摘要
无线传感器网络节点的能量有限,而分簇算法能有效解决节点能耗受限与不同节点能量开销不平衡问题。在网络路由分簇的基础上,提出了一种节点负载均衡的分簇算法。该算法对经典的分簇协议LEACH的簇头选择机制进行了改进,应用量子粒子群对簇头选取进行优化。为解决算法后期易陷入局部极小的问题,采用了基于群体适应值方差的早熟判断机制,结合模拟退火算法进行局部优化。仿真结果表明:该算法使网络节点负载更均衡,有效提高了无线传感器网络的性能。
The energy of wireless sensor networks node is usually limited,while clustering algorithm can resolve effectively node energy consumption limitation and the unbalanced consumption of different nodes.Based on clustering of network routing,a node load-balanced clustering algorithm for wireless sensor networks is proposed.This algorithm applies quantum-behaved particle swarm to optimize the cluster-head selection,improves cluster- head selection mechanism of LEACH classical clustering protocol.Aiming at solving problem of the algorithm easy to fall into local minimum,use the mechanism of premature judging based on variance of group adaptive value, combining with simulated annealing for local optimization.Simulation results show that the proposed algorithm balances the networks nodes load better and effectively improves performance of WSNs.
出处
《传感器与微系统》
CSCD
北大核心
2014年第3期139-142,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(61174021)
关键词
无线传感器网络
量子粒子群优化
分簇协议
模拟退火
wireless sensor networks（WSNs）
quantum-behaved particle swarm optimization（QPSO）
clustering protocol
simulated annealing
