改进的PSO动态WSN节点部署算法
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摘要
针对无线传感器网络(WSN)节点的优化部署问题,为改善因静态节点优化部署产生的诸多问题,使WSN未知节点动态部署的精度得到进一步提高,提出一种改进的粒子群优化动态节点部署算法。将区域分成大小相等的子区域,引入拟态物理学优化算法,根据子区域及其相邻区域的节点数目对其赋予一定的加权值,简单快速寻找到移动节点的坐标。实验结果表明,该算法的种群多样性更优,部署精度更高,将网络对目标区域的覆盖质量提高到了0.981。
To solve the problem of optimal deployment of wireless sensor networks(WSN)nodes and to solve many problems caused by the optimized deployment of static nodes.To further improve the accuracy of dynamic deployment of wireless sensor networks unknown nodes,an improved particle swarm optimization dynamically deploying nodes algorithm was proposed.The region was divided into equal sub-regions,physicomimetics optimization algorithm was combined,and a certain weighted value was assigned according to the number of nodes in the sub-regions and its adjacent regions.The coordinates of the mobile node were found simply and quickly.Experimental results show that the proposed algorithm has better population diversity and higher positioning accuracy,the coverage quality of the target area is increased to 0.981.
To solve the problem of optimal deployment of wireless sensor networks(WSN)nodes and to solve many problems caused by the optimized deployment of static nodes.To further improve the accuracy of dynamic deployment of wireless sensor networks unknown nodes,an improved particle swarm optimization dynamically deploying nodes algorithm was proposed.The region was divided into equal sub-regions,physicomimetics optimization algorithm was combined,and a certain weighted value was assigned according to the number of nodes in the sub-regions and its adjacent regions.The coordinates of the mobile node were found simply and quickly.Experimental results show that the proposed algorithm has better population diversity and higher positioning accuracy,the coverage quality of the target area is increased to 0.981.
引文
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[3]Rout M,Roy R.Optimal wireless sensor network information coverage using particle swarm optimization method[J].International Journal of Electronics Letters,2017,5(24):491-499.
[4]Sabor N,Sasaki S,Abo-Zahhad M,et al.A comprehensive survey on hierarchical-based routing protocols for mobile wireless sensor networks:Review,taxonomy,and future directions[J].Wireless Communications and Mobile Computing,2017(5):1-23.
[5]Zhu F,Wei J.Localization algorithm in wireless sensor networks based on improved support vector machine[J].Journal of Nanoelectronics and Optoelectronics,2017,12(5):452-459.
[6]Zhang Q,Fok MP.A two-phase coverage-enhancing algorithm for hybrid wireless sensor networks[J].Sensors,2017,17(1):117.
[7]Raja KA,Karlmarx LR.A novel PSO based automated optimally controlled watering system for a coriander plant field using wireless sensor network[J].Asian Journal of Research in Social Sciences and Humanities,2017,7(1):431-444.
[8]Mann PS,Singh S.Energy-efficient hierarchical routing for wireless sensor networks:A swarm intelligence approach[J].Wireless Personal Communications,2017,92(2):785-805.
[9]Guo Wenzhong,Chen Jiaye,Chen Guolong,et al.Trust dynamic task allocation algorithm with Nash equilibrium for heterogeneous wireless sensor network[J].Security and Communication Networks,2015,8(10):1865-1877.
[10]CAO Yiqin,CHEN Ningxia,HUANG Xiaosheng.A task allocation strategy for wireless sensor networks with mixed coalition[J].Computer Science,2017,44(3):89-96(in Chinese).[曹义亲,陈宁霞,黄晓生.一种带混合联盟的无线传感器网络任务分配策略[J].计算机科学,2017,44(3):89-96.]
[11]ZHOU Jun,CHEN Jinghua,LIU Guoxiang,et al.Summary on inertia weight in particle swarm optimization algorithm[J].Guangdong Electric Power,2013,26(7):6-12(in Chinese).[周俊,陈璟华,刘国祥,等.粒子群优化算法中惯性权重综述[J].广东电力,2013,26(7):6-12.]
[12]SONG Mingzhi,YANG Le.Improving coverage of wireless sensor network using enhanced adaptive PSO algorithm[J].Application Research of Computers,2013,30(11):3472-3475(in Chinese).[宋明智,杨乐.基于改进自适应PSO算法的WSN覆盖优化方法[J].计算机应用研究,2013,30(11):3472-3475.]
[13]CAO Yiqin,ZHANG Zhen,HUANG Xiaosheng.Improved binary particle swarm optimization algorithm with experience factor[J].Journal of Computer Applications,2013(2):311-315(in Chinese).[曹义亲,张贞,黄晓生.改进的带经验因子的二进制粒子群优化算法[J].计算机应用,2013(2):311-315.]
[14]Cui H,Shu M,Song M,et al.Parameter selection and performance comparison of particle swarm optimization in sensor networks localization[J].Sensors,2017,17(3):487.
[15]XIE Liping.Artificial physics inspired swarm intelligence method[M].Beijing:Publishing House of Electronics Industry,2015:64-89(in Chinese).[谢丽萍.拟态物理学启发的群智能方法[M].北京:电子工业出版社,2015:64-89.]
[16]LIAO Xianli.Study on multiple coverage scheduling algorithm for wireless sensor networks[D].Chongqing:Chongqing University,2013(in Chinese).[廖先莉.无线传感器网络多重覆盖调度算法的研究[D].重庆:重庆大学,2013.]