无线传感器网络覆盖优化仿真研究  

Simulation Research on Wireless Sensor Networks Coverage Optimization

作　　者：陈翔[1] 胡品爱[2] 

机构地区：[1]杭州师范大学杭州国际服务工程学院,浙江杭州310012 [2]浙江传媒学院信息化办公室,浙江杭州310018

出　　处：《计算机仿真》2012年第3期209-212,共4页Computer Simulation

基　　金：浙江省教育厅科研项目(Y201016580)

摘　　要：研究无线传感器覆盖(WSN)优化问题,由于网络传感器节点分布不均匀,又存在冗余等问题。传统WSN高密度部署方法,节点分布极不均匀,节点覆盖区域之间的重复率高,节点浪费严重,导致网络覆盖率低、成本高。为了提高无线传感器网络的覆盖率,提出一种混沌粒子群优化算法(CPSO)的WSN覆盖优化算法。首先以提高网络覆盖率为优化目标,建立WSN覆盖优化数学模型,然后通过粒子间协作进行求解,并对粒子群混沌扰动,保持粒子多样性,从而得到最优网络覆盖。仿真结果表明,相对于其它覆盖优化算法,CPSO能够以较少传感器节点获得较高网络覆盖率,提高了网络通信效率,降低网络成本。The premature may happen in particle swarm optimization algorithm.This paper proposed a wireless sensor network（WSN） coverage optimization method based on chaotic particle swarm optimization algorithm（CPSO） based on chaos theory.Firstly,WSN coverage optimization mathematical model was established to improve the network coverage as the optimization goal.Through the cooperation between the particles,chaos ergodicity and randomness were used to disturbed the particle swarm,maintaining the diversity of particles to prevent fall into local optimum.The simulation results show that,compared with other WSN coverage optimization algorithm,CPSO can use small sensor nodes to obtain higher coverage rate and effectively realize the wireless sensor network coverage.

关 键 词：无线传感器网络 覆盖优化 粒子群算法 混沌 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]