Edge Intelligence for Real-Time Data Analytics in an IoT-Based Smart Metering System

The recent widespread deployment of smart meters on a global scale has created an immense amount of fine-grained smart meter data, which requires effective and real-time analysis. Although the cloud center has powerful data processing capabilities, it is insufficient for real-time analysis, especial...

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Bibliographic Details
Published in:IEEE network 2020-09, Vol.34 (5), p.68-74
Main Authors: Hu, Hailin, Tang, Liangrui
Format: Article
Language:English
Subjects:
Artificial neural networks
Cloud computing
Collaboration
Computer architecture
Data analysis
Data processing
Edge computing
Intelligence
Internet of Things
Meters
Network latency
Real time
Real-time systems
Smart meters
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Summary:The recent widespread deployment of smart meters on a global scale has created an immense amount of fine-grained smart meter data, which requires effective and real-time analysis. Although the cloud center has powerful data processing capabilities, it is insufficient for real-time analysis, especially in the case of huge and distributed data volumes. Correspondingly, intelligent edge computing is merged with smart meters in this work to create an Internet-of-Things-based architecture for an edge-intelligence-enabled smart meter (EI-smart meter) system. To achieve its potential, we also propose two (one offline and one online) ultra-low-latency cloud-edge collaboration schemes regarding real-time data analytics. Unlike the existing work, we integrate a deep neural network (DNN) into the cloud-edge collaboration scheme in a bid to reduce execution time and improve the adaptability. Finally, numerical results are presented to validate the performance of our proposed system.
ISSN:0890-8044
1558-156X
DOI:10.1109/MNET.011.2000039