Edge Computing and IoT: Systems, Management and Security. First EAI International Conference, ICECI 2020, Virtual Event, November 6, 2020, Proceedings

Research Article

Data Gathering System Based on Multi-layer Edge Computing Nodes

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  • @INPROCEEDINGS{10.1007/978-3-030-73429-9_4,
        author={Shuzhen Xiang and Huigui Rong and Zhangchi Xu},
        title={Data Gathering System Based on Multi-layer Edge Computing Nodes},
        proceedings={Edge Computing and IoT: Systems, Management and Security. First EAI International Conference, ICECI 2020, Virtual Event, November 6, 2020, Proceedings},
        proceedings_a={ICECI},
        year={2021},
        month={7},
        keywords={Data gathering Edge computing Compress sense},
        doi={10.1007/978-3-030-73429-9_4}
    }
    
  • Shuzhen Xiang
    Huigui Rong
    Zhangchi Xu
    Year: 2021
    Data Gathering System Based on Multi-layer Edge Computing Nodes
    ICECI
    Springer
    DOI: 10.1007/978-3-030-73429-9_4
Shuzhen Xiang1, Huigui Rong1, Zhangchi Xu1
  • 1: Hunan University

Abstract

The development of Internet of Things technology brings new opportunities for the development of edge computing. As an emerging computing model, edge computing makes full use of the equipment resources at the edge of the network and creates a new network computing system at the edge of the network. At the same time, the emergence of edge computing solves the problem of high latency in WAN which cannot be solved for a long time in the field of cloud computing, and brings users with low latency, fast response and good service experience. This article will use the edges computing architecture to construct a multi-layer data collection system. In this system model, sensors upload data to the designated edge nodes for processing, rather than remote cloud computing centers. Data collection and sample training tasks of sensor nodes in different ranges are realized through the design of multi-layer edge nodes. This system reduces the energy consumption of data uploading and the delay in network communication. As a result, it provides a better network experience for the end users. And it tries to solve the problem that the edge node in the edge system cannot satisfy multiple training task requests at the same time.