WSN中基于灰狼和乌鸦搜索算法的簇头选择路由方案

Cluster Head Selection Routing Scheme Based on Gray Wolf and Crow Search Algorithm in WSN

针对无线传感器网络的节点吞吐量低、生命周期短和延迟时间长等问题,提出一种基于灰狼和乌鸦搜索混合优化算法的簇头选择路由方案,该方案综合考虑节点剩余能量、节点间距离和传输延迟等因素,采用基于灰狼优化(Grey Wolf Optimization,GWO)和乌鸦搜索(Crow Search Algorithm,CSA)混合优化算法选择簇头,实现能量均匀利用,提高网络预期寿命.混合算法充分利用CSA算法的全局寻优和GWO算法的局部开发能力,提高了簇头选择过程中最优解的精度和可靠性.实验结果表明:本文提出的方案簇头选择性能良好,在吞吐量、传输速率和网络寿命方面比其他对比算法更具优势.

Aiming at the problems of low throughput,short life cycle and long delay time of wireless sensor networks,a cluster head selection routing scheme based on gray wolf and crow search hybrid optimization algorithm has been proposed.In this scheme,the residual energy,the distance between nodes and the transmission delay are taken into account.The hybrid optimization algorithm based on grey wolf optimization(GWO)and crow search algorithm(CSA)is used to select cluster heads,which can realize the uniform utilization of energy and improve the expected life of the network.The hybrid algorithm makes full use of the global optimization ability of CSA algorithm and the local development ability of GWO algorithm,thus improving the accuracy and reliability of the optimal solution in the process of cluster head selection.The experimental results show that the proposed scheme has good cluster head selection performance,and has more advantages than other comparative algorithms in throughput,transmission rate and network life.