基于改进樽海鞘群的障碍物环境WSN节点覆盖优化  

WSN Node Coverage Optimization Based on Improved Salp Swarm Algorithm in Obstacle Environment

作　　者：张永 韩睿 徐华荣 王文浩 王肖丛 孙田弋 孙御骥 ZHANG Yong;HAN Rui;XU Huarong;WANG Wenhao;WANG Xiaocong;SUN Tianyi;SUN Yuji(State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310000,China;Electric Power Research Institute,State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310000,China;Nanjing Nanrui Information and Communication Technology Co.,Ltd.,Nanjing 210000,China;College of Microelectronics,Shandong University,Jinan 250000,China)

机构地区：[1]国网浙江省电力有限公司,浙江杭州310000 [2]国网浙江省电力有限公司电力科学研究院,浙江杭州310000 [3]南京南瑞信息通信科技有限公司,江苏南京210000 [4]山东大学微电子学院,山东济南250000

出　　处：《仪表技术与传感器》2023年第10期85-92,共8页Instrument Technique and Sensor

基　　金：国网总部科技项目(5700-202119266A-0-0-00)。

摘　　要：针对无线传感器网络节点部署易造成覆盖冗余和覆盖盲区的不足,提出一种障碍物环境中多策略融合改进樽海鞘群算法的WSN节点覆盖优化策略。为了提高樽海鞘群算法的寻优性能,设计基于模糊逻辑的种群角色调整机制,对优势领导者种群规模动态调整,平衡算法全局搜索与局部开发;引入多项式变异对跟随者个体扰动,增强跟随者局部随机搜索能力;设计拓扑对立学习生成领导者个体的拓扑对立解,充分挖掘区域内精英位置信息。将改进樽海鞘群算法应用于求解障碍物环境中WSN节点覆盖优化问题,以节点覆盖率最大为目标,迭代搜索节点部署的最优位置。结果表明,改进算法能够有效提升网络覆盖率,减少节点冗余,优化节点分布。Aiming at the shortage of coverage redundancy and coverage gap caused by node deployment in wireless sensor networks,this paper proposed a WSN node coverage optimization strategy based on multi-strategy fusion improved salp swarm algorithm in obstacle environments.In order to improve the optimization performance of salp swarm algorithm,a population role adjustment mechanism based on fuzzy logic was designed to dynamically adjust the size of the leader population and balance the global search and local development of the algorithm.The polynomial variation perturbation was introduced to carry out individual variation on the follower,so as to enhance the local random search ability of the follower.The topology opposite learning was designed to generate the topology opposite solution of the leader individual to fully tap the location information of the elite in the region.The improved salp swarm algorithm was applied to solve the WSN node coverage optimization problem in the obstacle environment.With the goal of maximum network coverage,the node deployment location was iteratively optimized.The results show that the improved algorithm improves network coverage,effectively reduces node redundancy and optimizes node distribution.

关 键 词：无线传感器网络 覆盖优化 障碍物 樽海鞘群算法 拓扑对立学习 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]