针对经典分簇算法LEACH存在的缺陷,设计了一种基于图形密铺的分簇算法。算法通过用正六边形对监测区域密铺,首先完成对节点的分簇;然后利用基于通信距离的相对剩余能量参数选举簇头,避免簇头成为瓶颈节点。仿真实验表明,与LEACH算法相比,该算法能够均衡各个簇的节点数,提高了网络生存时间和数据通信总量。
To overcome the defects of LEACH,a clustering hierarchy algorithm is proposed,based on graphic tessellation. By tessellating regular hexagon among the monitoring area,clustering is completed,following which the cluster head is selected according to relative residual energy connected with the communication distance,thus the cluster head is avoided becoming the bottleneck node. Simulation results show that our algorithm is able to balance the node number of each cluster and improve the network lifetime as well as the total amount of data communications.