基于边缘计算技术的终端设备远程部署节点智能识别研究
投稿时间:2020-12-08  修订日期:2020-12-29  点此下载全文
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作者单位邮编
卢玉华* 北京智芯半导体科技有限公司 北京 102200 102200
高文俊 北京智芯半导体科技有限公司 北京 102200 
张伟 北京智芯半导体科技有限公司 北京 102200 
中文摘要:传统的终端设备节点识别方法未计算节点测度指标,导致其节点识别效率和识别率低、识别速度慢。为此,本研究基于边缘计算技术设计了新的终端设备远程部署节点智能识别方法。首先采用希尔伯特变换技术,将处于时域的终端设备信号分解为复频域信号的频率和相位,并确定节点关联程度,建立终端设备网络空间模型;然后利用边缘计算技术设计节点参考框架,计算节点子图和最大邻居连通密度测度,从而实现对终端设备远程部署节点的有效识别。实验结果表明:本文方法识别终端设备远程部署节点所需的时间更短,且对节点的变化更为敏感,具有较高的识别效率、和节点识别率。
中文关键词:边缘计算技术  终端设备  远程部署节点  节点识别  节点关联程度  连通密度
 
Research on intelligent identification of remote deployment node of terminal equipment based on edge computing technology
Abstract:The traditional node recognition method of terminal equipment does not calculate the node measure index, which leads to the low node recognition efficiency and recognition rate and slow recognition speed. For this reason, a new intelligent identification method for remote deployment nodes of terminal equipment is designed based on edge computing technology. Firstly, the signal in the time domain is decomposed into the frequency and phase of the signal in the complex frequency domain by using The Hilbert transform technology, and the node correlation degree is determined to establish the network space model of the terminal equipment. Then, the node reference frame is designed by using edge computing technology, and the node subplot and the maximum neighbor connectivity density measure are calculated, so as to realize the effective identification of the terminal equipment remote deployment node. The experimental results show that the proposed method takes less time to identify the remote deployment nodes of terminal equipment, and is more sensitive to the changes of nodes, and has higher recognition efficiency and node recognition rate.
keywords:Edge computing technology  Terminal equipment  Remote deployment node  Node identification  Degree of node association  Connected density
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