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

被引:26
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
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