蜂窝聚类网络的能量级别分簇和簇头选择算法

Energy level clustering and cluster head selecting algorithm for cellular clustering networks

针对无线传感器网络分簇结构存在簇间重叠覆盖率较高和簇内节点能量不均衡的问题,提出一种能量级别的蜂窝聚类结构无线传感器网络结构。给出最小化总簇头能耗下的簇间通信距离,减少簇头在通信上的能量负担,由于分簇结构的正六边形特征使得所有的簇间通信距离相同,有利于簇头间的能量均衡,簇间的重叠覆盖率达到最小,提高网络的能量利用效率。在簇头的选择上,采用一种基于能量级别的簇头选举机制,延长节点的平均寿命。实验结果表明,相比基于多层次和距离感知的集群机制以及基于多目标模糊聚类的分簇算法,CSLC算法在节点平均剩余能量上分别提高了15.6%和24.5%,节点存活时间分别提高了15.8%和4.7%。

Aiming at the problem that the overlap coverage between clusters in the cluster structure of wireless sensor networks is higher and the energy of nodes in the cluster is unbalanced,an energy level cellular sensor network structure was proposed.The communication distance between clusters under minimizing total cluster head energy consumption was given,and the energy burden on the communication was reduced,at the same time,because of the regular hexagon characteristics of the cluster structure,the communication distance between all clusters was the same,which was beneficial to the energy balance between the cluster heads and the overlap between the clusters to achieve the minimum coverage,and the energy efficiency of the network was improved.For the selection of cluster head,a cluster head election mechanism based on the energy level was used to extend the average life of the node.The simulation results show that,compared to clustering mechanism based on the multi-level and distance perception and clustering algorithm based on fuzzy clustering multi-objective,a node average remaining energy is increased by 15.6%and 24.5%using CSLC algorithm,the node survival time is increased by 15.8%and 4.7%respectively.