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WSN中基于非线性自适应PSO的分簇策略
引用本文:李童悦,马文平.WSN中基于非线性自适应PSO的分簇策略[J].计算机科学,2018,45(5):44-48.
作者姓名:李童悦  马文平
作者单位:西安电子科技大学通信工程学院 西安710071,西安电子科技大学通信工程学院 西安710071
基金项目:本文受国家自然科学基金(61373171),高等学校创新引智计划项目(B08038)资助
摘    要:如何更大程度地延长网络的生命周期是设计无线传感器网络路由协议时需要考虑的重要因素。针对此问题,提出一种新型的基于改进粒子群优化的分簇算法。该算法调整了传统粒子群优化算法的惯性权重系数,能够避免其过早陷入局部最优;同时考虑到能量均衡和传输路径,将转发节点与簇头协作,以减轻簇头的能耗。仿真对比实验表明,改进算法在合理分配节点和平衡簇结构系统方面具有良好的性能。

关 键 词:无线传感器网络  分簇算法  粒子群优化算法  能量均衡
收稿时间:2017/2/27 0:00:00
修稿时间:2017/4/4 0:00:00

Clustering Method in Wireless Sensor Networks Using Nonlinear Adaptive PSO Algorithm
LI Tong-yue and MA Wen-ping.Clustering Method in Wireless Sensor Networks Using Nonlinear Adaptive PSO Algorithm[J].Computer Science,2018,45(5):44-48.
Authors:LI Tong-yue and MA Wen-ping
Abstract:How to prolong the network lifetime is an important factor when designing a routing protocol in wireless sensor network.To solve this problem,a novel clustering algorithm based on the improved particle swarm optimization was presented.The algorithm modifies the inertial weight to avoid particles trapping in local optimum.It also takes into account both energy balance and transmission distance,and cooperates relays nodes with cluster heads to reduce the excessive energy consumption of cluster heads.This paper compared the proposed algorithm with other algorithms in various scenarios.Simulation results show that the proposed algorithm has good capability on distributing nodes and balancing cluster system.
Keywords:Wireless sensor network  Clustering algorithm  Particle swarm optimization algorithm  Energy balance
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