基于多目标遗传算法的无线传感器网络重新部署方法

研究节点动态移动以增强覆盖率,同时考虑节点的最大移动距离最小化.通过引入虚拟合力对基因进行变异,提出一种基于NSGA-II框架的改进的多目标遗传算法,达到网络覆盖率与节点移动距离之间的平衡.实验证明,该结果能得到较分散的前沿占优解.

Based on multi-objective genetic algorithm wireless sensor network re-deploying method

In the past few years wireless sensor networks(WSNs) have received a greater interest for their applications. Effective sensor coverage is one of the key topics addressed in wireless sensor networks study, which refers to the deployment of WSNs. In many scenes,such as hostile environment,sensor nodes must are deployed randomly.However, random deployment of sensor nodes can leave holes in terms of coverage in the sensing area.How to enhance the coverage in randomly deployed sensor nodes is a hot problem. In this paper, the dynamic movement of the nodes to enhance the coverage is studied, and minimizing the maximum moving distances of nodes is considered. With virtual force on genetic variation a based on NSGA-II modified multi-objective genetic algorithm is proposed to reach a compromise between network coverage and moving distances of nodes. Experimental results state that the proposed algorithm can get more decentralized Pareto optimal set.