An Edge-Computing Paradigm for Internet of Things over Power Line Communication Networks

被引:25
|
作者
Qian, Yuwen [1 ]
Shi, Long [2 ]
Li, Jun [1 ]
Zhou, Xiangwei [3 ]
Shu, Feng [1 ]
Wang, Jiangzhou [4 ]
机构
[1] Nanjing Univ Sci & Technol, Nanjing, Jiangsu, Peoples R China
[2] Singapore Univ Technol & Design, Singapore, Singapore
[3] Louisiana State Univ, Baton Rouge, LA 70803 USA
[4] Univ Kent, Canterbury, Kent, England
来源
IEEE NETWORK | 2020年 / 34卷 / 02期
关键词
Internet of Things; Intelligent sensors; Cloud computing; Servers; Wireless sensor networks; Smart devices; BROAD-BAND; IOT; ORCHESTRATION;
D O I
10.1109/MNET.001.1900282
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Power line communication (PLC) technology has created a niche use in the Internet of Things (IoT) by offering flexible and reliable connection among power-driven IoT devices/sensors over existing wired networks. In IoT over PLC networks, massive real-time data generated by the ever-growing connected devices will eventually pose an overwhelming burden on the IoT cloud, which in turn severely degrades the network performance. To cope with these issues, edge computing (EC) has emerged as a complement to cloud computing, aiming at offloading a portion of computing in the cloud to the network edges closer to the IoT devices. However, confronting a practical scenario that some electrical devices cannot communicate with wireless and mobile networks directly, existing EC paradigms may not be directly applied to IoT over PLC networks. In this paper, we propose a novel EC-IoT over PLC paradigm to reduce the transmission latency while migrating a portion of computing from the cloud to the edges. First, we develop a distributed EC platform to serve terminal users (TUs) in different IoT systems with various IoT services. Second, we put forth a cache-enabled scheme to store the popular contents from the cloud and edge sensors to reduce redundant data transmissions between TUs and the cloud. Finally, our experimental results demonstrate that the proposed EC-IoT over PLC network can significantly reduce energy consumption and transmission latency.
引用
收藏
页码:262 / 269
页数:8
相关论文
共 50 条
  • [21] Edge Computing Application, Architecture, and Challenges in Ubiquitous Power Internet of Things
    Liu, Dongqi
    Liang, Haolan
    Zeng, Xiangjun
    Zhang, Qiong
    Zhang, Zidong
    Li, Minhong
    FRONTIERS IN ENERGY RESEARCH, 2022, 10
  • [22] EdgeKeeper: a trusted edge computing framework for ubiquitous power Internet of Things
    Yang, Weiyong
    Liu, Wei
    Wei, Xingshen
    Guo, Zixin
    Yang, Kangle
    Huang, Hao
    Qi, Longyun
    FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 2021, 22 (03) : 374 - 399
  • [23] Toward Smart Home Authentication Using PUF and Edge-Computing Paradigm
    Wu, Tsu-Yang
    Kong, Fangfang
    Wang, Liyang
    Chen, Yeh-Cheng
    Kumari, Saru
    Pan, Jeng-Shyang
    SENSORS, 2022, 22 (23)
  • [24] Toward Communication-Efficient Federated Learning in the Internet of Things With Edge Computing
    Sun, Haifeng
    Li, Shiqi
    Yu, F. Richard
    Qi, Qi
    Wang, Jingyu
    Liao, Jianxin
    IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (11) : 11053 - 11067
  • [25] Edge Computing and Cloud Computing for Internet of Things: A Review
    Andriulo, Francesco Cosimo
    Fiore, Marco
    Mongiello, Marina
    Traversa, Emanuele
    Zizzo, Vera
    INFORMATICS-BASEL, 2024, 11 (04):
  • [26] Research on Intelligent Power Automation Technology Based on Edge Computing of Power Internet of Things
    Su Zhiyong
    Lai Weiping
    Zhang Yanghua
    Huang Yanshan
    2020 INTERNATIONAL CONFERENCE OF RECENT TRENDS IN ENVIRONMENTAL SUSTAINABILITY AND GREEN TECHNOLOGIES (ICRTEG 2020), 2020, 204
  • [27] Measurement and Characterization of Electromagnetic Noise in Edge Computing Networks for the Industrial Internet of Things
    Li, Huiting
    Liu, Liu
    Li, Yiqian
    Yuan, Ze
    Zhang, Kun
    SENSORS, 2019, 19 (14)
  • [28] SG-Edge: Key Technology of Power Internet of Things Trusted Edge Computing Framework
    Yang W.-Y.
    Liu W.
    Cui H.-Z.
    Wei X.-S.
    Huang H.
    Liao P.
    Qian Z.-Z.
    Wang Y.-Q.
    Ruan Jian Xue Bao/Journal of Software, 2022, 33 (02): : 641 - 663
  • [29] Edge Computing for Internet of Things Based on FPGA
    Ferdian, Rian
    Aisuwarya, Ratna
    Erlina, Tati
    2020 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY SYSTEMS AND INNOVATION (ICITSI), 2020, : 20 - 23
  • [30] Mobile Edge Computing Empowers Internet of Things
    Ansari, Nirwan
    Sun, Xiang
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2018, E101B (03) : 604 - 619