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Cloud-Fog Automation: Vision, Enabling Technologies, and Future Research Directions
Swinburne University of Technology, School of Science, Computing and Engineering Technologies, Hawthorn, VIC, Australia.ORCID iD: 0000-0002-0306-2691
La Trobe University, Department of Computer Science and Information Technology, Bundoora, VIC, Australia.ORCID iD: 0000-0002-6777-8197
Deakin University, School of Information Technology, Geelong, VIC, Australia.ORCID iD: 0000-0001-9699-9418
University of Windsor, Department of Electrical and Computer Engineering, Windsor, ON, Canada.ORCID iD: 0000-0002-8781-4925
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2024 (English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 20, no 2, p. 1039-1054Article in journal (Refereed) Published
Abstract [en]

The Industry 4.0 digital transformation envisages future industrial systems to be fully automated, including the control, upgrade, and configuration processes of a large number of heterogeneous wired/wireless interconnected devices in Industrial Internet of Things environments. Most of the industrial automation systems today are based on the traditional International Society of Automation (ISA)-95 model, with some recently transitioned to Cloud Automation systems. Latest developments in network connectivity technologies, artificial intelligence, and Cloud/Fog computing technologies have motivated us to rethink the ISA-95 model. In this article, we propose a vision that aims to migrate most of the computational and automation tasks closer to the ground, which we term the collaborative 'Cloud-Fog Automation' paradigm. We perform a comprehensive survey of the state-of-the-art and formulate the three pillars of this vision: Deterministic connectivity, deterministic connected intelligence, and deterministic networked computing. In each of these pillars, we review their latency and reliability, security, and functional safety requirements and challenges. Finally, we articulate and highlight key future research directions to realize this vision.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. Vol. 20, no 2, p. 1039-1054
Keywords [en]
Artificial intelligence, automation, cloud, Fog, Industrial Internet of Things (IIoT), Industry 4.0
National Category
Computer Sciences Communication Systems Computer Systems Computer Engineering
Identifiers
URN: urn:nbn:se:kth:diva-367144DOI: 10.1109/TII.2023.3272696ISI: 001129667400003Scopus ID: 2-s2.0-85159836332OAI: oai:DiVA.org:kth-367144DiVA, id: diva2:1984237
Note

QC 20250715

Available from: 2025-07-15 Created: 2025-07-15 Last updated: 2025-07-15Bibliographically approved

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Pang, Zhibo

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