MetaSlicing: A Novel Resource Allocation Framework for Metaverse

Chu, NH; Hoang, DT; Nguyen, DN; Phan, KT; Dutkiewicz, E; Niyato, D; Shu, T

MetaSlicing: A Novel Resource Allocation Framework for Metaverse

Chu, NH Hoang, DT Nguyen, DN Phan, KT Dutkiewicz, E

Niyato, D Shu, T

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Mobile Computing, 2023, PP, (99), pp. 1-18
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Chu, NH
dc.contributor.author	Hoang, DT
dc.contributor.author	Nguyen, DN
dc.contributor.author	Phan, KT
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286
dc.contributor.author	Niyato, D
dc.contributor.author	Shu, T
dc.date.accessioned	2023-11-09T08:45:06Z
dc.date.available	2023-11-09T08:45:06Z
dc.date.issued	2023-01-01
dc.identifier.citation	IEEE Transactions on Mobile Computing, 2023, PP, (99), pp. 1-18
dc.identifier.issn	1536-1233
dc.identifier.issn	1558-0660
dc.identifier.uri	http://hdl.handle.net/10453/173278
dc.description.abstract	Creating and maintaining the Metaverse requires enormous resources that have never been seen before, especially computing resources for intensive data processing to support the Extended Reality, enormous storage resources, and massive networking resources for maintaining ultra high-speed and low-latency connections. Therefore, this work aims to propose a novel framework, namely MetaSlicing, that can provide a highly effective and comprehensive solution in managing and allocating different types of resources for Metaverse applications. In particular, by observing that Metaverse applications may have common functions, we first propose grouping applications into clusters, called MetaInstances. In a MetaInstance, common functions can be shared among applications. As such, the same resources can be used by multiple applications simultaneously, thereby enhancing resource utilization dramatically. To address the real-time characteristic and resource demand's dynamic and uncertainty in the Metaverse, we develop an effective framework based on the semi-Markov decision process and propose an intelligent admission control algorithm that can maximize resource utilization and enhance the Quality-of-Service for end-users. Extensive simulation results show that our proposed solution outperforms the Greedy-based policies by up to 80% and 47% in terms of long-term revenue for Metaverse providers and request acceptance probability, respectively.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Transactions on Mobile Computing
dc.relation.isbasedon	10.1109/TMC.2023.3288085
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4604 Cybersecurity and privacy
dc.subject.classification	4606 Distributed computing and systems software
dc.title	MetaSlicing: A Novel Resource Allocation Framework for Metaverse
dc.type	Journal Article
utslib.citation.volume	PP
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2023-11-09T08:44:53Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	PP
utslib.citation.issue	99

Abstract:

Creating and maintaining the Metaverse requires enormous resources that have never been seen before, especially computing resources for intensive data processing to support the Extended Reality, enormous storage resources, and massive networking resources for maintaining ultra high-speed and low-latency connections. Therefore, this work aims to propose a novel framework, namely MetaSlicing, that can provide a highly effective and comprehensive solution in managing and allocating different types of resources for Metaverse applications. In particular, by observing that Metaverse applications may have common functions, we first propose grouping applications into clusters, called MetaInstances. In a MetaInstance, common functions can be shared among applications. As such, the same resources can be used by multiple applications simultaneously, thereby enhancing resource utilization dramatically. To address the real-time characteristic and resource demand's dynamic and uncertainty in the Metaverse, we develop an effective framework based on the semi-Markov decision process and propose an intelligent admission control algorithm that can maximize resource utilization and enhance the Quality-of-Service for end-users. Extensive simulation results show that our proposed solution outperforms the Greedy-based policies by up to 80% and 47% in terms of long-term revenue for Metaverse providers and request acceptance probability, respectively.

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http://hdl.handle.net/10453/173278