摘要
为了解决无线传感器网络分簇路由算法中存在的"热区"问题和簇头选取问题,设计了一种自适应粒子群优化的非均匀分簇路由算法。首先通过候选节点与汇聚节点之间的距离计算竞争半径并构造出大小不等的多个簇,然后根据簇规模引入优化的粒子群算法,评价节点剩余能量和节点之间的距离等因素选取最终簇头,以剩余能量较多的簇头作为下一跳,形成以汇聚节点为根节点的多跳路由。仿真结果表明,与LEACH算法和EEUC算法相比,所提算法网络生存期分别延长了34%和16%,平均能量消耗分别减少了22%和12%,有效地减少了网络节点的能量消耗。
To deal with the ＂hot area＂ problem and cluster heads selection in clustering routing algorithm of Wireless Sensor Network（WSN）,the paper designed an uneven clustering routing algorithm based on adaptive Particle Swarm Optimization（PSO）.Firstly,according to the distance between candidate nodes and sink node,the competitive radius was calculated and clusters of various sizes were constructed.Then this paper introduced the PSO according to the cluster size.The PSO was used to select the final cluster heads by evaluating factors such as residual energy of nodes and distance between nodes.The cluster heads with more residual energy were chosen as the next hop to form multi-top route in which the sink node is the root.The simulation results show that compared with other two similar algorithms,LEACH and EUCC,the proposed algorithm extends 34% and 16% of survival time of network separately,reduces 22% and 12% of average energy consumption respectively,and effectively decreases the network nodes energy consumption.
出处
《计算机应用》
CSCD
北大核心
2012年第1期131-133,共3页
journal of Computer Applications
基金
湖南省自然科学基金资助项目(09JJ6094)
湖南省2011科技计划项目(2011FJ3082)
关键词
无线传感器网络
非均匀分簇路由算法
粒子群优化算法
能量消耗
生存期
Wireless Sensor Network（WSN）
uneven clustering routing algorithm
Particle Swarm Optimization（PSO） algorithm
energy consumption
survival time
