传感器网络分簇时间跨度优化聚类算法  

Sensor network clustering algorithm with clustering time span optimization

作　　者：梁娟[1,2] 赵开新 吴媛 

机构地区：[1]河南工学院计算机科学与技术系,河南新乡453002 [2]武汉理工大学信息工程学院,武汉430070

出　　处：《计算机应用》2016年第10期2670-2674,共5页journal of Computer Applications

基　　金：河南省高等学校重点科研项目(15A520064;16A520084)~~

摘　　要：针对无线传感器网络(WSN)簇头节点能效低、网络能量负载不均衡问题,提出一种传感器网络分簇时间跨度优化(CTSO)聚类算法。该算法首先在簇头选举方式上关注了簇内成员数量和簇头间距的约束问题,尽可能地避免各个簇之间发生覆盖重叠,优化簇内节点能量;接着对簇头的选举周期进行优化,以任务执行周期大小作为一个时间跨度并分为多个轮,通过最小化簇头选举的轮数来减少用于选择簇头而花费在广播消息上的能量,提升簇头节点的能量利用率。实验仿真结果表明,对比基于多Agent的同质态数据汇聚路由方案以及自适应数据汇聚路由策略,CTSO算法的平均能量效率分别提高了62.0%和138.4%,节点寿命则分别提高了17%和9%。CTSO算法在提升无线传感器网络簇头能效及均衡节点能量上具有较好的效果。Concerning the low energy efficiency and network energy imbalance of cluster head in Wireless Sensor Network （WSN）, a sensor network clustering algorithm with Clustering Time Span Optimization （CTSO） was proposed. Firstly, the constraints within the cluster membership and cluster head spacing in cluster head election was considered to avoid overlapping between the various clusters as much as possible and optimize the energy of the cluster nodes. Secondly, the cluster head election cycle was optimized and divided into rounds by considering the task excution cycle as time span, by minimizing the cluster head election rounds, the cost for selecting cluster heads and the energy for broadcasting messages were reduced, and energy utilization of cluster nodes was improved. Simulation results showed that, compared to the homogeneous state data routing scheme based on multiple Agents and adaptive data aggregation routing policy, the average energy efficiency of CTSO was increased by 62.0% and 138.4% respectively, and the node life was increased by 17% and 9 % respectively. CTSO algorithm has a good effect on promoting the energy efficiency of cluster head node and balancing the energy of nodes in WSN.

关 键 词：传感器网络 时间跨度 分布式能量流聚类 簇头选择周期优化 

分 类 号：TP929.5[自动化与计算机技术]