基于匹配信任度机制的移动传感网簇头更新算法
Cluster head updating algorithm for mobile sensor networks based on matching trust mechanism
王恒 1郑笔耕1
作者信息
- 1. 荆楚理工学院电子信息工程学院 荆门 448000
- 折叠
摘要
为解决移动传感网部署过程中存在的簇头节点更新质量不佳和节点生存率较低等不足,提出了一种基于匹配信任度机制的移动传感网簇头更新算法.首先,引入K-means算法,利用误差平方根函数来完成网络初始聚类,以快速定位聚类中心,提升聚类形成速度.随后,综合考虑备选簇头剩余能量、备选簇头与当前簇头的欧氏距离、备选簇头覆盖范围内节点总数3个因素,设计了基于匹配信任度的簇头更新方法,按权值对各因素进行平均分配,进而将信任度权值最高的节点作为备选簇头,从而选举出生存质量较高的节点.仿真实验表明,算法具有更高的网络稳定运行时间和簇头节点生存率,以及更低的节点故障概率.其中,网络稳定运行时间提升了80%以上,簇头节点生存率保持在90%以上,节点故障概率也较低,具有明显的优势.
Abstract
In order to the problems of poor update quality and low survival rate of cluster head nodes in the deployment process of mobile sensor networks,a cluster head update algorithm for mobile sensor networks based on matching trust mechanism is proposed.First,K-means algorithm is introduced to complete the initial clustering of the network by using the square root function of error to quickly locate the cluster center and improve the clustering speed.Then,considering the three factors of the residual energy of the candidate cluster head,the Euclidean distance between the candidate cluster head and the current cluster head,and the total number of nodes within the coverage range of the candidate cluster head,a cluster head update method based on matching trust is designed.Each factor is evenly distributed according to the weight value,and then the node with the highest trust weight value is used as the candidate cluster head,so as to elect the node with higher survival quality.Simulation results show that the algorithm in this paper has higher network stable running time,higher cluster head node survival rate,and lower node failure probability.Among them,the stable running time of the network has been improved by over 80%,the survival rate of cluster head nodes has been maintained at over 90%,and the probability of node failure is also low,which has obvious advantages.
关键词
移动传感网/匹配信任度/簇头更新/欧氏聚类/区域分割Key words
mobile sensor network/matching trust/head updating/euclidean clustering/region segmentation引用本文复制引用
基金项目
荆门市科学技术局科技计划项目(2023YFYB089)
荆楚理工学院科学研究项目(YB202319)
出版年
2024
NETL
NSTL
万方数据