融合VFA和ISSA的多目标优化WSN覆盖算法  

Multi-objective optimized WSN coverage algorithm integrating VFA and ISSA

作　　者：余修武 晋诗琪 YU Xiuwu;JIN Shiqi(School of Resource&Environment and Safety Engineering,University of South China,Hengyang 421001,China;Hunan Engineering Research Center for Uranium Tailings Decommission and Treatment,Hengyang 421001,China;Hunan Province Engineering Research Center of Radioactive Control Technology in Uranium Mining and Metallurgy,Hengyang 421001,China)

机构地区：[1]南华大学资源环境与安全工程学院,湖南衡阳421001 [2]湖南省铀尾矿库退役治理技术工程技术研究中心,湖南衡阳421001 [3]铀矿冶放射性控制技术湖南省工程研究中心,湖南衡阳421001

出　　处：《西安电子科技大学学报》2024年第6期60-72,共13页Journal of Xidian University

基　　金：国家自然科学基金项目(11875164);核污染无线监测传感网数据多源融合优化与精确定位方法研究(2024JJ5338)。

摘　　要：针对无线传感器网络在监测目标区域过程中存在覆盖率低、覆盖冗余度高、节点移动距离长等问题,提出了一种虚拟力导向的改进麻雀搜索算法。首先,采用Tent混沌映射初始化种群,以增加种群的多样性;其次,引入虚拟力算法引导麻雀种群的发现者位置更新过程:节点与节点、边界、障碍物之间的相互作用力可引导发现者前往更优的位置探索,从而增强算法的全局搜索能力;然后,利用莱维飞行扰动策略改善跟随者的位置更新过程,避免算法陷入局部最优的困境;最后,采用随机反向学习策略优化全局最优个体的位置,使其在附近区域进行局部寻优,进一步提高算法的收敛速度和种群多样性。实验结果表明,相比传统算法,该算法在提高覆盖率的同时,还能减少节点的移动距离,节点分布也更加均匀。此外,在含障碍物的监测区域内,该算法将虚拟力算法的有效避障能力与麻雀搜索算法强大的寻优能力相结合,实现了有效避障的同时,仍然可以合理部署节点,实际应用价值更高。An improved sparrow search algorithm led by virtual force is put forward,aiming to address the issues of a low coverage rate,large coverage redundancy,and long node moving distance in the process of monitoring the target region of wireless sensor networks.To begin with,the population is initialized using the Tent chaotic map in order to improve the population’s diversity.Second,a virtual force algorithm is presented to direct the sparrow population’s discoverers to search for better positions.That is to say,interaction forces between nodes,boundaries,and barriers might assist the algorithm in more wide exploration by guiding discoverers into a more beneficial place.To keep the algorithm out of the local optimum dilemma,the Levy flight disturbance approach is then used to optimize the followers′position.Ultimately,the method of random reverse learning is utilized to improve the position of the global optimal individual,thus allowing for local optimization to occur in the nearby area,and improving the algorithm’s population diversity and convergence speed.Experimental findings demonstrate that the proposed algorithm can enhance the coverage rate while reducing the node’s moving distance and achieving a more uniform distribution when compared to other traditional algorithms.Furthermore,the proposed algorithm incorporates the virtual force algorithm’s effective obstacle avoidance capabilities with the sparrow search algorithm’s potent optimization seeking capabilities in the obstacle-filled monitoring area,which makes sure that the nodes successfully avoid impediments while allowing the network to deploy the nodes′placements in a reasonable manner.The approach is hence more useful for real-world applications.

关 键 词：无线传感器网络 节点部署 多目标优化 麻雀搜索算法 虚拟力算法 融合算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]