首页|基于多因素均衡动态分簇的WSN路由协议算法

基于多因素均衡动态分簇的WSN路由协议算法

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为了解决无线传感器网络分簇路由协议随机筛选簇头节点的位置分布不均衡及转发节点的数据传输路径不合理会加剧节点能量消耗、缩短网络生存周期的问题,提出一种基于改进社交网络搜索(improved social network search,ISNS)算法优化模糊 C 均值聚类(fuzzy C-means,FCM)的多因素均衡动态分簇路由协议(multi-factor balanced dynamic clustering routing protocol,MD-LEACH).首先,引入莱维飞行改进反向精英学习策略,以增强社交网络搜索算法的全局寻优能力;接着,使用ISNS优化模糊C均值聚类算法对网络节点动态均匀分簇,均衡网络负载;此外,在每个簇内,考虑簇内节点的能量因素和位置因素引入模糊推理,设计两种簇头选取模式,动态选举簇首,提高簇首质量.在稳定传输阶段,将单跳改为簇首之间的通信的方式,使用改进的蚁群算法寻找最优数据传输路径,提高能量效率.仿真结果表明,算法能够有效提高能量效率,平衡网络负载,延长网络生存期.
WSN Routing Protocol Algorithm Based on Multi-factor Balanced Dynamic Clustering
In order to solve the problem that the unbalanced positional distribution of randomly screened cluster head nodes and un-reasonable data transmission paths of forwarding nodes of the cluster routing protocol for wireless sensor networks will exacerbate the node's energy consumption and shorten the network's survival period,a multifactorial balanced dynamic cluster routing protocol based on improved social network search(ISNS)algorithm optimized fuzzy C-mean clustering(FCM)(multi-factor balanced dynamic cluste-ring routing protocol,MD-LEACH)was proposed.Firstly,the Levy flight was introduced to improve the reverse elite learning strategy to enhance the global optimization capability of the social network search algorithm.Then,the ISNS-optimized fuzzy C-mean clustering algorithm was used to dynamically cluster the network nodes uniformly and balance the load of the network.Moreover,fuzzy reasoning was introduced to consider the energy factor and the location factor of nodes in the clusters in each cluster,and two cluster-head selec-tion modes were designed to dynamically elect the cluster head to improve the Cluster head quality.In the stable transmission phase,the single hop was changed to the way of communication between cluster heads,and the improved ant colony algorithm was used to find the optimal data transmission path to improve the energy efficiency.Simulation results show that the algorithm can effectively improve the energy efficiency,balance the network load,and extend the network survival period.

improved social network search(ISNS)algorithmsfuzzy C-means clustering(FCM)Levy flightmulti-factor equi-libriumdynamic clusteringfuzzy reasoning

朱本科、高丙朋、蔡鑫

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新疆大学电气工程学院,乌鲁木齐 830047

改进社交网络搜索(ISNS)算法 模糊C均值聚类(FCM) 莱维飞行 多因素均衡 动态分簇 模糊推理

国家自然科学基金新疆维吾尔自治区自然科学基金自治区高校基本科研业务费科研项目

622630312022D01C694XJEDU2023P025

2024

10.12404/j.issn.1671-1815.2305655

科学技术与工程
中国技术经济学会

科学技术与工程

CSTPCD北大核心
影响因子：0.338
ISSN：1671-1815
年,卷(期)：2024.24(16)