<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Different Radio Access Technologies (RATs) coexist in the same area has encouraged the researchers to get profit from the available networks by selecting of the best RAT at each moment of the call session to satisfy the user requirements. In this paper, we address a real-world problem which is the frequent mobility of the users in heterogeneous networks. We present in this paper a framework that allows users to select the best networks for the whole call session especially form a mobility perspective. The framework consists of several steps, starting by the path prediction which is performed using a Markov model order 2. The second step is to make the network selection on the zones of each predicted path, while in the third step; we get the best RAT’s configuration for each predicted path. Finally, we use another function to select one of the best configurations to be used for all the possible used paths. The results show that our proposal performs very well by eliminating the unnecessary vertical handover while maintaining a good Quality of Service (QoS).</p></abstract>

Different Radio Access Technologies (RATs) coexist in the same area has encouraged the researchers to get profit from the available networks by selecting of the best RAT at each moment of the call session to satisfy the user requirements. In this paper, we address a real-world problem which is the frequent mobility of the users in heterogeneous networks. We present in this paper a framework that allows users to select the best networks for the whole call session especially form a mobility perspective. The framework consists of several steps, starting by the path prediction which is performed using a Markov model order 2. The second step is to make the network selection on the zones of each predicted path, while in the third step; we get the best RAT’s configuration for each predicted path. Finally, we use another function to select one of the best configurations to be used for all the possible used paths. The results show that our proposal performs very well by eliminating the unnecessary vertical handover while maintaining a good Quality of Service (QoS).

Mobility Aware Network Selection in a Heterogeneous Wireless Environment

Transport and Telecommunication Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Mobility Aware Network Selection in a Heterogeneous Wireless Environment"}

Different Radio Access Technologies (RATs) coexist in the same area has encouraged the researchers to get profit from the available networks by selecting of...

Mobility Aware Network Selection in a Heterogeneous Wireless Environment

Publié en ligne: 27 févr. 2020

Pages: 32 - 46

DOI: https://doi.org/10.2478/ttj-2020-0003

Mots clés
Radio Access Technologies, network selection, paths prediction, Markov model, vertical handover, QoS, call session

© 2020 Fayssal Bendaoud et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mobility Aware Network Selection in a Heterogeneous Wireless Environment

Publié en ligne: 27 févr. 2020

Pages: 32 - 46

DOI: https://doi.org/10.2478/ttj-2020-0003

Mots clésRadio Access Technologies, network selection, paths prediction, Markov model, vertical handover, QoS, call session

© 2020 Fayssal Bendaoud et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Radio Access Technologies, network selection, paths prediction, Markov model, vertical handover, QoS, call session