文献类型：期刊文献

中文题名：基于自适应粒子群的WSN覆盖优化

英文题名：WSN Coverage Optimization Based on Adaptive Particle Swarm Optimization

作者：齐薇[1];虞慧群[1,2];范贵生[1];陈亮[1]

机构：[1]华东理工大学计算机科学与工程系,上海200237;[2]上海市计算机软件测评重点实验室,上海201112

年份：2020

卷号：47

期号：7

起止页码：243

中文期刊名：计算机科学

外文期刊名：Computer Science

收录：CSTPCD;;北大核心:【北大核心2017】；CSCD:【CSCD_E2019_2020】；

基金：国家自然科学基金(61702334,61772200);上海市自然科学基金资助项目(17ZR1406900,17ZR1429700);上海市高等教育学会规划课题(GJEL18135)。

语种：中文

中文关键词：混合传感器网络;自适应粒子群;虚拟力策略;覆盖控制;重部署

外文关键词：Hybrid sensor networks;Adaptive particle swarm optimization;Virtual force strategy;Coverage control;Redeployment

摘要：数据感知层的无线传感器网络覆盖范围对感知服务质量具有非常重要的意义。鉴于无线传感器网络初始部署的随机性所造成的覆盖冗余、覆盖空洞以及粒子群算法自身的早熟收敛等问题,提出一种基于二项感知覆盖的自适应虚拟力粒子群优化算法,以优化网络的有效覆盖率。该算法通过在网络中添加移动节点来进行位置调度的重部署分布,并计算种群进化程度和相对聚合程度以自适应调节惯性权重,同时利用适应度方差阈值判断当前状态是否需要引入虚拟力策略的干扰。文中重点分析了初始部署类别和移动节点占比对重部署覆盖性能的影响,并给出了相应的算法实现。仿真实验表明,相比ACPSO,DACPSO,DVPSO算法,改进的粒子群算法的覆盖率达到了98.33%,并且具有较高的移动效率,充分证明了该算法的有效性。
The wireless sensor network(WSN)coverage of data sensing layer has great significance on the quality of sensing services.In view of the problems of coverage redundancy,coverage void and premature convergence of particle swarm optimization caused by the randomness of initial deployment of wireless sensor network,an adaptive virtual force particle swarm optimization algorithm based on binomial perception coverage is proposed,which optimizes the effective coverage of the network.By adding mobile nodes to the network,the algorithm performs the redeployment distribution of position scheduling,adjusts the inertia weight by calculating the degree of population evolution and the degree of relative aggregation,and ueses the threshold of fitness variance to judge whether the intergerence of virtual force strategy is needed in the current state.This paper focuses on the analysis of the impact of the initial deployment category and mobile node proportion on the redeployment coverage performance,and gives the corresponding implementation algorithm.Simulation results show that compared with ACPSO,DACPSO and DVPSO,the improved PSO has 98.33%coverage and high mobile efficiency,which fully proves the effectiveness of the algorithm.