MobiEdge: Mobile Service Provisioning for Edge Clouds with Time-varying Service Demands

Wu, T; Fan, X; Qu, Y; Yang, P

MobiEdge: Mobile Service Provisioning for Edge Clouds with Time-varying Service Demands

Wu, T Fan, X

Qu, Y Yang, P

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, 2022, 2021-December, pp. 490-497
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Wu, T
dc.contributor.author	Fan, X https://orcid.org/0000-0001-8945-3046
dc.contributor.author	Qu, Y
dc.contributor.author	Yang, P
dc.date	2021-12-14
dc.date.accessioned	2023-04-11T00:01:26Z
dc.date.available	2023-04-11T00:01:26Z
dc.date.issued	2022-01-01
dc.identifier.citation	Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, 2022, 2021-December, pp. 490-497
dc.identifier.isbn	9781665408783
dc.identifier.issn	1521-9097
dc.identifier.uri	http://hdl.handle.net/10453/169457
dc.description.abstract	With the proliferation of mobile and Internet of Things (IoT) devices, there has been an unprecedented growth of data consumption and computation requests at the network edge. To support latency-sensitive and resource-intensive mobile services, cellular base stations can be integrated with Mobile Edge Computing (MEC) technologies for service provisioning. MEC prompts flexible and configurable provisions of applications or services to make more efficient responses to mobile users' demands. Nevertheless, the time-varying nature of service demands inevitably becomes a vital challenge for existing service provisioning solutions. In this work, we propose MobiEdge, a multi-frame service provisioning scheme across two distinct timescales for MEC networks under various constraints of computation, communication and storage resources. We show that the large timescale indicated by 'frame' is more suitable for adjusting edge server activation and service placement, while the small timescale indicated by 'time slot' is more feasible to schedule users' requests. By leveraging the submodular techniques, we formulate a joint optimization problem and further propose an approximation algorithm with theoretical analysis and proofs. Synthetic and trace-driven evaluation results validate that MobiEdge can benefit both service providers and mobile users in MEC with high profits (e.g., 94% of the optimal) and a relatively low complexity.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS
dc.relation.ispartof	Proceedings of the International Conference on Parallel and Distributed Systems
dc.relation.isbasedon	10.1109/ICPADS53394.2021.00067
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	MobiEdge: Mobile Service Provisioning for Edge Clouds with Time-varying Service Demands
dc.type	Conference Proceeding
utslib.citation.volume	2021-December
utslib.location.activity	Beijing, China
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-04-11T00:01:25Z
pubs.finish-date	2021-12-16
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2021-12-14
pubs.volume	2021-December
dc.location	Piscataway, USA

Abstract:

With the proliferation of mobile and Internet of Things (IoT) devices, there has been an unprecedented growth of data consumption and computation requests at the network edge. To support latency-sensitive and resource-intensive mobile services, cellular base stations can be integrated with Mobile Edge Computing (MEC) technologies for service provisioning. MEC prompts flexible and configurable provisions of applications or services to make more efficient responses to mobile users' demands. Nevertheless, the time-varying nature of service demands inevitably becomes a vital challenge for existing service provisioning solutions. In this work, we propose MobiEdge, a multi-frame service provisioning scheme across two distinct timescales for MEC networks under various constraints of computation, communication and storage resources. We show that the large timescale indicated by 'frame' is more suitable for adjusting edge server activation and service placement, while the small timescale indicated by 'time slot' is more feasible to schedule users' requests. By leveraging the submodular techniques, we formulate a joint optimization problem and further propose an approximation algorithm with theoretical analysis and proofs. Synthetic and trace-driven evaluation results validate that MobiEdge can benefit both service providers and mobile users in MEC with high profits (e.g., 94% of the optimal) and a relatively low complexity.

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http://hdl.handle.net/10453/169457