基于AVMC算法的WSN节点分布优化策略
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摘要
能耗和通信质量问题制约着无线传感器网络技术的发展,合理的节点部署既能降低能耗又能促进网络通信,就此提出一种基于蚁群算法(ACA,ant colony algorithm)、拟物力(VMF,virtual material force)和质心算法(CA,centroid algorithm)的WSN节点分布优化策略(AVMC).首先,该策略中采用蚁群算法选取合理个数和位置的节点,将节点位置优化模型转化为简单的线性模型;其次,运用拟物力算法对选中的节点进行位置优化;最后,结合Voronoi图在点与点之间的专属特性,采用质心算法提高节点位置精度.实验仿真结果表明,该优化策略能够减少WSN中节点冗余度,并在提高监测区域覆盖率的基础上提高了网络节点覆盖效率.
The development of wireless sensor networks is restricted by energy consumption and communication quality. But reasonable node deployment can reduce energy consumption and promote network communication. In this paper, a distribution optimization strategy of WSN nodes based on ant colony algorithm, virtual material force and centroid algorithm is proposed. Firstly, ant colony algorithm is used to select nodes with reasonable number and location, and transforming the node optimization model into a simple linear model. Secondly, we use the algorithm of quasi physical force to optimize the location of the selected nodes. Finally, we combine with the exclusive characteristics of Voronoi diagrams between points and points to precise location accuracy of nodes using centroid algorithm. And experimental simulation results show that, the optimization strategy can reduce nodes redundancy in WSN, and improve the coverage efficiency of network nodes on the basis of improving the coverage rate of monitoring area.
The development of wireless sensor networks is restricted by energy consumption and communication quality. But reasonable node deployment can reduce energy consumption and promote network communication. In this paper, a distribution optimization strategy of WSN nodes based on ant colony algorithm, virtual material force and centroid algorithm is proposed. Firstly, ant colony algorithm is used to select nodes with reasonable number and location, and transforming the node optimization model into a simple linear model. Secondly, we use the algorithm of quasi physical force to optimize the location of the selected nodes. Finally, we combine with the exclusive characteristics of Voronoi diagrams between points and points to precise location accuracy of nodes using centroid algorithm. And experimental simulation results show that, the optimization strategy can reduce nodes redundancy in WSN, and improve the coverage efficiency of network nodes on the basis of improving the coverage rate of monitoring area.
引文
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[2] 王曙光,杨蕾,刘满仓.自适应半径调整的无线传感器网络覆盖算法[J].传感器与微系统,2016,35(12):137-139.
[3] 王凯彬,程良伦.一种无线传感器网络冗余节点状态调度方法[J].计算机应用研究,2018,35(4):1227-1230.
[4] 王珊,王庆生,樊茂森.基于移动节点的无线传感器网络覆盖空洞修复方法[J].传感器与微系统,2015,34(4):134-136.
[5] 刘小垒,张小松,胡腾,等.分布式布谷鸟算法在无线传感器网络布局优化中的应用[J].计算机应用研究,2018,35(7):2063-2065.
[6] 彭丽英.改进的蚁群算法网络节点覆盖优化研究[J].计算机仿真,2011,28(9):151-153.
[7] 梁俊卿.基于改进粒子群算法的无线传感器网络覆盖优化[J].现代电子技术,2017,40(17):32-35.
[8] ALDURAIBI F,LASLA N,YOUNIS M.Coverage-based node placement optimization in wireless sensor network with linear topolpgy[C]//IEEE International Conference on Communications.Changchun,China,2016:107-124.
[9] XIA J.Coverage optimization strategy of wireless sensor network based on swarm intelligence algorithm[C]//International Conference on Smart City and Systems Engineering.Changsha,China,2017:179-182.
[10] DAOUDI A,DETIENNE B,AZOUZI R E,et al.Robust coverage optimization approach in wirless sensor networks[C]//Interational Conference on Wireless Networks and Mobile Communications.Shenzhen,China,2017:1-7.
[11] 王明亮,闵新力,薛君志.基于改进人工鱼群算法的WSN覆盖优化策略[J].微电子学与计算机,2015,32(6):78-81.
[12] LE D V,OH H,YOON S.VirFID:A virtual force(VF)-based interest-driven moving phenomenon monitoring scheme using multiple mobile sensor nodes[J].Ad Hoc Networks,2015(27):112-132.
[13] 李光辉,胡世红.基于VF-CS的移动传感器网络覆盖优化算法[J].通信学报,2018,39(3):95-107.
[14] 曾梦凡,陈思洋,张文茜,等.利用蚁群算法生成覆盖表:探索与挖掘[J].软件学报,2016,27(4):855-878.
[15] 毛科技,方凯,戴国勇,等.基于改进蚁群算法的无线传感器网络栅栏覆盖优化研究[J].传感技术学报,2015,28(7):1058-1065.
[16] 祁春阳,戴欢,赵晓燕,等.基于虚拟力和泰森多边形的分布式覆盖算法[J].计算机工程与设计,2018,39(3):606-611.
[17] Abo Zahhad M,Sabor N,Sasaki,et al.A centralized immune-Voronoi deployment algorithm for coverage maximization and energy conservation in mobile wireless sensor networks[J].Information Fusion,2016,30(C):36-51.
[18] 赵春江,吴华瑞,刘强,朱丽.基于Voronoi的无线传感器网络覆盖控制优化策略[J].通信学报,2013,34(9):115-122.
[19] 王婷婷,孙彦景,徐钊,等.基于虚拟力的异构无线传感器网络覆盖优化策略[J].传感技术学报,2016,29(8):1253-1259.