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The Journal of Supercomputing

Erschienen in:

07.09.2022

New network interface selection based on MADM and multi-objective whale optimization algorithm in heterogeneous wireless networks

verfasst von: Brahim Mefgouda, Hanen Idoudi

Erschienen in: The Journal of Supercomputing | Ausgabe 4/2023

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Abstract

Multi-attribute decision-making (MADM) approaches are commonly used to model and solve the network interface selection problem in heterogeneous wireless networks. Despite their importance and advantages to deal with this issue, they suffer from the rank reversal problem (RRP) and the selection of the highest-ranking score network without considering the user’s/service requirements. In this paper, a novel method is introduced to solve the MADM limitations. Besides, the weights assignment technique is modelled as a multi-objective problem. Then, an extended version of the Whale Optimization Algorithm is applied to obtain the suitable weights of the decision criteria. The obtained results showed that applying the developed technique with MADM approaches reduces (sometimes avoids completely) the RRP by an average up to 94%, compared to Analytical Hierarchy Process. It also allows meeting the user’s/service requirements by optimizing data rate and packet loss, for streaming services, by an average up to 14.3 (kbps) and \(20\times 10^\text {6}\hbox {(ms)}\), respectively.

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Titel: New network interface selection based on MADM and multi-objective whale optimization algorithm in heterogeneous wireless networks
verfasst von: Brahim Mefgouda
Hanen Idoudi
Publikationsdatum: 07.09.2022
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 4/2023
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-022-04791-y

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