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

作　　者：滕志军 吕金玲 郭力文 许媛媛 TENG Zhijun;Lü Jinling;GUO Liwen;XU Yuanyuan(School of Information Engineering,Northeast Electric Power University,Jilin Jilin 132012,China)

机构地区：[1]东北电力大学信息工程学院,吉林吉林132012

出　　处：《广西师范大学学报（自然科学版）》2018年第3期9-16,共8页Journal of Guangxi Normal University:Natural Science Edition

基　　金：国家自然科学基金(51277023);吉林省教育厅"十三五"科学研究规划项目(JJKH20180439KJ)

摘　　要：针对粒子群算法在无线传感器网络优化方面存在收敛速率慢、容易陷进"早熟"等缺点,本文提出一种基于动态加速因子的粒子群优化算法(PSO-DAC)。该算法主要采用呈线性变化的加速因子以及引入递减的惯性权重系数。实验结果显示,该算法的网络优化覆盖率相比粒子群算法提高了34.6%,比基于递减惯性权重系数的粒子群算法提高了29.3%,证明PSO-DAC算法可有效提高收敛速度以及移动节点覆盖率,从而改善了整个网络的覆盖效果,延伸网络生存周期。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 29.3%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 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]