基于混沌粒子群算法的无线传感器网络覆盖优化

摘要

To improve the unreasonable distribution of sensors' random deployment, increase network coverage rate,taking the network coverage rate as the optimized goal, an optimization method of wireless sensor networks coverage based on Chaos Particle Swarm Optimization (CPSO) was proposed in this paper.Based on the ergodicity, stochastic property of chaos,the algorithm can avoid the shortage of being easily trapped in a local extremum at the later evolution stage.The simulation results indicate that the addressed algorithm is superior to particle swarm optimization in coverage optimization.%为了改善传感器节点随机部署时的不合理分布,提高网络覆盖率,以网络覆盖率为优化目标,提出了基于混沌粒子群的无线传感器网络覆盖优化算法.该算法利用混沌运动的遍历性和随机性,克服了粒子群算法后期陷入局部最优的缺点.仿真结果表明,该算法比基本粒子群算法具有更好的覆盖优化效果.