采用遗传模拟退火策略的WSN节点部署优化  

Deployment of Wireless Sensor Network Nodes by Improved Genetic Simulated Annealing Algorithm

作　　者：李忠[1] 

机构地区：[1]重庆电子工程职业学院物联网学院,重庆401331

出　　处：《系统仿真学报》2014年第2期353-356,共4页Journal of System Simulation

基　　金：重庆市教委科学技术研究项目(KJ122204)

摘　　要：无线传感器网络(Wireless sensor networks,WSN)节点部署优化是近年来国内外学者研究的热点。针对目前WSN节点部署方法存在生命周期过短、网络节点严重冗余等缺陷,提出一种改进的遗传模拟退火策略用于WSN节点部署,该策略融合遗传算法和模拟退火算法的基本思想,借鉴小生境的思想对遗传算法选择算子进行设计,避免了遗传初期有效基因的丢失;使用自适应算子对交叉算子和变异算子进行改进,并对模拟退火参数重新进行了设计。最后进行了对比实验,通过对实验结果分析表明策略能够以相对较小的代价完成传WSN节点部署,能快速收敛于最优解,提高网络的整体覆盖率。Deployment of wireless sensor network nodes is a hot research issue at home and abroad in recent years. For the defects of the WSN node deployment method with serious redundant network nodes and short life cycle, an improved genetic simulated annealing algorithm for WSN node deployment was proposed, which integrated the basic idea of genetic algorithms and simulated annealing algorithm. In genetic, the algorithm drew on the idea of niche, to avoid the loss of genetic effective early gene selection operator; adaptive crossover and mutation operator, the redesign of the simulated annealing parameters. Contrast experimental results show that the algorithm can be completed at a relatively small cost sensor sensing node deployment, fast convergence to the optimal solution to improve the coverage of the network as a whole.

关 键 词：遗传算法 模拟退火 节点部署 无线传感器网络 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]