摘要： 针对现有覆盖算法存在早熟、收敛性差以及易陷入局部搜索等缺点，结合三峡库区水质监测的应用环境，提出一种无线传感器网络覆盖优化算法。基于带收缩因子的粒子群优化模型，利用混沌Tent映射产生的混沌序列代替模型原有的随机参数，并将聚集度指标作为判定条件，实现参数的自适应调整。实验结果表明，该算法能提高网络覆盖率。

关键词: 无线传感器网络, 覆盖优化, 粒子群优化, 收缩因子, 混沌, 自适应

Abstract: Aiming at the disadvantages of existing coverage optimization algorithms, such as early maturity, poor convergence performance and easy to fall into local extreme, this paper combines the application environment of the Three Gorges Reservoir water quality monitoring, presents a new coverage optimization algorithm for Wireless Sensor Network(WSN). The Particle Swarm Optimization(PSO) model within constriction factors is adopted. It uses chaotic sequence generated by chaotic Tent mapping instead of the original random parameter, introduces the conception of aggregation degree for judging, and realizes parameters adaptive adjustments. Experimental results show that the algorithm can improve network coverage.

Key words: Wireless Sensor Network(WSN), coverage optimization, Particle Swarm Optimization(PSO), constriction factor, chaos, self- adaptation

中图分类号: 

• TN915