计算机与现代化

• 网络与通信 • 上一篇    下一篇

基于改进粒子群优化算法的无线传感器网络定位

  

  1. 河南工业职业技术学院计算机工程系,河南南阳473000
  • 收稿日期:2015-02-13 出版日期:2015-07-23 发布日期:2015-07-28
  • 作者简介:作者简介:裴祥(1984-),男,重庆奉节人,河南工业职业技术学院计算机工程系助教,硕士,研究方向:计算机网络; 李巧君(1983-),女,河南郑州人,讲师,硕士,研究方向:计算机网络。

Localization for Wireless Sensor Network Based on Modified Particle #br# Swarm Optimization Algorithm

  1. Department of Computer Engineering, Henan Polytechnic Institute, Nanyang 473000, China
  • Received:2015-02-13 Online:2015-07-23 Published:2015-07-28

摘要:

针对经典DVHop定位算法第3阶段计算未知节点位置存在较大误差的问题,提出一种基于改进粒子群优化算法的无线传感器网络定位方法。首先分析DVHop算法误差大的原因,并将定位问题转
换成未知节点坐标的优化问题,然后采用改进粒子群算法对问题进行优化,并引入收缩因子加快搜索速度和精度,找到全局最优未知节点坐标,最后在Matlab 2012平台上进行仿真实验。仿真结果表明,
本文算法提高了传感器节点的定位精度,大幅度降低了定位误差。

关键词: 无线传感器网络, 节点定位, 改进粒子群优化算法, DVHop算法

Abstract:

The third stage in classical DVHop location algorithm has big localization error, so this paper puts forward a localization method for wireless sensor network based
on modified particle swarm optimization algorithm. Firstly, the defects of DVHop algorithm is analyzed, and the unknown nodes positioning problem is converted into the
optimization problem, and then the modified particle swarm optimization algorithm is used to optimize the problem, and the shrinkage factor is introduced to accelerate the
search speed and precision, and find out the global optimal position of unknown nodes, finally the simulation experiment is carried out on Matlab 2012 platform. The simulation
results show that the proposed algorithm improves the positioning accuracy of sensor nodes, and greatly reduces the positioning error.

Key words: wireless sensor network, node localization, modified particle swarm optimization algorithm, DVHop algorithm

中图分类号: