基于事件的移动认知无线传感器网分簇算法

Event-Based Clustering Algorithm for Mobile Cognitive Radio Sensor Networks

移动认知无线传感网中,节点的移动特性会导致网络拓扑结构不断变化,节点的能耗不均衡等问题,本文提出一种基于事件的移动认知无线传感器网的分簇算法,来重点解决上述问题.算法根据通信区域内的预估计停留时间确定了合格节点和备用节点,通过节点的移动方向、速度、节点在簇中的预估计连接时间等特性,采用直接分簇的方法来建簇,提高簇的稳定性,保证了路由跳数最少.同mESAC,EACRP和MNB 3个算法进行了仿真实验比较,验证了本算法有更低的分簇能耗和更好的连通性.

In mobile cognitive wireless sensor networks,the mobile characteristics of nodes will lead to continuous changes in network topology and uneven energy consumption of nodes.This study proposes an event-based clustering algorithm for mobile cognitive wireless sensor networks.The above problem is solved.The algorithm determines the qualified node and the standby node according to the pre-estimated dwell time in the communication area and adopts the direct clustering method to build the node by the moving direction,speed,and pre-estimated connection time of the node in the cluster.Clusters improve the stability of the cluster and ensure the minimum number of router hops.Compared with the simulation algorithms of m ESAC,EACRP,and MNB,the algorithm has lower cluster energy consumption and better connectivity.