To achieve lower energy and higher detection coverage simultaneously in scattering distribution wireless sensor networks (WSNs), a multi-objective optimization function combined with area coverage and node-communication energy is constructed. Based on the multi-objective quantum genetic algorithm (Mo-QGA) proposed by Li Bin and Zhuang-zhen Quan et al, we have obtained optimum solutions close to Pareto front. Experimental results indicate that the Mo-QGA has advantages both on efficiency and coverage, as well as low energy.

Date Published: 13 March 2013
PDF: 7 pages
Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87840H (13 March 2013); doi: 10.1117/12.2013799

Published in SPIE Proceedings Vol. 8784:
Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)