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基于改进型粒子群的WSN分簇路由算法

发表时间:2011-10-31  浏览量:1162  下载量:349
全部作者: 夏季文,马福昌
作者单位: 太原理工大学测控技术研究所
摘 要: 为有效延长无线传感器网络(wireless sensor network, WSN)的生存时间,需要设计能量有效的簇头选择和成簇机制,以适应无线传感器网络的特点。基于此提出了一种改进型粒子群——非线性自适应粒子群优化(particle swarm optimization, PSO)的分簇路由算法。在适应度函数中,根据节点的能量分布定义了基于节点剩余能量的簇内加权平均距离,并同时考虑了网络节点和簇头节点的平均剩余能量比,以及网络节点的平均传输能量损耗3个因素。在成簇过程中融入了新的竞争机制F,考虑了簇头的剩余能量和距离基站的远近等因素,并对其进行仿真。仿真结果表明:该优化算法使得簇头分布均匀,均衡了网络能耗,是WSN能耗最小化的一种有效方法。
关 键 词: 计算机应用;无线传感器网络;非线性自适应粒子群;分簇路由;簇内加权平均距离
Title: Improved PSO-based clustering routing algorithm for WSN
Author: XIA Jiwen, MA Fuchang
Organization: Institute of Measuring and Controlling Technology, Taiyuan University of Technology
Abstract: In order to prolong the network lifetime for wireless sensor network (WSN), an energy-efficient mechanism of cluster-head selection and formation of clusters is needed to be designed to adapt to the characteristics of (wireless sensor network, WSN). Therefore, this paper proposes an improved routing algorithm (NAPSO-CA). In the fitness function, according to the energy distribution of nodes, the weighting average of distance in clusters is defined based on residual energy of nodes, also taking into consideration the factors of proportion of nodes and cluster-heads' average residual energy, the average transmission energy dissipation of network. In formation of clusters, blending to a new competition mechanism F, the factors of cluster-heads' energy and distance to base station are included, and the simulation analysis is carried out. The simulation results show that the modified algorithm makes cluster-head distribution more even, balances network energy and is considered an effective method to solve the minimization problem of the energy consumption of WSN.
Key words: computer application; wireless sensor network; nonlinear adaptive particle swarm optimization; clustering routing; weighting average of distance in clusters
发表期数: 2011年10月第20期
引用格式: 夏季文,马福昌. 基于改进型粒子群的WSN分簇路由算法[J]. 中国科技论文在线精品论文,2011,4(20):1871-1876.
 
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