线性无线传感器网络能耗均衡算法  

Energy Balancing Algorithm in Linear Wireless Sensor Networks

作　　者：王元平[1] 鲍宇[1] 倪尧[1] 胡媛[1] 

机构地区：[1]中国矿业大学计算机学院,江苏徐州221116

出　　处：《小型微型计算机系统》2016年第12期2627-2631,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(51204185)资助;国家自然科学基金重点项目(51034005)资助;中国博士后科学基金面上项目(2012M521147)资助;国家"九七三"重点基础研究发展计划项目(2013CB227900)资助;国家"八六三"高技术研究发展计划项目(2012AA062004)资助;教育部新世纪优秀人才支持计划项目(NCET-13-1022)资助

摘　　要：在中继节点等间距线性部署的无线传感器网络中,所有普通节点的能耗不均衡,因而网络过早死亡.为解决这个问题,在综合考虑所有普通节点能耗的基础上,提出一种网络能耗均衡算法.算法采用改进的粒子群算法对网络中中继节点的位置进行优化,适应度函数选取普通节点的能耗值的标准差.首先采用自适应的动态惯性权重替代基本粒子群算法的静态权重,加快了其收敛速度;然后利用提出的迭代多阶段粒子群算法优化中继节点的位置,均衡普通节点的能耗.仿真实验结果表明经改进后的粒子群优化的网络,能耗更为均衡,网络的生存周期得以延长.In linear array wireless sensor network which relay nodes are deployed equidistantly, sensor nodes died in network early peri- od due to imbalance energy consumption. For solving this problem, under comprehensive consideration of the energy consumption of sensor nodes, an energy balancing algorithm are proposed, taking all sink nodes＇ energy consumption into consideration. The improved particle swarm optimization algorithm is used to optimize the location of relay nodes in the network. And the fitness function is the standard deviation of sink nodes＇ energy consumption. Firstly, a kind of adaptive inertia weight to be employed for optimizing the par- ticle swarm optimization, which speeds up the convergence rate. Secondly, the location of relay nodes is optimized by the proposed it- erative multi-phase particle swarm optimization algorithm, then balancing the consumption of network. Simulation experiment results show that sink nodes＇ energy more balanced and network survivals longer in the post-optimized network by particle swarm optimiza- tion.

关 键 词：线性传感器网络 粒子群算法 中继节点 生存周期 能耗均衡 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]