摘要
针对无线传感器网络中分簇路由算法节点能量利用率低、能量消耗不均匀等问题,提出了一种优化聚类分簇结合自适应中继策略的双簇首无线传感器网络路由算法.该算法对分簇路由协议中的三个阶段分别进行优化设计.成簇阶段,首先对双簇首模型下最优成簇规模与网络能耗的关系进行理论分析,然后使用改进的算术优化算法计算模糊C均值算法的初始聚类中心,提高了模糊C均值算法聚类成簇的准确率和鲁棒性.簇首选举阶段,引入双簇首策略,以节点的位置、能量和中心度为影响因子,根据承担任务的不同分别为内外簇首设计独立的簇首评价函数,以评价值为依据由节点分布式动态选举簇首减少了广播数量,同时可以将整个簇的能量负载平均分配到每个簇成员节点中.数据传输阶段,设置了多跳中继策略的距离适用条件,并以能量消耗速率为依据选择中继节点,避免了节点提前过载.仿真结果表明:在多种规模的网络中,该算法相较于对比算法在均衡网络负载、提高能量利用效率方面效果更好,从而延长了网络的有效感测时间.
Aiming at the problems of low node energy utilization and uneven energy consumption of clustered routing algorithm in wireless sensor networks,a dual head wireless sensor networks routing algorithm based on optimized cluster analysis for clustering combined with adaptive relay strategy was proposed.The algorithm optimizes the design of the three stages in the clustering routing protocol respectively.In the clustering stage,the relationship between optimal cluster size and network energy consumption under the dual cluster head model is theoretically analyzed,and then use the improved arithmetic optimization algorithm to calculate the initial clustering center of the fuzzy C-means algorithm,which improves the clustering accuracy and robustness of fuzzy C-means algorithm.In the stage of cluster head election,introduce the dual cluster head strategy,and take the position,energy and centrality of nodes as the influencing factors,and design independent cluster head evaluation functions for the inner and outer cluster heads according to the different tasks they undertake.The cluster head is dynamically elected by nodes based on the evaluation value,which can reduce the number of broadcasts and evenly distribute the energy load of the whole cluster to each cluster member node.In the data transmission stage,set the distance applicable conditions of the multi-hop relay policy,and select relay nodes based on the energy consumption rate to avoid node overload in advance.The simulation results show that in various scale networks,the algorithm is more effective in balancing the network load and improving the energy utilization efficiency than the comparison algorithms,thus prolonging the effective sensing time of the network.
作者
张晶
高翔
张宏
ZHANG Jing;GAO Xiang;ZHANG Hong(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China;Yunnan Xiaorun Technology Service Co.,Ltd.,Kunming 650500,China;Yunnan Key Laboratory of Artificial Intelligence,Kunming University of Science and Technology,Kunming 650500,China;Key Laboratory of Computer Technology Application of Yunnan Province,Kunming University of Science and Technology,Kunming 650500,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2024年第4期1007-1017,共11页
Journal of Chinese Computer Systems
基金
云南省科技计划项目重大科技专项计划项目(202202AD080008)资助
云南省基础研究计划重点项目(202101AS070016)资助
2020年云南省研究生优质课程“算法分析与设计”建设项目(109920210048)资助
云南省“兴滇英才支持计划”产业创新人才项目(云发改人事[2019]1096号)资助
云南省技术创新人才项目(2019HB113)资助
云南省计算机技术应用重点实验室开放基金项目(CB22144S073A)资助.
关键词
无线传感器网络
分簇路由算法
模糊C均值
算术优化算法
能耗优化
wireless sensor networks
clustering routing algorithm
fuzzy C-means
arithmetic optimization algorithm
energy consumption optimization
