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Enabling Technologies for Energy Cloud
Department of Computer Science, College of Computing and Informatics, University of Sharjah, United Arab Emirates.
Beijing Institute of Technology, China.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems. Electrical Engineering Department, Faculty of Engineering, Al-Azhar University at Qena, Qena 83513, Egypt. Centre for Security, Communications and Network Research, University of Plymouth, Plymouth PL4 8AA, United Kingdom.ORCID iD: 0000-0002-3800-0757
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, China.
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2021 (English)In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 152, p. 108-110Article in journal, Editorial material (Other academic) Published
Abstract [en]

We are thrilled and delighted to present this special issue, which emphasises on the novel area of Enabling Technologies for Energy Cloud. This guest editorial provides an overview of all articles accepted for publication in this special issue.
Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 152, p. 108-110
Keywords [en]
Energy cloud, Machine learning, Artificial intelligence, Cybersecurity, Networks security, Cyber-physical systems
National Category
Computer Sciences
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-83266DOI: 10.1016/j.jpdc.2021.02.020ISI: 000637996500011Scopus ID: 2-s2.0-85102631904OAI: oai:DiVA.org:ltu-83266DiVA, id: diva2:1537153
Note

Godkänd;2021;Nivå 0;2021-04-14 (alebob)

Available from: 2021-03-15 Created: 2021-03-15 Last updated: 2021-05-10Bibliographically approved

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Awad, Ali Ismail

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