WSN中节点分布的协方差矩阵自适应优化策略

摘要

针对无线传感器网络( WSNs )中传感器节点的分布优化问题，提出了一种基于协方差矩阵自适应进化策略( CMA-ES)的网络节点分布优化方法。首先，以最大化网络的区域覆盖率为目标建立问题的求解模型，然后，采用CMA-ES算法对模型求解得到网络最优的节点位置分布方案。仿真对比实验表明：CMA-ES算法可以很好地解决无线传感器网络节点的分布优化问题，相比于传统遗传算法、基本粒子群算法和差分进化算法，表现出较快的寻优速度和更高的区域覆盖率。%Aiming at the node distribution optimization problem of Wireless Sensor Networks ( WSNs) ,then a method for net-work node distribution optimization based on Covariance Matrix Adaptation Evolution Strategy ( CMA-ES) was proposed. Firstly, for the goal of maximizing network area coverage rate,the solving model was established,and then the model was solved using CMA-ES algorithm,and the optimal node distribution scheme for WSNs was got. Simulation comparative experiments show that CMA-ES algorithm can efficiently solve the distribution optimization problem of wireless sensor network node,comparing with traditional genetic algorithm,particle swarm optimization algorithm and differential evolution algorithm,and CMA-ES achieves faster optimiza-tion speed and higher area coverage rate.