Finding a robust configuration for the AEDB information dissemination protocol for mobile ad hoc networks

Abstract : The Adaptive Enhanced Distance Based Broadcasting Protocol, AEDB hereinafter, is an advanced adaptive protocol for information dissemination in mobile ad hoc networks (MANETs). It is based on the Distance Based broadcasting protocol, and it acts differently according to local information to minimize the energy and network use, while maximizing the coverage of the broadcasting process. As most of the existing communication protocols, AEDB relies on different thresholds for adapting its behavior to the environment. We propose in this work to look for configurations that induce a stable performance of the protocol in different networks by automatically fine tuning these thresholds thanks to the use of cooperative coevolutionary multi-objective evolutionary algorithms. Finding robust solutions for this problem is important because MANETs have a highly unpredictable and dynamic topology, features that have a strong influence on the performance of the protocol. Consequently, robust solutions that show a good performance under any circumstances are required. In this work, we define different fitness functions that measure robustness of solutions for better guiding the algorithm towards more robust solutions. They are: median, constrained, worst coverage, and worst hypervolume. Results show, that the two worst-case approaches perform better, not only in case of robustness but also in terms of accuracy of the reported AEDB configurations on a large set of networks.
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Article dans une revue
Applied Soft Computing, Elsevier, 2015, 32, pp.494-508. 〈10.1016/j.asoc.2015.04.003〉
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https://hal.inria.fr/hal-01249479
Contributeur : Talbi El-Ghazali <>
Soumis le : vendredi 1 janvier 2016 - 19:26:17
Dernière modification le : mardi 3 juillet 2018 - 11:49:12

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Patricia Ruiz, Bernabé Dorronsoro, El-Ghazali Talbi, Pascal Bouvry. Finding a robust configuration for the AEDB information dissemination protocol for mobile ad hoc networks. Applied Soft Computing, Elsevier, 2015, 32, pp.494-508. 〈10.1016/j.asoc.2015.04.003〉. 〈hal-01249479〉

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