Machine Learning Empowered Intelligent Data Center Networking

Wang, T; Li, B; Chen, M; Yu, S

Machine Learning Empowered Intelligent Data Center Networking

Wang, T Li, B Chen, M Yu, S

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Publisher:: Springer Nature Singapore
Publication Type:: Chapter
Citation:: SpringerBriefs in Computer Science, 2023, pp. 15-99
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Wang, T
dc.contributor.author	Li, B
dc.contributor.author	Chen, M
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2023-11-13T02:49:24Z
dc.date.available	2023-11-13T02:49:24Z
dc.date.issued	2023-01-01
dc.identifier.citation	SpringerBriefs in Computer Science, 2023, pp. 15-99
dc.identifier.isbn	9789811973949
dc.identifier.uri	http://hdl.handle.net/10453/173369
dc.description.abstract	Machine learning has been widely studied and practiced in data center networks, and a large number of achievements have been made. In this chapter, we will review, compare, and discuss the existing work in the following research areas: flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, network security, and new intelligent networking concepts.
dc.language	en
dc.publisher	Springer Nature Singapore
dc.relation.ispartof	SpringerBriefs in Computer Science
dc.relation.isbasedon	10.1007/978-981-19-7395-6_3
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Machine Learning Empowered Intelligent Data Center Networking
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/DVC (International)/Australia-China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	closed_access	*
dc.date.updated	2023-11-13T02:49:20Z
pubs.publication-status	Published

Abstract:

Machine learning has been widely studied and practiced in data center networks, and a large number of achievements have been made. In this chapter, we will review, compare, and discuss the existing work in the following research areas: flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, network security, and new intelligent networking concepts.

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http://hdl.handle.net/10453/173369