Evolving Container to Unikernel for Edge Computing and Applications in Process Industry

Chen, Shichao; Zhou, Mengchu

doi:10.3390/pr9020351

Open AccessFeature PaperReview

Evolving Container to Unikernel for Edge Computing and Applications in Process Industry

by

Shichao Chen

^1,2

and

Mengchu Zhou

^1,3,4,*

¹

The Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems, Macau University of Science and Technology, Macau 999078, China

²

The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

³

Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA

⁴

Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia

^*

Author to whom correspondence should be addressed.

Processes 2021, 9(2), 351; https://doi.org/10.3390/pr9020351

Submission received: 2 February 2021 / Revised: 6 February 2021 / Accepted: 10 February 2021 / Published: 14 February 2021

(This article belongs to the Special Issue Feature Review Papers in Advanced Process Systems Engineering)

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Abstract

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; lightweight virtualization; cloud computing; edge computing; industrial process; Industry 4.0; Internet of things; machine learning; process industry; fault diagnosis

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MDPI and ACS Style

Chen, S.; Zhou, M. Evolving Container to Unikernel for Edge Computing and Applications in Process Industry. Processes 2021, 9, 351. https://doi.org/10.3390/pr9020351

AMA Style

Chen S, Zhou M. Evolving Container to Unikernel for Edge Computing and Applications in Process Industry. Processes. 2021; 9(2):351. https://doi.org/10.3390/pr9020351

Chicago/Turabian Style

Chen, Shichao, and Mengchu Zhou. 2021. "Evolving Container to Unikernel for Edge Computing and Applications in Process Industry" Processes 9, no. 2: 351. https://doi.org/10.3390/pr9020351

APA Style

Chen, S., & Zhou, M. (2021). Evolving Container to Unikernel for Edge Computing and Applications in Process Industry. Processes, 9(2), 351. https://doi.org/10.3390/pr9020351

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Evolving Container to Unikernel for Edge Computing and Applications in Process Industry

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