摘要
为了在海量物联网数据中准确监测异常节点状态,提高无线网络的安全性,提出激光红外技术下物联网异常节点状态监测方法。采用基于角度测量的激光红外定位方法判断出物联网异常节点的大概范围,将该区域作为采集区域展开异常节点特征数据采集和降维,通过奇异值分解对采集到的异常节点数据展开去噪处理,结合随机矩阵理论和平均谱半径判断节点的异常状态,以此实现对物联网异常节点状态监测。实验结果表明,所提方法的定位误差值最大仅为4.3%、监测时间在79.85 ms以下、丢包率低于0.22%,具有良好的监测能力。
In order to accurately monitor the status of abnormal nodes in massive IoT data and improve the security of wireless networks,a method for monitoring the status of abnormal nodes in IoT using laser infrared technology is pro-posed.The laser infrared positioning method based on angle measurement is used to determine the approximate range area of abnormal nodes of the Internet of Things.This area is used as the collection area to carry out abnormal node feature data collection and dimension reduction.The collected abnormal node data is denoised through singular value decomposition,and the abnormal status of nodes is judged by combining random matrix theory and average spectral ra-dius,so as to realize the monitoring of abnormal node status of the Internet of Things.The experimental results show that the proposed method has a maximum positioning error value of only 4.3%,a monitoring time of less than 79.85ms,and a packet loss rate of less than 0.22%,indicating good monitoring capability.
作者
李丹
刘磊
唐骞
LI Dan;LIU Lei;TANG Qian(Chengdu College of University of Electronic Science and Technology of China,Chengdu 611731,China)
出处
《激光杂志》
CAS
北大核心
2024年第4期186-190,共5页
Laser Journal
基金
四川省教育厅自然科学类重点研究项目(No.17ZA0193)。
关键词
激光红外技术
物联网节点
节点状态监测
激光红外定位
奇异值分解
laser infrared technology
iot nodes
node status monitoring
laser infrared positioning
singular val-ue decomposition
