节点密度自适应的传感器网络加权分簇算法

The Weighted Clustering Algorithm with Adaptive Density of Nodes for WSNS

无线传感器网络的分簇密度不确定会导致网络的有效性降低、生存周期减少等问题。提出了一种节点密度自适应的传感器网络加权分簇算法,通过设定权值,将节点的节点度、与邻节点的平均距离及节点的剩余能量考虑在内,保证综合性能最好的节点成为簇头。再通过控制簇头发射功率使簇内节点密度控制在合理范围内。该分簇算法优化了簇头选择,均衡了网络节点的能量消耗,延长了网络的生命周期。最后通过仿真进一步验证该分簇算法的性能。

The uncertain clustering density of WSNS can reduce the effectiveness and lifetime of the network. A weighted clustering algorithm with adaptive density of nodes for wireless sensor networks is proposed. By setting weights which including nodes＇ degrees, the distances between nodes and the left energy of nodes, the best nodes can be chosen as cluster headers. Power transmitting control of the cluster head makes the node density reasonable. This clustering algorithm optimizes cluster head choosing, balances the networks energy consumption,and prolongs the networks lifetime. Finally the simulation tests the effect of this clustering algorithm on the behaviour of the network.