基于改进蜣螂优化模糊C均值的WSN分簇路由算法  

WSN Clustering Routing Algorithm Based on Improved Dung Beetle Optimized Fuzzy C-means

作　　者：刘晓悦 郑新颖 LIU Xiaoyue;ZHENG Xinying(School of Electrical Engineering,North China University of Science and Technology)

机构地区：[1]华北理工大学电气工程学院

出　　处：《仪表技术与传感器》2025年第1期105-111,126,共8页Instrument Technique and Sensor

基　　金：国家自然科学基金项目(42274056)。

摘　　要：针对无线传感器网络能耗不均、生存周期短的问题,提出一种基于改进蜣螂优化模糊C均值的WSN分簇路由算法(IDFCA)。分簇阶段,采用改进蜣螂算法优化模糊C均值、初始聚类中心的选取,根据距离以及网络最优簇头个数划分网络拓扑结构,以均衡各簇内节点能耗;簇头选举阶段,综合考虑节点能量和距离,并设置簇头更换阈值,降低簇头更换频率,减少网络能耗;数据传输阶段,利用改进的蜣螂算法,基于能量、负载和转发方向搜索簇头到基站的最优传输路径。仿真结果表明:IDFCA算法的网络相比于LEACH、CS-K、POFCA分别提高了56.1%、26.1%、14.6%。IDFCA算法能够均衡网络能耗,延长网络生命周期。Aiming at the problems of uneven energy consumption and short survival cycle of wireless sensor network(WSN),a WSN cluster routing algorithm based on improved dung beetle optimized fuzzy C-mean(IDFCA)was proposed.In the clustering stage,to balance the energy consumption of nodes within each cluster,the improved dung beetle algorithm(IDBO)optimized the selection of initial clustering centers for fuzzy C-means,network topology was segmented based on distance and optimal number of cluster heads.In the cluster heads selection phase,to reduce the frequency of cluster heads replacement and minimize network energy consumption,cluster heads replacement threshold was set comprehensively considering the node energy and distance.In the data transmission phase,IDBO was used to search for the optimal transmission path from the cluster head to the base station,focusing on energy,load and forwarding direction.Simulation results show that the network with IDFCA algorithm improves 56.1%,26.1%,and 14.6%compared to LEACH,CS-K,and POFCA,respectively.The IDFCA algorithm is able to equalize the energy consumption of the network and prolong the network life cycle.

关 键 词：无线传感器网络 改进蜣螂优化算法 模糊C均值 分簇路由算法 能量均衡 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]