A genetic algorithm with elite mutation to optimize cruise area of mobile sinks in hierarchical wireless sensor networks

Authors:
Mong-Fong Horng;Yi-Ting Chen;Shu-Chuan Chu;Jeng-Shyang Pan;Bin-Yih Liao;Jang-Pong Hsu;Jia-Nan Lin
Affiliations:
Department of Electronics Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan;Department of Electronics Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan;School of Information Science, Engineering and Mathematics, Flinders University, Adelaide, Australia;Department of Electronics Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan, Innovative Information Industry Research Center (IIIRC), Shenzhen Graduate School, Harb ...;Department of Electronics Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan;Advance Multimedia Internet Technology Inc., Tainan, Taiwan;Advance Multimedia Internet Technology Inc., Tainan, Taiwan
Venue:
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
Year:
2012

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Abstract

In this paper, a new genetic algorithm with elite mutation is proposed for optimization problems. The proposed elite mutation scheme (EM) improves traditional genetic algorithms with a better ability to locate and to approach fast to optimal solutions, even in cases of huge data set. The proposed EM is to select elite chromosomes and mutate according to the similarity between elite chromosomes and selected chromosomes. The designed similarity guides effectively the search toward optimal solutions with less generation. The proposed EM is applied to optimize the cruise area of mobile sinks in hierarchical wireless sensor networks (WSNs). Numeric results show that (1) the proposed EM benefits the discovery of optimal solutions in a large solution space; (2) the approach to optimal solutions is more stable and faster; (3) the search guidance derived from the chromosome similarity is critical to the improvements of optimal solution discovery. Besides, the minimization of cruise are been proved to have the advantages of energy-saving, time-saving and reliable data collection in WSNs.