传感技术学报2016，Vol.29Issue(4)：559-565,7.DOI:10.3969/j.issn.1004-1699.2016.04.016
改进自适应粒子群算法在WSN覆盖优化中的应用
Application of Improved Adaptive Particle Swarm Optimization Algorithm in WSN Coverage Optimization
摘要
Abstract
Aiming at the problem that the coverage rate of Wireless Sensor Network(WSN)is low due to the uneven coverage of nodes,a method of coverage optimization based on improved adaptive particle swarm optimization algo⁃rithm is proposed. Firstly,the mathematical model of WSN coverage optimization is established. Then,the evolutionary factor and the polymerization factor are introduced in the inertia weight coefficient of the particle swarm optimization (PSO)algorithm in order to make the improved algorithm have a strong adaptive ability. And then,the collision resilient strategy is introduced in the iterative process of the algorithm in order to overcome the weakness that the improved parti⁃cle swarm optimization algorithm is easy to fall into local optimum in the late optimization. The experimental shows that the network coverage rates after optimizations of WSN by the algorithm in this paper are improved by 2%~6%com⁃pared with algorithms in other literatures and the distribution of sensor nodes is more uniform. Therefore,it can effec⁃tively improve the performance of wireless sensor networks,is a strong application coverage optimization algorithm.关键词
无线传感器网络/覆盖优化/改进自适应粒子群算法/惯性权重系数/碰撞回弹策略Key words
wireless sensor network/coverage optimization/improved adaptive particle swarm optimization algo-rithm/inertia weight coefficient/collision resilient strategy分类
信息技术与安全科学引用本文复制引用
吴意乐,何庆,徐同伟..改进自适应粒子群算法在WSN覆盖优化中的应用[J].传感技术学报,2016,29(4):559-565,7.基金项目
贵州省科技厅基金项目（黔科合LH字［2014］7628）；贵州省科技厅基金项目（黔科合J字［2012］2171）；贵州大学博士基金项目（贵大人基合字）（［2010］010）；贵州大学研究生创新基金项目 （）
