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Genetic Representations for Evolutionary Minimization of Network Coding Resources

Minkyu Kim·Varun Aggarwal·Una-May O'Reilly·Muriel Medard·Wonsik Kim
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Abstract

We 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.

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Minkyu Kim, Varun Aggarwal, Una-May O'Reilly, Muriel Medard, Wonsik Kim. 2007-02-07. Genetic Representations for Evolutionary Minimization of Network Coding Resources. https://arxiv.org/abs/cs/0702038

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