New Game-Theoretic Approach to Decentralized Path Selection and Sleep Scheduling for Mobile Edge Computing

Wu, B; Zeng, J; Shao, S; Ni, W; Tang, Y

New Game-Theoretic Approach to Decentralized Path Selection and Sleep Scheduling for Mobile Edge Computing

Wu, B Zeng, J Shao, S Ni, W

Tang, Y

Permalink

Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Wireless Communications, 2022, 21, (8), pp. 6125-6140
Issue Date:: 2022-08-01

Closed Access

	Filename	Description	Size
	New_Game-Theoretic_Approach_to_Decentralized_Path_Selection_and_Sleep_Scheduling_for_Mobile_Edge_Computing.pdf	Published version	19.25 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Wu, B
dc.contributor.author	Zeng, J
dc.contributor.author	Shao, S
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Tang, Y
dc.date.accessioned	2023-04-12T22:34:25Z
dc.date.available	2023-04-12T22:34:25Z
dc.date.issued	2022-08-01
dc.identifier.citation	IEEE Transactions on Wireless Communications, 2022, 21, (8), pp. 6125-6140
dc.identifier.issn	1536-1276
dc.identifier.issn	1558-2248
dc.identifier.uri	http://hdl.handle.net/10453/169663
dc.description.abstract	Network function virtualization (NFV) implements mobile edge computing (MEC) services as software appliances, and allows resources to be adaptively allocated to accommodate demand variations. Scalability and network cost (including operational cost and response latency) are key challenges. This paper presents a new game-theoretic approach to minimizing the network cost, where access points (APs) select MEC servers and routes in a decentralized manner, and unloaded routers and links are deactivated for cost saving. The key idea is that we interpret the minimization of network cost as a mixed game with a non-monotonic cost function capturing both the operational cost and response latency. We prove that the game is conditionally an ordinary potential game and converges to α-approximate equilibriums. A closed-form expression is derived for the convergence delay. Another important aspect is that we integrate Stackelberg routing into the proposed mixed game to avoid inefficient equilibriums (with high cost or latency). We prove that the mixed game can converge faster to better equilibriums under linear response latency models. Extensive simulations corroborate the new game-theoretic approach can significantly outperform existing techniques in terms of efficiency, convergence, and scalability.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Transactions on Wireless Communications
dc.relation.isbasedon	10.1109/TWC.2022.3146514
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.title	New Game-Theoretic Approach to Decentralized Path Selection and Sleep Scheduling for Mobile Edge Computing
dc.type	Journal Article
utslib.citation.volume	21
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2023-04-12T22:34:22Z
pubs.issue	8
pubs.publication-status	Published
pubs.volume	21
utslib.citation.issue	8

Abstract:

Network function virtualization (NFV) implements mobile edge computing (MEC) services as software appliances, and allows resources to be adaptively allocated to accommodate demand variations. Scalability and network cost (including operational cost and response latency) are key challenges. This paper presents a new game-theoretic approach to minimizing the network cost, where access points (APs) select MEC servers and routes in a decentralized manner, and unloaded routers and links are deactivated for cost saving. The key idea is that we interpret the minimization of network cost as a mixed game with a non-monotonic cost function capturing both the operational cost and response latency. We prove that the game is conditionally an ordinary potential game and converges to α-approximate equilibriums. A closed-form expression is derived for the convergence delay. Another important aspect is that we integrate Stackelberg routing into the proposed mixed game to avoid inefficient equilibriums (with high cost or latency). We prove that the mixed game can converge faster to better equilibriums under linear response latency models. Extensive simulations corroborate the new game-theoretic approach can significantly outperform existing techniques in terms of efficiency, convergence, and scalability.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/169663