be taken by the vehicle only when the current base station link is not good. But in case of sudden need in transmitting a safety application, it makes network selection process at that moments along with the consideration of data type as one of the parameters. Handover decision is the decision by which the need for handover is determined and it performs handover to the available network. For handover decision dynamic Q-learning in which the threshold is set as per the environment. If the handover has to be performed, it then selects a network from fuzzy-convolution neural network (F-CNN). For network selection, the fuzzy rules are defined and used in CNN. Then routing takes place by using an optimization algorithm called jellyfish algorithm that selects V2V pairs between source to destination and so, it is called V2V chain routing.\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_002\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 2:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eProposed system model.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_002.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=7c8e1b2b5904d103545e0a04963db98c313496900499931f6daabcce70b1809b\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_004_s_002\"\u003e\u003cdiv\u003eHandover decision\u003c/div\u003e\u003cp\u003eHandover decision by dynamic Q-learning, the dynamic means to use threshold concerning the available network. Dynamic Q-learning algorithm determines the need for handover by evaluating vehicle speed and signal strength. We set the threshold for signal strength using Shannon entropy rule as shown in the following equation:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_001\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_001.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(1)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi\u003eS\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003es\u003c/mi\u003e\u003cmi\u003es\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmi\u003eE\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e[\u003c/mo\u003e\u003cmrow\u003e\u003cmo\u003e−\u003c/mo\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi\u003elog\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003es\u003c/mi\u003e\u003cmi\u003es\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e]\u003c/mo\u003e\u003c/mrow\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e(1)where \u003citalic\u003eS\u003c/italic\u003e(\u003citalic\u003ess\u003c/italic\u003e) denotes the Shannon entropy for signal strength that composes of \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_001.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi mathvariant=\"italic\"\u003ess\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e values for DSRC, mmWave, and LTE that range between (‒30 to ‒70 dBm). \u003citalic\u003eP\u003c/italic\u003e(\u003citalic\u003ess\u003c/italic\u003e) denotes the probability of the signal strength (\u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_003\"\u003eFigure 3\u003c/a\u003e).\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_003\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 3:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eWorkflow of dynamic Q-learning.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_003.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_003.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=7343cb6b31b0e31544f4f0cd228cea5dd72b2e6a5e79d9ebeb6c161b4f959ec0\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eLet \u003citalic\u003eQ\u003c/italic\u003e(\u003citalic\u003eS,A\u003c/italic\u003e) represent state \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_002.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eS\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e and action \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_003.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eA\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e based on the \u003citalic\u003eQ\u003c/italic\u003e-values. Each state \u003citalic\u003eS\u003c/italic\u003e will have two parameters and this \u003citalic\u003eQ\u003c/italic\u003e(\u003citalic\u003eS,A\u003c/italic\u003e) is determined and updated in the rule. The temporal difference update rule is as follows:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_002\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_002.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(2)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi\u003eQ\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eS\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmi\u003eA\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmi\u003eα\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmi\u003eγ\u003c/mi\u003e\u003cmi\u003eQ\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmrow\u003e\u003cmi\u003eS\u003c/mi\u003e\u003cmo\u003e′\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eA\u003c/mi\u003e\u003cmo\u003e′\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e−\u003c/mo\u003e\u003cmi\u003eQ\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eS\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmi\u003eA\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e→\u003c/mo\u003e\u003cmi\u003eQ\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eS\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmi\u003eA\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eThe term \u003citalic\u003eQ\u003c/italic\u003e(\u003citalic\u003eS\u003c/italic\u003e\u003csup\u003e\u003citalic\u003e΄\u003c/italic\u003e\u003c/sup\u003e\u003citalic\u003e,A\u003c/italic\u003e\u003csup\u003e\u003citalic\u003e΄\u003c/italic\u003e\u003c/sup\u003e) defines next state and action \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_004.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eR\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e is the reward given by the agent, \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_005.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eγ\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e is the discount factor that is [0–1], then \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_006.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eα\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e is the learning rate [0–1], i.e. it denotes the step length to estimate the (\u003citalic\u003eS,A\u003c/italic\u003e). The action is taken using \u003citalic\u003eϵ-\u003c/italic\u003egreedy policy where \u003citalic\u003eϵ\u003c/italic\u003e represents epsilon. The pseudo-code for dynamic Q-learning is given below to decide the decision for handover:\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_unfig_001\" fig-type=\"figure\"\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_unfig_001.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_001.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=007b7cb6f8dc5dc92c34cf0a8e193ec40fcd496ffda4727cc93cbb39fa03cf8a\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_004_s_003\"\u003e\u003cdiv\u003eNetwork selection\u003c/div\u003e\u003cp\u003eNetwork selection is the process of selecting a network from the available RANs. F-CNN algorithm is applied for network selection. The CNN is designed with layers of convolution, max-pooling, and fully connected layers. The layers are employed with fuzzy rules that are defined from the metrics signal strength, the distance between BS and vehicle, vehicle density in serving BS, data type (safety or non-safety), and line of sight. The definition for each metric is depicted below.\u003c/p\u003e\u003cp\u003eDefinition 1: Signal strength – signal strength defines the SNR which gives the number of signals. A channel will compose noise as well as signal, the high the noise, the channel is unfit for transmission. The SNR (\u003citalic\u003eS\u003c/italic\u003e\u003csub\u003e\u003citalic\u003er\u003c/italic\u003e\u003c/sub\u003e) is determined from signal power \u003citalic\u003eP\u003c/italic\u003e\u003csub\u003e\u003citalic\u003es\u003c/italic\u003e\u003c/sub\u003e, and noise \u003citalic\u003eP\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eN\u003c/italic\u003e\u003c/sub\u003e respectively. The formulation is:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_003\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_003.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(3)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eS\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003er\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003es\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003en\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eDefinition 2: Distance between BS and vehicle – the distance between BS and a vehicle is estimated using Euclidean distance. This measure defines the stability of the link, as the distance increases the link will be unstable and when the distance decreases the link will be stronger. Euclidean distance is computed using the following equation:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_004\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_004.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(4)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eD\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eB\u003c/mi\u003e\u003cmi\u003eS\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eV\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmsqrt\u003e\u003cmrow\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003ex\u003c/mi\u003e\u003cmo\u003e−\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ex\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/msup\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003ey\u003c/mi\u003e\u003cmo\u003e−\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ey\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/msup\u003e\u003c/mrow\u003e\u003c/msqrt\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eFor computing distance, the coordinate points of the BS and vehicle is used. Distance \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_007.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eD\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eB\u003c/mi\u003e\u003cmi\u003eS\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eV\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e is determined from the BS location coordinates of (\u003citalic\u003ex,y\u003c/italic\u003e), and vehicle location coordinates of (\u003citalic\u003ex\u003c/italic\u003e\u003csub\u003e1\u003c/sub\u003e\u003citalic\u003e,y\u003c/italic\u003e\u003csub\u003e1\u003c/sub\u003e), respectively. The location of BS is fixed and so it requires to know only the vehicle coordinate for distance estimation.\u003c/p\u003e\u003cp\u003eDefinition 3: Vehicle density – the density of vehicle \u003citalic\u003eV\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eD\u003c/italic\u003e\u003c/sub\u003e denotes the number of vehicles that are connected with that particular BS.\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_005\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_005.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(5)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eV\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eD\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmo\u003e∑\u003c/mo\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eC\u003c/mi\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e(5)where \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eCL\u003c/italic\u003e\u003c/sub\u003e and \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eNL\u003c/italic\u003e\u003c/sub\u003e represents the number of connected links and number of new links.\u003c/p\u003e\u003cp\u003eDefinition 4: Data type – the data type in vehicles are two, they are safety and non-safety. In this work, safety is denoted as 0 and non-safety as 1. The safety messages will be of traffic information, high-speed vehicle information. This type of data has a higher priority in transmission than the non-safety data.\u003c/p\u003e\u003cp\u003eDefinition 5: LoS – line of sight defines the direct contact between the vehicle and BS without any obstacles that block the signals. For transmission, LoS is only preferred and the signals in Non-LoS are not preferred.\u003c/p\u003e\u003cp\u003eThe above five metrics involve the development of fuzzy rules. The fuzzy logic deals with the decision-making by the defined rules as shown in \u003ca ref-type=\"table\" href=\"#j_ijssis-2021-012_tab_001\"\u003eTable 1\u003c/a\u003e. The mmWave signals will be chosen for any type of traffic, but only when the LoS is present since blockage of mmWave leads to poor performance, in case of blockage the vehicle selection will be 4G LTE.\u003c/p\u003e\u003ctable-wrap id=\"j_ijssis-2021-012_tab_001\" position=\"float\"\u003e\u003clabel\u003eTable 1.\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eFuzzy rules.\u003c/p\u003e\u003c/caption\u003e\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"/\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"5\"\u003eInput\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"/\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eRule number\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e\u003citalic\u003eS\u003c/italic\u003e\u003csub\u003e\u003citalic\u003er\u003c/italic\u003e\u003c/sub\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eDistance\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e\u003citalic\u003eV\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eD\u003c/italic\u003e\u003c/sub\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eData type\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eLoS\u003c/th\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eOutput\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR1\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR2\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR3\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR4\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR5\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR6\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR7\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR8\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR9\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR10\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR11\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR12\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR13\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR14\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR15\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR16\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR17\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR18\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR19\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR20\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR21\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR22\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR23\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR24\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR25\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR26\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR27\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR28\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR29\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR30\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eM\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR31\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eH\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eR32\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eL\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/table-wrap\u003e\u003cp\u003eThe fuzzy logic method operates with the IF-THEN rules in the interference engine. The input is in crisp values that are converted into a fuzzy set. As per the fuzzy rule, the interference engine constructs membership function between [0,1]. The fuzzy logic operations are built into CNN. \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_004\"\u003eFigure 4\u003c/a\u003e depicts the constructed fuzzy logic with CNN. The output high (H), medium (M), and low (L) denotes as follows:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_006\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_006.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eH\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmi\u003eM\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e→\u003c/mo\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi mathvariant=\"normal\"\u003emmWave\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi mathvariant=\"normal\"\u003eLTE\u003c/mi\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi mathvariant=\"normal\"\u003eDSRC\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_004\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 4:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eFuzzy-convolutional neural network.\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_004.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_004.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=dd1de1b23b1402cf8df6d99161a6253bb07b75b28cde35656d232b19feac4e8f\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eA pseudo-code below is illustrated based on the workflow of this fuzzy-CNN algorithm:\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_unfig_002\" fig-type=\"figure\"\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_unfig_002.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_unfig_002.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=29c2f59577776976b5bd1faa22634c6ad37cf80d7160d34fb96213f414613d7d\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eThe use of CNN will give results for multiple vehicles at the same time by parallel processing. The proposed fuzzy-CNN is composed of 32 rules, which are defined from five parameters. Since the CNN can process in parallel, the 32 rules will be processed in the convolution layer. According to the selected network, the requested vehicle will handover from the current network to the target network.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_004_s_004\"\u003e\u003cdiv\u003eOptimized routing using jelly fish optimization algorithm\u003c/div\u003e\u003cp\u003eThe process of routing is carried out using jellyfish optimization algorithm where the vehicles are formed like V2V pairs, hence the name V2V chain routing. The routes are selected by computing the objective function using channel metrics (SNR (\u003citalic\u003es\u003c/italic\u003e\u003csub\u003e\u003citalic\u003er\u003c/italic\u003e\u003c/sub\u003e), link quality (\u003citalic\u003el\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eq\u003c/italic\u003e\u003c/sub\u003e)), vehicle metrics (Speed (\u003citalic\u003es\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ep\u003c/italic\u003e\u003c/sub\u003e), Relative direction (\u003citalic\u003eR\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ed\u003c/italic\u003e\u003c/sub\u003e)), and vehicle performance metrics (Delay (\u003citalic\u003eD\u003c/italic\u003e\u003csub\u003e\u003citalic\u003el\u003c/italic\u003e\u003c/sub\u003e), throughput (\u003citalic\u003eT\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ep\u003c/italic\u003e\u003c/sub\u003e)).\u003c/p\u003e\u003cp\u003eA time control mechanism is used to switch between active or passive movements in this algorithm. The time control \u003citalic\u003ec\u003c/italic\u003e(\u003citalic\u003et\u003c/italic\u003e) is formulated and computed using the following equations:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_007\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_007.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(6)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi\u003ec\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmi\u003et\u003c/mi\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmo\u003e|\u003c/mo\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003cmo\u003e‒\u003c/mo\u003e\u003cmfrac\u003e\u003cmi\u003et\u003c/mi\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi mathvariant=\"normal\"\u003eMax\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ei\u003c/mi\u003e\u003cmi\u003et\u003c/mi\u003e\u003cmi\u003ee\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e×\u003c/mo\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003cmo\u003e×\u003c/mo\u003e\u003cmi mathvariant=\"normal\"\u003erand\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmn\u003e0\u003c/mn\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e‒\u003c/mo\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e|\u003c/mo\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003ewhen rand(0,1) \u0026gt; (1‒\u003citalic\u003ec\u003c/italic\u003e(\u003citalic\u003et\u003c/italic\u003e)), then passive motion:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_008\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_008.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(7)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi mathvariant=\"normal\"\u003erand\u003c/mi\u003e\u003cmspace width=\".25em\"/\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmn\u003e0\u003c/mn\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e\u0026lt;\u003c/mo\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003cmo\u003e‒\u003c/mo\u003e\u003cmi\u003ec\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmi\u003et\u003c/mi\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi mathvariant=\"normal\"\u003ethen\u003c/mi\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi mathvariant=\"normal\"\u003eactive\u003c/mi\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi mathvariant=\"normal\"\u003emotion\u003c/mi\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eHere the jellyfish are assumed as vehicles and the ocean is assumed as road lane where the vehicle moves in different speed.\u003c/p\u003e\u003cp\u003eThe ocean current direction represented as \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_008.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmover accent=\"true\"\u003e\u003cmrow\u003e\u003cmi\u003eO\u003c/mi\u003e\u003cmi\u003eC\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"true\"\u003e→\u003c/mo\u003e\u003c/mrow\u003e\u003c/mover\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e and it is mathematically given as below:\u003c/p\u003e\u003cp\u003eLet:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_009\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_009.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(8)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmover accent=\"true\"\u003e\u003cmrow\u003e\u003cmi\u003eO\u003c/mi\u003e\u003cmi\u003eC\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"true\"\u003e→\u003c/mo\u003e\u003c/mrow\u003e\u003c/mover\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmn\u003e1\u003c/mn\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eV\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ep\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmi\u003eX\u003c/mi\u003e\u003c/mrow\u003e\u003cmo\u003e*\u003c/mo\u003e\u003c/msup\u003e\u003cmo\u003e‒\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ee\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ec\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmi\u003eμ\u003c/mi\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eThen:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_010\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_010.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(9)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmover accent=\"true\"\u003e\u003cmrow\u003e\u003cmi\u003eO\u003c/mi\u003e\u003cmi\u003eC\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"true\"\u003e→\u003c/mo\u003e\u003c/mrow\u003e\u003c/mover\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmi\u003eX\u003c/mi\u003e\u003c/mrow\u003e\u003cmo\u003e*\u003c/mo\u003e\u003c/msup\u003e\u003cmo\u003e‒\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ed\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ef\u003c/mi\u003e\u003cmi\u003ef\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e(9)where ‘\u003citalic\u003eV\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ep\u003c/italic\u003e\u003c/sub\u003e’ is the vehicle density. \u003citalic\u003eX\u003c/italic\u003e\u003csup\u003e*\u003c/sup\u003e denotes the best location, \u003citalic\u003eμ\u003c/italic\u003e is the mean location, and \u003citalic\u003ee\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ec\u003c/italic\u003e\u003c/sub\u003e is the attraction factor, here the attraction of on destination. Then, the objective function is defined to select a best route. This function OF is formulated as follows:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_011\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_011.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(10)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi mathvariant=\"normal\"\u003eOF\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003eM\u003c/mi\u003e\u003cmi\u003es\u003c/mi\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmo\u003e∑\u003c/mo\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003es\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003er\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eq\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003es\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ep\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ed\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eD\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eT\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ep\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003e\u003citalic\u003eMs\u003c/italic\u003e represents a set of parameters in which the delay and speed must be minimum and all the other parameters can be a maximum value for the selection of the routes. Here the OF is applied for the complete route, since this work selects an optimal route from the available routes. The metrics are estimated from the channel:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_012\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_012.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(11)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eq\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmn\u003e1\u003c/mn\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ef\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e×\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003er\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e(11)\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_013\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_013.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(12)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ed\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmn\u003e2\u003c/mn\u003e\u003cmi\u003er\u003c/mi\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi\u003esin\u003c/mi\u003e\u003cmspace width=\".25em\"/\u003e\u003cmsqrt\u003e\u003cmrow\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmi\u003esin\u003c/mi\u003e\u003c/mrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/msup\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eΔ\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003cmi\u003ea\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/mfrac\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003c/msqrt\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi\u003ecos\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ea\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ev\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e×\u003c/mo\u003e\u003cmspace width=\".25em\"/\u003e\u003cmi\u003ecos\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ea\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003en\u003c/mi\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003ep\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003ei\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003cmo\u003e×\u003c/mo\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmi\u003esin\u003c/mi\u003e\u003c/mrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/msup\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eΔ\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eln\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/mfrac\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e(12)\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_014\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_014.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(13)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eD\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003el\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmi\u003eb\u003c/mi\u003e\u003c/mfrac\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e(13)where \u003citalic\u003eP\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ef\u003c/italic\u003e\u003c/sub\u003e\u003citalic\u003eP\u003c/italic\u003e\u003csub\u003e\u003citalic\u003er\u003c/italic\u003e\u003c/sub\u003e represents the number of transmitted and the received packets in the same link between two vehicles, (\u003citalic\u003ela\u003c/italic\u003e,\u003citalic\u003eln\u003c/italic\u003e) represents the latitude and longitude, (\u003citalic\u003ela\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ev\u003c/italic\u003e\u003c/sub\u003e,\u003citalic\u003eln\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ev\u003c/italic\u003e\u003c/sub\u003e) represents the vehicle location, and (\u003citalic\u003ela\u003c/italic\u003e\u003csub\u003e\u003citalic\u003enp\u003c/italic\u003e\u003c/sub\u003e, \u003citalic\u003eln\u003c/italic\u003e\u003csub\u003e\u003citalic\u003enp\u003c/italic\u003e\u003c/sub\u003e) represents the next hop location and r is the radius. \u003citalic\u003eP\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eL\u003c/italic\u003e\u003c/sub\u003e, \u003citalic\u003eb\u003c/italic\u003e represents packet length and bit rate, i.e. transmission speed in bits per second that are used to compute the delay estimation.\u003c/p\u003e\u003cp\u003e\u003ca ref-type=\"disp-formula\" href=\"#j_ijssis-2021-012_eq_011\"\u003eEquation 10\u003c/a\u003e defines the objective function through which the optimal route is selected using jellyfish optimization algorithm.\u003c/p\u003e\u003cp\u003eThe performance of the proposed HO, network selection, and routing algorithms are evaluated in the next section.\u003c/p\u003e\u003c/sec\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_005\"\u003e\u003cdiv\u003eSimulation results\u003c/div\u003e\u003cp\u003eThe section is split into three parts as simulation setup and specifications, comparative analysis, and result discussion. The simulation details and the parameters are discussed in detail in this section.\u003c/p\u003e\u003csec id=\"j_ijssis-2021-012_s_005_s_001\"\u003e\u003cdiv\u003eSimulation setup and specifications\u003c/div\u003e\u003cp\u003eThe proposed work is simulated using OMNeT++. \u003ca ref-type=\"table\" href=\"#j_ijssis-2021-012_tab_002\"\u003eTable 2\u003c/a\u003e shows the simulation parameters assumed in our proposed work.\u003c/p\u003e\u003ctable-wrap id=\"j_ijssis-2021-012_tab_002\" position=\"float\"\u003e\u003clabel\u003eTable 2.\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eSimulation specifications.\u003c/p\u003e\u003c/caption\u003e\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eParameter\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eRange/Value\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eSimulation area\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2,500 m × 2,500 m\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eNumber of vehicles\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e100\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eNumber of 5G mmWave BSs\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eNumber of 4G LTE BSs\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eVehicle mobility type\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eLinear mobility\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eVehicle speed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e10-40 m/s\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"2\"\u003eTransmission range\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e DSRC\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e300 m (Max)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e mmWave\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e~500 m\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003e LTE\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e100 km (Max)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTransmission rate\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e3-5 packets per second\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003ePacket size\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e512 bytes\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eSimulation time\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e1,000 sec\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/table-wrap\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_005_s_002\"\u003e\u003cdiv\u003eComparative results\u003c/div\u003e\u003cp\u003eThe comparative analysis gives the obtained results in comparative graphs. The proposed work is compared with previous works that use conventional RSS-based selection, TOPSIS, ANDSF, and V2I-MoloHA methods relating to handover, network selection, and routing issues. It is a multi-criteria decision-making algorithm that processes with more than one criterion. The parameters that are considered for the evaluation are mean handover, handover failure, throughput, and delay.\u003c/p\u003e\u003csec id=\"j_ijssis-2021-012_s_005_s_002_s_001\"\u003e\u003cdiv\u003eMean handover and handover failure\u003c/div\u003e\u003cp\u003eThe mean handover is the number of successful handovers of a vehicle from one network to another. Handover failure is defined as the number of unsuccessful handovers that happen due to poor decision-making.\u003c/p\u003e\u003cp\u003eThe lesser mean handover denotes the better performance of the proposed algorithm as it has minimized the number of unnecessary handovers in the network. In previous work of TOPSIS, it was used for the selection of network that fails to perform proper ranking. Similarly, the use of parameters for the selection of network was either based on vehicle characteristic or environmental characteristic which leads to select the best target network that eventually increases mean handover along with the increase in the handover failure.\u003c/p\u003e\u003cp\u003eThe proposed dynamic Q-learning algorithm can learn the vehicle environment in a particular surrounding. The prediction of handover requirement from the vehicle speed and signal strength is efficient. Further to the prediction, we perform a selection of networks using the F-CNN algorithm for selecting a network by analyzing the metrics of the particular vehicle. The process of prediction and network selection in this work tends to improve the performance of the handover-based metrics.\u003c/p\u003e\u003cp\u003e\u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_005\"\u003eFigures 5\u003c/a\u003e and \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_006\"\u003e6\u003c/a\u003e illustrate the mean handover and handover failure concerning the increase in vehicle speed. The improvement in the performances of HO failure rate and mean handover is due to the handover decisions made by dynamic Q-learning algorithm and appropriate selection of networks due to fuzzy-CNN. The mean handover in the proposed work decreases with the increase in vehicle speed and hence, suitable for large-scale environments. Besides, the decrease in mean handover reduces the HO failure counts. In general with the increase in vehicle speed, the handover failure occurs but as the proposed work uses Q-learning for predicting the requirement of handover before that of the network selection it can take an absolute decision at the increase of vehicle speed. The main reasons behind the degradation of handover are illustrated below.\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_005\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 5:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eComparison of mean handover (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e; \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_012\"\u003eSheng et al., 2018\u003c/a\u003e).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_005.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_005.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=3e5c8fda9455086f35cf5bdb7f32631a948797d41c755dfa6c51e5edcab42ac5\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_006\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 6:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eComparison of HO failure (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e; \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_012\"\u003eSheng et al., 2018\u003c/a\u003e).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_006.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_006.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=055e08cf21dda6ba730cf94a1888636b00b7aa3af0e07ae95f1a9e1562f5ca00\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eSelection of parameters to select the suitable network which requires considering vehicle metrics as well as the BS metrics:\u003clist id=\"j_ijssis-2021-012_list4\" list-type=\"bullet\"\u003e\u003clist-item\u003e\u003cp\u003eThe number of handovers increases due to the absence of prediction of the vehicle regarding the need for handover. This leads to an increase the number of unnecessary handovers which also requires large resource blocks for performing the computations.\u003c/p\u003e\u003c/list-item\u003e\u003c/list\u003e\u003c/p\u003e\u003cp\u003eThe handover failure rate HO\u003csub\u003e\u003citalic\u003eFR\u003c/italic\u003e\u003c/sub\u003e is computed mathematically based on the below equation:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_015\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_015.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(14)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi mathvariant=\"normal\"\u003eHO\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eF\u003c/mi\u003e\u003cmi\u003eR\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi mathvariant=\"normal\"\u003eHO\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eF\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi mathvariant=\"normal\"\u003eHO\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eS\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi mathvariant=\"normal\"\u003eHO\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eF\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eThe terms\u003citalic\u003eHO\u003csub\u003eF\u003c/sub\u003e\u003c/italic\u003e and \u003citalic\u003eHO\u003csub\u003eS\u003c/sub\u003e\u003c/italic\u003e represents the number of handover failure and handover success, respectively. According to the count of these measurements, the handover failure rate is determined. The handover failure is caused because of the poor handover decision; hereby the proposed work first predicts the handover requirement from the vehicle request by learning the environment and then if the decision is to perform handover, it selects a target network. From the comparative graph, the average value of failure rate in proposed is 0.015, while the previous work achieves 0.13, 0.04, 0.07, and 0.03 in conventional, TOPSIS, ANDSF-HO, and V2I-MoLoHA, respectively. The minimization of handover failure reflects on absolute handover decision. Similarly, the reduction in the number of handover shows that the unnecessary handover is reduced by efficient prediction and network selection in proposed.\u003c/p\u003e\u003cp\u003e\u003ca ref-type=\"table\" href=\"#j_ijssis-2021-012_tab_003\"\u003eTable 3\u003c/a\u003e gives a comparison on the average values estimated from the performance of conventional method, TOPSIS, ANDSF-HO, and V2I-MoLoHA in terms of number of handover and handover failure. Then the improvement percentage of handover efficiency is depicted in the above table. The handover efficiency impact on other network parameters that enhances overall network efficiency.\u003c/p\u003e\u003ctable-wrap id=\"j_ijssis-2021-012_tab_003\" position=\"float\"\u003e\u003clabel\u003eTable 3.\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eComparison of HO efficiency.\u003c/p\u003e\u003c/caption\u003e\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eMethod\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eAverage number of HO\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eAverage HO\u003csub\u003e\u003citalic\u003eFR\u003c/italic\u003e\u003c/sub\u003e\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eConventional\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e5.51\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e55%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.133\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e90%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTOPSIS\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e2.15\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e20%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.041\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e40%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eANDSF-HO\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e3.57\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e30%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.069\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e60%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eV2I-MoLoHA\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e3.03\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e25%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.029\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e20%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eProposed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e1.30\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e0.01\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/table-wrap\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_005_s_002_s_002\"\u003e\u003cdiv\u003eThroughput, delay and packet loss\u003c/div\u003e\u003cp\u003eThroughput is one of the significant performances metric in a network and it is mathematically computed using the formula as follows:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_016\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_016.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(15)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi\u003eT\u003c/mi\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003es\u003c/mi\u003e\u003cmi\u003ez\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003et\u003c/mi\u003e\u003cmi\u003et\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003cmo\u003e×\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmn\u003e1.2\u003c/mn\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eP\u003c/mi\u003e\u003cmsup\u003e\u003cmrow\u003e\u003cmi\u003eL\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e0.5\u003c/mn\u003e\u003c/mrow\u003e\u003c/msup\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cp\u003eThe throughput \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_009.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eT\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e is estimated from the packet size \u003citalic\u003eP\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eSZ\u003c/italic\u003e\u003c/sub\u003e, round trip time \u003citalic\u003eR\u003c/italic\u003e\u003csub\u003e\u003citalic\u003ett\u003c/italic\u003e\u003c/sub\u003e and packet loss \u003citalic\u003ePL\u003c/italic\u003e.\u003c/p\u003e\u003cp\u003e\u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_007\"\u003eFigures 7\u003c/a\u003e and \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_008\"\u003e8\u003c/a\u003e show the graphs for throughput, and delay. From \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_007\"\u003eFigures 7\u003c/a\u003e and \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_008\"\u003e8\u003c/a\u003e, there is an increase in the throughput and decrease in delay when compared to the existing techniques. This is due to the optimal selection of routes using jellyfish optimization algorithm. The graph shows little increase, and drops in the delay. The end-to-end delay is determined in terms of transmission delay between the relay vehicles from the source vehicle to the destination vehicle. The end-to-end delay (\u003citalic\u003eEE\u003c/italic\u003e\u003csub\u003e\u003citalic\u003eD\u003c/italic\u003e\u003c/sub\u003e) is determined as follows:\n\u003cdisp-formula id=\"j_ijssis-2021-012_eq_017\"\u003e\u003clabel\u003e()\u003c/label\u003e\u003calternatives\u003e\u003cgraphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_eq_017.png\"\u003e\u003c/graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"block\"\u003e\u003cmtable\u003e\u003cmlabeledtr\u003e\u003cmtd\u003e\u003cmtext\u003e(16)\u003c/mtext\u003e\u003c/mtd\u003e\u003cmtd\u003e\u003cmi\u003eE\u003c/mi\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eE\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eD\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e=\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003cmi\u003eb\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e0\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e0\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003cmi\u003eb\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e1\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmn\u003e2\u003c/mn\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmo\u003e⋯\u003c/mo\u003e\u003cmi\u003e…\u003c/mi\u003e\u003cmo\u003e+\u003c/mo\u003e\u003cmfrac\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003cmi\u003eb\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003en\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003em\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003eR\u003c/mi\u003e\u003cmrow\u003e\u003cmo stretchy=\"false\"\u003e(\u003c/mo\u003e\u003cmrow\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003en\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003cmo\u003e,\u003c/mo\u003e\u003cmsub\u003e\u003cmrow\u003e\u003cmi\u003eN\u003c/mi\u003e\u003c/mrow\u003e\u003cmrow\u003e\u003cmi\u003em\u003c/mi\u003e\u003c/mrow\u003e\u003c/msub\u003e\u003c/mrow\u003e\u003cmo stretchy=\"false\"\u003e)\u003c/mo\u003e\u003c/mrow\u003e\u003c/mrow\u003e\u003c/mfrac\u003e\u003c/mtd\u003e\u003c/mlabeledtr\u003e\u003c/mtable\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/disp-formula\u003e\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_007\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 7:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eComparison of throughput (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e; \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_012\"\u003eSheng et al., 2018\u003c/a\u003e).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_007.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_007.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=08567be3e13fa07225c15570ac6a28b13ce573313174e97d12ce9706261c0e82\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_008\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 8:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eComparison of end-to-end delay (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e; \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_012\"\u003eSheng et al., 2018\u003c/a\u003e).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_008.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_008.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=37df6a93aea33af2bafc280bfc1445624f78c5b86ce281b1b78ed6da7020ee3a\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003cp\u003eLet the vehicles in a route be represented as \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e0\u003c/sub\u003e, \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e1\u003c/sub\u003e, \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e2, \u003c/sub\u003e…, \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e\u003citalic\u003en\u003c/italic\u003e\u003c/sub\u003e, \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e\u003citalic\u003em\u003c/italic\u003e\u003c/sub\u003e for which the number of bits in each node is denoted as \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_010.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi mathvariant=\"italic\"\u003eNb\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e and the rate of transmission is \u003citalic\u003eR\u003c/italic\u003e. The \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e0\u003c/sub\u003e is the source vehicle node, \u003citalic\u003eN\u003c/italic\u003e\u003csub\u003e\u003citalic\u003em\u003c/italic\u003e\u003c/sub\u003e is the destination vehicle node, while the nodes are the relay. In accordance to the estimation of the delay a better efficiency in the route selection is analyzed. In a route, the delay occur between every pair of vehicle due to the use of signal strength and hence the delay is predicted for each pair and end-to-end delay from the source to destination is determined.\u003c/p\u003e\u003cp\u003eThe comparative results depict that proposed work is better than the previous conventional method, TOPSIS, ANDSF-HO, and V2I-MoLoHA. Among all the previous work, the conventional method of using only signal strength results in poor performance due to the growth of multiple challenges in data transmission of vehicles. \u003ca ref-type=\"table\" href=\"#j_ijssis-2021-012_tab_004\"\u003eTable 4\u003c/a\u003e illustrates the mean value determined for each work in the performance of throughput and delay. Based on the mean throughput and delay, the percentage of improvement is proposed than the existing works. As per the comparison, a minimum of 23% and a maximum of 46% is better performance than the previous methods in this network (\u003ca ref-type=\"table\" href=\"#j_ijssis-2021-012_tab_005\"\u003eTable 5\u003c/a\u003e).\u003c/p\u003e\u003ctable-wrap id=\"j_ijssis-2021-012_tab_004\" position=\"float\"\u003e\u003clabel\u003eTable 4.\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eComparison of throughput and delay.\u003c/p\u003e\u003c/caption\u003e\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eMethod\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eMean \u003cinline-formula\u003e\u003calternatives\u003e\u003cinline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_ieq_011.png\"\u003e\u003c/inline-graphic\u003e\u003cmath xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" display=\"inline\"\u003e\u003cmi\u003eT\u003c/mi\u003e\u003c/math\u003e\u003ctex-math/\u003e\u003c/alternatives\u003e\u003c/inline-formula\u003e (kbps)\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eAverage delay (ms)\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eConventional\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e13.7\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e46%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e39\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e21%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTOPSIS\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e35.96\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e23%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e30\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e12%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eANDSF-HO\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e25\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e34%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e37\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e19%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eV2I-MoLoHA\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e31.89\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e27%\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e34\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e16%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eProposed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e58.89\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e18\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/table-wrap\u003e\u003ctable-wrap id=\"j_ijssis-2021-012_tab_005\" position=\"float\"\u003e\u003clabel\u003eTable 5.\u003c/label\u003e\u003ccaption\u003e\u003cp\u003eComparison of packet loss.\u003c/p\u003e\u003c/caption\u003e\u003ctable frame=\"hsides\"\u003e\u003ccolgroup span=\"1\"\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003ccol align=\"left\" width=\"1*\" span=\"1\"/\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eMethod\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003ePacket loss (%)\u003c/th\u003e\u003cth align=\"center\" rowspan=\"1\" colspan=\"1\"\u003eBetter efficiency\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eConventional\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e48\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e21%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eTOPSIS\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e32.4\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e12%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eANDSF-HO\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e24\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e19%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eV2I-MoLoHA\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e18.8\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e16%\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" rowspan=\"1\" colspan=\"1\"\u003eProposed\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e12\u003c/td\u003e\u003ctd align=\"center\" rowspan=\"1\" colspan=\"1\"\u003e–\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/table-wrap\u003e\u003cp\u003eOne of the major reasons for the increase in packet losses is due to the link degradation problems which occur mainly due to high vehicle density, poor signal quality. In our work, we have proposed a jellyfish optimization algorithm for the selection of routes taking into account vehicle metrics, channel metrics, and transmission metrics. \u003ca ref-type=\"fig\" href=\"#j_ijssis-2021-012_fig_009\"\u003eFigure 9\u003c/a\u003e shows the graphical plots where there is a decrease in the packet loss concerning the vehicle density due to consideration of multiple metrics for selecting the shortest path. From the figure, when there is an increase in the vehicle density, there are possibilities of an increase in data transmission due to which the packet loss can increase. However, in our work, the packet losses are minimized due to the selection of optimized routes. The previous works of TOPSIS, ANDSF-HO, and V2I-MoLoHA fails to select the best route among the available route between source and destination. Therefore, the deployment of an algorithm for selecting the best route minimizes packet loss. Even the vehicle density increases there is a reduction in packet loss since not all vehicles will use the route for transmission. That is to say, the vehicles nearby will not require data transmission. Due to this reason, the packet loss in the proposed work does not increase suddenly with the increase in the number of vehicles.\u003c/p\u003e\u003cfigure id=\"j_ijssis-2021-012_fig_009\" fig-type=\"figure\"\u003e\u003ch2\u003eFigure 9:\u003c/h2\u003e\u003cfigCaption\u003e\u003cp\u003eComparison on packet loss (\u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_010\"\u003eNdashimye et al., 2020\u003c/a\u003e; \u003ca ref-type=\"bibr\" href=\"#j_ijssis-2021-012_ref_012\"\u003eSheng et al., 2018\u003c/a\u003e).\u003c/p\u003e\u003c/figCaption\u003e\u003cimg xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"graphic/j_ijssis-2021-012_fig_009.jpg\" src=\"https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/62242a2c0d198124537c32f6/j_ijssis-2021-012_fig_009.jpg?X-Amz-Algorithm=AWS4-HMAC-SHA256\u0026amp;X-Amz-Date=20230203T065859Z\u0026amp;X-Amz-SignedHeaders=host\u0026amp;X-Amz-Expires=18000\u0026amp;X-Amz-Credential=AKIA6AP2G7AKP25APDM2%2F20230203%2Feu-central-1%2Fs3%2Faws4_request\u0026amp;X-Amz-Signature=1439d9dead49c156ab3acbc1c1230896fd05f7a75067574d0981beee475cfea4\" class=\"mw-100\"\u003e\u003c/img\u003e\u003c/figure\u003e\u003c/sec\u003e\u003c/sec\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_006\"\u003e\u003cdiv\u003eResult discussion\u003c/div\u003e\u003cp\u003eIn this section, the obtained results are discussed concerning the evaluation metrics used in this work. The handover-based metrics and data transmission-based metrics are discussed.\u003c/p\u003e\u003cp\u003eFirst, number of handover and handover failure: handover is the process of changing the RAN connectivity from one network to another. In general, 5G is a heterogeneous network that has support for all short-range and long-range data transmissions. Due to the presence of a variety of RAN, the process of network selection is significant in the 5G environment. On the other hand, the vehicles move at a different speeds, so the concept of handover is incorporated. This work proposes handover prediction and selection of networks, which was not performed in previous work.\u003c/p\u003e\u003cp\u003eIn the existing study of the TOPSIS algorithm, ANDSF, and V2I-MoLoHA methods, the network was selected from the computation of one or more metrics once it receives the request from the vehicle. While in the proposed work, on receiving a vehicle request, it predicts the requirement of handover, and then it selects a network only if needed. The prediction process using dynamic Q-learning leads to minimizing unnecessary handover and then F-CNN leads to improve optimal network selection. Hereby 45 to 50% of the performance of handover is improved than the existing algorithms.\u003c/p\u003e\u003cp\u003eSecond, throughput and delay: throughput and end-to-end delay are the important parameters that are used to measure the performance of the proposed work with the previous algorithms. The selection of routes using an optimization algorithm with vehicle metrics can identify an optimal route. As a result, 40 to 45% of the throughput is improved than the previous methods. The improvement in throughput will also impact other network parameters. Then the end-to-end delay is 10 to 15% improved than the previous algorithms.\u003c/p\u003e\u003cp\u003eThe proposed algorithms for handover decision, network selection, and routing have a major impact on the performances of the network. This work takes into account the most essential metrics for making a decision and network selection. As a result, the proposed work achieves better performance when compared with previous work of handover.\u003c/p\u003e\u003c/sec\u003e\u003csec id=\"j_ijssis-2021-012_s_007\"\u003e\u003cdiv\u003eConclusion\u003c/div\u003e\u003cp\u003eWe have proposed three algorithms for making handover, network selection, and routing in the IoV environment due to the presence of multiple radio access networks. The data transmission requirement depends on each data type. Dynamic Q-learning algorithm is used for making handovers by computing the dynamic thresholds using Shannon entropy rule, and also determines the need for handover. It is clear from the results that using the dynamic Q-learning algorithm, there is a reduction in unnecessary handovers. Appropriate selection of network is achieved using fuzzy-CNN that processes multiple requests simultaneously and enables to considerate multiple parameters to select the network. Besides, a routing algorithm is proposed that forms V2V pairs and selects the best route using a jellyfish optimization algorithm to reduce end-to-end delay, and packet losses. The objective function is defined using vehicle metrics, channel metrics, and performance metrics. The simulation results have shown the superiority of the proposed work considering mean HO, HO failure rate, throughput, delay, and packet loss as the evaluation metrics. The evaluation of switching delays between multiple RAT is the future scope of our work.\u003c/p\u003e\u003c/sec\u003e\u003c/div\u003e","keywords":[{"title":"Keywords","language":null,"keywords":["4G LTE","DSRC","Internet of Vehicles","mmwave 5G","Network selection","Vertical handover"]}],"recentIssues":{"10.2478/ijssis-2022-0008":"\u003carticle-title\u003eEigen-structure problem optimization for multirate, multi-input multi-output systems applied to a roll rate autopilot\u003c/article-title\u003e","10.2478/ijssis-2022-0009":"\u003carticle-title\u003eThe ordinary negative changing refractive index for estimation of optical confinement factor\u003c/article-title\u003e","10.2478/ijssis-2022-0006":"\u003carticle-title\u003eModel based on the principles of smart agriculture to mitigate the effects of frost and improve agricultural production in the Cundiboyacense plateau\u003c/article-title\u003e","10.2478/ijssis-2022-0007":"\u003carticle-title\u003eEfficient way to ensure the data 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\u003c1\u003econtact our representative\u003c/1\u003e for your territory to meet and discuss the terms of the White Label Publishing House offer.","whiteLabelContent.first":"Sciendo has a special offer for universities and other organizations that are seeking a partner to publish all or some of their English, German, French, Spanish, Italian and Polish languages journals, books and other publications. This applies to new publications and to previously published books and back journal volumes. We publish monographs, textbooks, edited volumes, and other categories.","whiteLabelContent.fourth":"The university can decide which package of services applies to each journal and book. Such packages are described in the pages for \u003c1\u003ejournals\u003c/1\u003e and \u003c3\u003ebooks\u003c/3\u003e. \u003c5\u003eIf the value of the contract exceeds an agreed amount, the university can enjoy discounts up to 60% on standard fees.\u003c/5\u003e","whiteLabelContent.second":"The university can decide if a given journal or book is published using the Open Access or paid access model. All books and journal articles bear both the university and the Sciendo logos.","whiteLabelContent.third":"At no cost to the university, Sciendo will design, produce and manage the website of this publishing house. The role of the university is to select and channel books and book proposals for this publishing co-operation, as well as to promote this publishing opportunity to its faculty.","conferenceServices.first":"If you would like to learn more about these services, please contact Sales \u0026 Publishing Specialist — Services for conference organizers: \u003c1\u003ealexandru.vlad@sciendo.com\u003c/1\u003e or call directly \u003c3\u003e+44 2086388130\u003c/3\u003e.","conferenceServices.second":"Sciendo is the only company in the world that meets the two most important needs of an academic conference organizer. As well as publishing conference proceedings, we can also provide the organizer with one of the world's best event management systems. We have partnered with Cvent and Converia.","conferenceServices.third":"We can publish your conference proceedings and optionally provide you with the event management systems. We publish conference proceedings online using theOpen Access model. Printed copies can be bought online. We currently publish proceedings in English language only.","conferenceServices.fourth":"The services and solutions that we offer for conference proceedings are bundled into three packages: \u003c1\u003eStandard\u003c/1\u003e, \u003c3\u003eClassic\u003c/3\u003e and \u003c5\u003ePremier\u003c/5\u003e. We charge for each paper published and the charge depends on the package and any additional services and solutions you choose.","conferenceServices.fifth":"The diagram shows the key components of each package.","conferenceServices.sixth":"Sciendo would be delighted to publish your conference proceedings and provide event management systems for your conference. Please refer to the services shown in the chart above and \u003c1\u003edownload the brochure\u003c/1\u003e for more information.","fullPublishingContent.first":"Sciendo publishes books from universities, research institutes, academies of sciences, learned societies and other organizations. We offer both the Open Access and traditional (paid access) models. The following rules also apply to individual authors whose institutions are willing to pay the publishing fees for the publication of their books.","fullPublishingContent.second":"\u003c0\u003eWe have a special offer for universities and other organizations to publish all or some of their English language journals, books and other publications. \u003c1\u003eSee more here.\u003c/1\u003e\u003c/0\u003e","fullPublishingContent.third":"The services and solutions that we offer are bundled into three packages: Standard, Classic and Premier. These packages range from standard components required for publication to a full-service package and a hybrid between “basic” and “full-service”. We charge for each book published, the charge is dependent on the package and any additional services and solutions are chosen.","fullPublishingContent.fourth":"The table shows the key components of each package. Sciendo would be delighted to offer the services shown in the chart below to books whose publication is financed by institutions.","fullPublishingContent.fifth":"Institutions and authorsinterested in learning more about the services and relevant charges should \u003c1\u003econtact our representative\u003c/1\u003e for their territory, to meet and discuss the terms.","journals.first":"Sciendo publishes academic journals that belong to universities, research institutes, academies of sciences, learned societies and other organizations. We can publish them both in the Open Access and in traditional ( paid access) models. 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