基于模糊密度峰聚类和PSO的WSN能量均衡算法  

A WSN Energy Equilibrium Algorithm Based on Fuzzy Density Peak Clustering and PSO

作　　者：张勇 吕黎明 ZHANG Yong;LV Li-ming(School of Computer Engineering,Jiangsu Ocean University,Lianyungang Jiangsu 222000,China)

机构地区：[1]江苏海洋大学计算机工程学院,江苏连云港222000

出　　处：《计算机仿真》2023年第7期418-422,共5页Computer Simulation

基　　金：江苏省“六大人才高峰”项目(XYDXX-140);江苏海洋大学人才引进项目(KQ20039)。

摘　　要：针对无线传感器网络的节点能量受限以及能量利用率低等问题,设计一种基于模糊密度峰聚类和粒子群优化的能量均衡路由算法。算法主要针对成簇阶段和数据传输阶段进行优化。在成簇阶段,采用模糊密度峰值聚类算法选取首轮簇头并将节点聚类。在传输阶段,将传输路径选择转换为旅行商问题,通过粒子群优化算法建立基站与各簇头节点之间数据传输的最优路径。将此算法与EE-LEACH和PSO-K-MEANS算法进行比较,仿真结果表明,所提算法提高了网络的使用寿命和能源效率,生存周期与其它两种算法相比,分别提高了18.4%和15.9%。In the paper,an energy equilibrium routing algorithm based on fuzzy density peak clustering and particle group optimization was designed with limited node energy and low energy efficiency of the wireless sensor network.The algorithm was optimized for cluster formation and data transmission stages.In the cluster-forming stage,the first cluster heads were selected and the cluster nodes were clustered using the fuzzy density peak clustering algorithm.In the transmission stage;The transmission path selection was transformed into a travel quotient problem,and the optimal path of data transmission between the base station and each cluster head node was established through the particle cluster optimization algorithm.Finally,this algorithm was compared with the EE-LEACH and PSO-KMEANS algorithms,and the simulation results show that it improves the network service life and energy efficiency,and compared with the other two algorithms,the survival cycle has been improved by 18.4%and 15.9%,respectively.

关 键 词：无线传感器网络 模糊密度峰值聚类 粒子群优化 路由算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]