Title | ||
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An Edge-Computing Paradigm for Internet of Things over Power Line Communication Networks |
Abstract | ||
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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. |
Year | DOI | Venue |
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2020 | 10.1109/MNET.001.1900282 | IEEE Network |
Keywords | DocType | Volume |
Internet of Things,Intelligent sensors,Cloud computing,Servers,Wireless sensor networks,Smart devices | Journal | 34 |
Issue | ISSN | Citations |
2 | 0890-8044 | 1 |
PageRank | References | Authors |
0.35 | 0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Yuwen Qian | 1 | 1 | 0.35 |
long shi | 2 | 59 | 16.04 |
Jun Li | 3 | 747 | 90.31 |
Xiangwei Zhou | 4 | 451 | 35.87 |
Feng Shu | 5 | 300 | 48.17 |
Jiangzhou Wang | 6 | 2674 | 212.44 |