摘要： 在传感器网络中，分簇是有效的层次组织方法。提出一种新的基于自适应粒子群优化的分簇路由算法。粒子群是典型的群智能算法，受启发于鸟群的捕食行为，并逐渐发展成为一种成熟的优化算法。对其进行改进，使其能够得到更好的收敛效果。仿真结果表明，相比低功耗自适应集簇分层型协议算法，该方法更具节能特性，延长了全网生存时间。

关键词: 传感器网络, 分簇路由, 自适应粒子群优化

Abstract: Clustering in Wireless Sensor Networks(WSNs) is an effective approach for organizing the network into a connected hierarchy. This paper proposes a novel clustering routing algorithm based on Adaptive Particle Swarm Optimization(APSO). Particle Swarm Optimization(PSO) is a typical swarm intelligence algorithm. It’s inspired by social behavior of bird flocking and acted as a fine optimization method. This advantage is utilized and improved to gain better convergence. Compared with Low Energy Adaptive Clustering Hierarchy(LEACH) algorithm, this protocol can reduce energy consumption and achieve better network lifetime.

Key words: sensor networks, clustering routing, Adaptive Particle Swarm Optimization(APSO)

中图分类号: 

• TP301.6