Self-Adaptive Particle Swarm Mutation Rate of Genetic Algorithm in the Link Optimization of Network Coding

Xin Jian Zhuo; Han Wen Wang

doi:10.4028/www.scientific.net/AMM.713-715.2478

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715Self-Adaptive Particle Swarm Mutation Rate of...

Self-Adaptive Particle Swarm Mutation Rate of Genetic Algorithm in the Link Optimization of Network Coding

Abstract:

Considering a multicast scenario, we want to minimize the coding links used for network coding while achieving the desired throughput. This article solves the optimization of the network coding to get with the lowest coding link scheme by using APGA. According to the simulation results, it can be concluded that the better performance of APGA than the previous algorithms.

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Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

2478-2481

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.2478

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Online since:

January 2015

Authors:

Xin Jian Zhuo*, Han Wen Wang

Keywords:

Genetic Algorithm (GA), Optimizing of Network Coding, Particle Swarm Mutation Rate

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* - Corresponding Author

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