Genetic Representations for Evolutionary Minimization of Network Coding Resources

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dc.creatorKim, Minkyu
dc.creatorAggarwal, Varun
dc.creatorO'Reilly, Una-May
dc.creatorMedard, Muriel
dc.creatorKim, Wonsik
dc.date2007-02-07
dc.date.accessioned2026-07-07T07:45:15Z
dc.date.available2026-07-07T07:45:15Z
dc.descriptionWe demonstrate how a genetic algorithm solves the problem of minimizing the resources used for network coding, subject to a throughput constraint, in a multicast scenario. A genetic algorithm avoids the computational complexity that makes the problem NP-hard and, for our experiments, greatly improves on sub-optimal solutions of established methods. We compare two different genotype encodings, which tradeoff search space size with fitness landscape, as well as the associated genetic operators. Our finding favors a smaller encoding despite its fewer intermediate solutions and demonstrates the impact of the modularity enforced by genetic operators on the performance of the algorithm.
dc.description10 pages, 3 figures, accepted to the 4th European Workshop on the Application of Nature-Inspired Techniques to Telecommunication Networks and Other Connected Systems (EvoCOMNET 2007)
dc.identifierhttps://arxiv.org/abs/cs/0702038
dc.identifierhttp://arxiv.org/abs/cs/0702038
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/123469
dc.subjectNeural and Evolutionary Computing
dc.subjectNetworking and Internet Architecture
dc.titleGenetic Representations for Evolutionary Minimization of Network Coding Resources
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