Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation

Authors

DOI:

https://doi.org/10.4108/eai.28-9-2015.2261426

Keywords:

wireless sensor networks, simulated evolutionary computation, fuzzy controller

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.

Downloads

Download data is not yet available.

Downloads

Published

14-12-2015

How to Cite

1.
Zhou J, Dutkiewicz E, Liu RP, Fang G, Liu Y. Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation. EAI Endorsed Trans Energy Web [Internet]. 2015 Dec. 14 [cited 2024 May 18];3(8):e5. Available from: https://publications.eai.eu/index.php/ew/article/view/1057