广西师范大学学报（自然科学版）2018，Vol.36Issue(3)：9-16,8.DOI:10.16088/j.issn.1001-6600.2018.03.002
基于改进粒子群算法的无线传感器网络覆盖策略
Coverage Strategy of Wireless Sensor Network Based on Improved Particle Swarm Optimization Algorithm
摘要
Abstract
As particle swarm optimization algorithm in the optimization of wireless sensor networks is easy to fall into local optimal solution and slow late convergence as well as other shortcomings,an improved particle swarm optimization algorithm based on dynamic acceleration factor (PSO-DAC)is proposed.It adopts decreasing inertia weight coefficients and introduces dynamic acceleration coefficients.The experimental results show that the algorithm has improved the coverage ratio by 34.6%than that of the basic particle swarm algorithm,which is 2 9.3% higher than that of the particle swarm algorithm based on decreasing inertia weight coefficient.It is proved that the PSO-DAC algorithm can effectively increase the convergence speed and improve the coverage rate of nodes,so as to improve the coverage effect of the whole network and prolong the network lifetime.关键词
无线传感器网络/PSO-DAC算法/加速因子/网络覆盖/覆盖率Key words
wireless sensor network/PSO-DAC algorithm/acceleration coefficients/network coverage/coverage rate分类
信息技术与安全科学引用本文复制引用
滕志军,吕金玲,郭力文,许媛媛..基于改进粒子群算法的无线传感器网络覆盖策略[J].广西师范大学学报（自然科学版）,2018,36(3):9-16,8.基金项目
国家自然科学基金(51277023) （51277023）
吉林省教育厅"十三五"科学研究规划项目(JJKH20180439KJ) （JJKH20180439KJ）
