计算机科学 ›› 2012, Vol. 39 ›› Issue (Z6): 129-131.

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基于量子粒子群优化的WSN节点定位改进

王新芳,张冰,冯友兵   

  1. (江苏科技大学电子信息学院 镇江212003)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Improvement of Node Localization in Wireless Sensor Networks Based on Quantum-behaved Particle Swarm Optimization

  • Online:2018-11-16 Published:2018-11-16

摘要: 针对无线传感器网络定位低成本、低功耗和高精度的要求,在基于接收信号强度(RSSI )测距的基础上,提出 了一种量子粒子群优化(QPSO)的改进加权质心定位算法,即采用QPSO优化WCLA的佑计坐标来改善定位误差, 并改进收缩扩展系数增强QPSO算法的收敛速度。仿真表明,改进的算法与WCLA算法和经过粒子群优化的 WCI_A算法相比,其节点定位精度得到显著提高,且能克服粒子群优化算法的收敛速度慢、易陷入局部极小值的缺点。

关键词: 无线传感器网络,接收信号强度指示,加权质心算法,量子粒子群优化算法,节点定位

Abstract: Focusing on the requirements of low cost and high accuracy in wireless sensor network(WSN),an improvc- ment method of weighted centroid localization algorithm was introduced based on received signal strength indicator(RS- SI) which used the quantum-behaved particle sSwarm optimization(QPSO ) to optimize WCLA evaluation coordinates to decrease the localization error, moreover, the convergence rate was quicken by improving expand/ contract coefficient. The simulation shows that the localization accuracy of the new algorithm is significantly superior to that of weighted centroid localization algorithm and weighted centroid localization optimized by PSO, and it could also overcome the short coming of PSO that convergent slowly and easy to fall into local minimum.

Key words: Wireless sensor networks, RSSI, Weighted centroid localization algorithm, Quantum-behaved particle swarm optimization, Nodc localization

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