基于节点分布均匀度模型的加权能量检测GAF算法

GAF algorithm based on node uniformity model and weighted energy detection

在分析了传统GAF算法在选举簇头和虚拟单元格方格划分不足的基础上,提出了一种节点分布均匀度模型的加权能量检测GAF算法,在对虚拟单元格形状改进的基础上,建立节点分布均匀度模型,进一步对虚拟单元格的划分提供参考,同时对算法中簇头选举综合考虑节点剩余能量及其与虚拟单元格内物理节点的质心间距,能有效解决节点能量消耗不均衡问题。最后以GPSR作为GAF算法的底层通信协议进行仿真,结果表明该算法有效地节省了节点的能量,延长了网络的生存周期。

On the basis of analyzing shortcomings of the cluster head election and virtual cell division of traditional GAF algorithm, a GAF algorithm based on node uniformity model and weighted energy detection is proposed. On the basis of improving the shape of virtual cell, we build the node uniformity model and further provide the reference for virtual cell division. And we also consider the residual energy of the nodes and the distance between the cluster and the center of mass of nodes in virtual cell. It can solve the unbalanced energy consumption of nodes effectively. We use GPSR as the lower layer communication protocols of GAF algorithm, and the simulation results show that the improved algorithm can save the energy of the nodes effectively and prolong the network lifetime.