Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation

Journal Title: EAI Endorsed Transactions on Energy Web - Year 2016, Vol 3, Issue 8

Abstract

A low energy clustering method of body area networks based on fuzzy simulated evolutionary computation is proposed in this paper. To reduce communication energy consumption, we also designed a fuzzy controller to dynamically adjust the crossover and mutation probability. Simulations are conducted by using the proposed method, the clustering methods based on the particle swarm optimization and the method based on the quantum evolutionary algorithm. Results show that the energy consumption of the proposed method decreased compare with the other two methods, which means the proposed method significantly improves the energy efficiency.

Authors and Affiliations

Jie Zhou, Eryk Dutkiewicz, Ren Ping Liu, Gengfa Fang, Yuanan Liu

Keywords

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  • EP ID EP45148
  • DOI http://dx.doi.org/10.4108/eai.28-9-2015.2261426
  • Views 257
  • Downloads 0

How To Cite

Jie Zhou, Eryk Dutkiewicz, Ren Ping Liu, Gengfa Fang, Yuanan Liu (2016). Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation. EAI Endorsed Transactions on Energy Web, 3(8), -. https://europub.co.uk/articles/-A-45148