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Performance evaluation of vertical handover in Internet of Vehicles

Shaik Mazhar Hussain

Shaik Mazhar Hussain

  • Department of Communications and Advanced Telecommunication Technology, Universiti Teknologi Malaysia (UTM)Johor Bahru, Malaysia
  • School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi MalaysiaJohor Bahru, Malaysia
  • Middle East CollegeMuscat, Oman
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Hussain, Shaik Mazhar
, 
Kamaludin Mohamad Yusof

Kamaludin Mohamad Yusof

  • Department of Communications and Advanced Telecommunication Technology, Universiti Teknologi Malaysia (UTM)Johor Bahru, Malaysia
  • School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi MalaysiaJohor Bahru, Malaysia
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Yusof, Kamaludin Mohamad
, 
Shaik Ashfaq Hussain

Shaik Ashfaq Hussain

  • Department of Communications and Advanced Telecommunication Technology, Universiti Teknologi Malaysia (UTM)Johor Bahru, Malaysia
  • School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi MalaysiaJohor Bahru, Malaysia
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Hussain, Shaik Ashfaq
 e 
Rolito Asuncion

Rolito Asuncion

Middle East CollegeMuscat, Oman
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Asuncion, Rolito
  
28 giu 2021
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Pubblicato online: 28 giu 2021
Pagine: 1 - 16
Ricevuto: 16 gen 2021
DOI: https://doi.org/10.21307/ijssis-2021-012
Parole chiave
© 2021 Shaik Mazhar Hussain et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

Workflow procedure of ANDSF (Ndashimye et al., 2020).
Workflow procedure of ANDSF (Ndashimye et al., 2020).

Figure 2:

Proposed system model.
Proposed system model.

Figure 3:

Workflow of dynamic Q-learning.
Workflow of dynamic Q-learning.
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Figure 4:

Fuzzy-convolutional neural network.
Fuzzy-convolutional neural network.
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Figure 5:

Comparison of mean handover (Ndashimye et al., 2020; Sheng et al., 2018).
Comparison of mean handover (Ndashimye et al., 2020; Sheng et al., 2018).

Figure 6:

Comparison of HO failure (Ndashimye et al., 2020; Sheng et al., 2018).
Comparison of HO failure (Ndashimye et al., 2020; Sheng et al., 2018).

Figure 7:

Comparison of throughput (Ndashimye et al., 2020; Sheng et al., 2018).
Comparison of throughput (Ndashimye et al., 2020; Sheng et al., 2018).

Figure 8:

Comparison of end-to-end delay (Ndashimye et al., 2020; Sheng et al., 2018).
Comparison of end-to-end delay (Ndashimye et al., 2020; Sheng et al., 2018).

Figure 9:

Comparison on packet loss (Ndashimye et al., 2020; Sheng et al., 2018).
Comparison on packet loss (Ndashimye et al., 2020; Sheng et al., 2018).

Comparison of HO efficiency_

MethodAverage number of HOBetter efficiencyAverage HOFRBetter efficiency
Conventional5.5155%0.13390%
TOPSIS2.1520%0.04140%
ANDSF-HO3.5730%0.06960%
V2I-MoLoHA3.0325%0.02920%
Proposed1.30–0.01–

Fuzzy rules_

Input
Rule numberSrDistanceVDData typeLoSOutput
R1HHHHHH
R2HHHHLH
R3HHHLHM
R4HHHLLM
R5HHLHHH
R6HHLHLM
R7HHLLHL
R8HHLLLM
R9HLHHHH
R10HLHHLL
R11HLHLHL
R12HLHLLL
R13HLLHHH
R14HLLHLM
R15HLLLHL
R16HLLLLM
R17LHHHHH
R18LHHHLL
R19LHHLHH
R20LHHLLM
R21LHLHHH
R22LHLHLH
R23LHLLHL
R24LHLLLL
R25LLHHHH
R26LLHHLM
R27LLHLHL
R28LLHLLL
R29LLLHHM
R30LLLHLM
R31LLLLHL
R32LLLLLL

Simulation specifications_

ParameterRange/Value
Simulation area2,500 m × 2,500 m
Number of vehicles100
Number of 5G mmWave BSs2
Number of 4G LTE BSs2
Vehicle mobility typeLinear mobility
Vehicle speed10-40 m/s
Transmission range
 DSRC300 m (Max)
 mmWave~500 m
 LTE100 km (Max)
Transmission rate3-5 packets per second
Packet size512 bytes
Simulation time1,000 sec

Comparison of throughput and delay_

MethodMean T (kbps)Better efficiencyAverage delay (ms)Better efficiency
Conventional13.746%3921%
TOPSIS35.9623%3012%
ANDSF-HO2534%3719%
V2I-MoLoHA31.8927%3416%
Proposed58.89–18–

Comparison of packet loss_

MethodPacket loss (%)Better efficiency
Conventional4821%
TOPSIS32.412%
ANDSF-HO2419%
V2I-MoLoHA18.816%
Proposed12–
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