Research Article
Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation
@ARTICLE{10.4108/eai.28-9-2015.2261426, author={Jie Zhou and Eryk Dutkiewicz and Ren Ping Liu and Gengfa Fang and Yuanan Liu}, title={Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation}, journal={EAI Endorsed Transactions on Energy Web}, volume={3}, number={8}, publisher={ACM}, journal_a={EW}, year={2015}, month={12}, keywords={wireless sensor networks, simulated evolutionary computation, fuzzy controller}, doi={10.4108/eai.28-9-2015.2261426} }- Jie Zhou
Eryk Dutkiewicz
Ren Ping Liu
Gengfa Fang
Yuanan Liu
Year: 2015
Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation
EW
EAI
DOI: 10.4108/eai.28-9-2015.2261426
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.
Copyright © 2015 R. P. Liu et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.