LAPSE:2023.24844
Published Article
LAPSE:2023.24844
Evolving Container to Unikernel for Edge Computing and Applications in Process Industry
March 28, 2023
Industry 4.0 promotes manufacturing and process industry towards digitalization and intellectualization. Edge computing can provide delay-sensitive services in industrial processes to realize intelligent production. Lightweight virtualization technology is one of the key elements of edge computing, which can implement resource management, orchestration, and isolation services without considering heterogenous hardware. It has revolutionized software development and deployment. The scope of this review paper is to present an in-depth analysis of two such technologies, Container and Unikernel, for edge computing. We discuss and compare their applicability in terms of migration, security, and orchestration for edge computing and industrial applications. We describe their performance indexes, evaluation methods and related findings. We then discuss their applications in industrial processes. To promote further research, we present some open issues and challenges to serve as a road map for both researchers and practitioners in the areas of Industry 4.0, industrial process automation, and advanced computing.
Keywords
big data analytics, cloud computing, edge computing, fault diagnosis, industrial process, Industry 4.0, Internet of things, lightweight virtualization, Machine Learning, process industry
Suggested Citation
Chen S, Zhou M. Evolving Container to Unikernel for Edge Computing and Applications in Process Industry. (2023). LAPSE:2023.24844
Author Affiliations
Chen S: The Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems, Macau University of Science and Technology, Macau 999078, China; The State Key Laboratory for Management and Control of Complex Systems, Institute of Au [ORCID]
Zhou M: The Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems, Macau University of Science and Technology, Macau 999078, China; Department of Electrical and Computer Engineering, New Jersey Institute of Technology, [ORCID]
Journal Name
Processes
Volume
9
Issue
2
First Page
351
Year
2021
Publication Date
2021-02-14
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr9020351, Publication Type: Review
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LAPSE:2023.24844
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doi:10.3390/pr9020351
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Mar 28, 2023
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CC BY 4.0
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