组移动模型中一种基于种群特性的传感器网络分簇方法

A Flock-Based Clustering Algorithm in WSNs with Group Mobile Model

为了增强传感器网络在组移动模型下的簇结构稳定性,提出了一种基于生物种群特性的分簇算法——FBCA算法。算法利用移动代理向信息素高的节点迁移实现簇头的轮换,并将节点与簇头之间的链路稳定性作为节点选择所加入簇的衡量指标,有效地利用了组移动模型下节点的移动特征来优化簇结构的稳定性。仿真表明,在组移动模型中,采用FBCA算法的传感器网络有着较好的簇结构稳定性和能量效率及较均匀的簇头分布性。

To promote cluster＇s stability in wireless sensor networks （WSNs） under the circumstance of nodes moving in group, we propose a flock-based clustering algorithm （FBCA）. The algorithm change cluster-head by moving mobile agent to neighborhood with the highest pheromone, and use link stability between node and cluster-head as standard to join which cluster, making use of mobile character to optimize stability of cluster in an effective way. The simulation result prove the good performance of FBCA in mobile group model.