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Let's share: a game-theoretic framework for resource sharing in mobile edge clouds

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Title: Let's share: a game-theoretic framework for resource sharing in mobile edge clouds
Authors: Zafari, F
Leung, KK
Towsley, D
Basu, P
Swami, A
Li, J
Item Type: Journal Article
Abstract: Mobile edge computing seeks to provide resources to different delay-sensitive applications. This is a challenging problem as an edge cloud-service provider may not have sufficient resources to satisfy all resource requests. Furthermore, allocating available resources optimally to different applications is also challenging. Resource sharing among different edge cloud-service providers can address the aforementioned limitation as certain service providers may have resources available that can be “rented” by other service providers. However, edge cloud service providers can have different objectives or utilities . Therefore, there is a need for an efficient and effective mechanism to share resources among service providers, while considering the different objectives of various providers. We model resource sharing as a multi-objective optimization problem and present a solution framework based on Cooperative Game Theory (CGT). We consider the strategy where each service provider allocates resources to its native applications first and shares the remaining resources with applications from other service providers. We prove that for a monotonic, non-decreasing utility function, the game is canonical and convex. Hence, the core is not empty and the grand coalition is stable. We propose two algorithms, Game-theoretic Pareto optimal allocation (GPOA) and Polyandrous-Polygamous Matching based Pareto Optimal Allocation (PPMPOA) that provide allocations from the core. Hence the obtained allocations are Pareto optimal and the grand coalition of all the service providers is stable. Experimental results confirm that our proposed resource sharing framework improves utilities of edge cloud-service providers and application request satisfaction.
Issue Date: 1-Jun-2021
Date of Acceptance: 2-Dec-2020
URI: http://hdl.handle.net/10044/1/90278
DOI: 10.1109/TNSM.2020.3044870
ISSN: 1932-4537
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 2107
End Page: 2122
Journal / Book Title: IEEE Transactions on Network and Service Management
Volume: 18
Issue: 2
Copyright Statement: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: IBM United Kingdom Ltd
Funder's Grant Number: PO 4603 458 249
Keywords: Science & Technology
Technology
Computer Science, Information Systems
Computer Science
Games
Resource management
Optimization
Cloud computing
Pareto optimization
Game theory
Linear programming
Cooperative game theory
core
edge cloud
resource allocation
OPTIMIZATION
ALLOCATION
NETWORKS
Science & Technology
Technology
Computer Science, Information Systems
Computer Science
Games
Resource management
Optimization
Cloud computing
Pareto optimization
Game theory
Linear programming
Cooperative game theory
core
edge cloud
resource allocation
OPTIMIZATION
ALLOCATION
NETWORKS
cs.NI
cs.NI
cs.DC
cs.MA
Networking & Telecommunications
0805 Distributed Computing
0906 Electrical and Electronic Engineering
1005 Communications Technologies
Publication Status: Published
Online Publication Date: 2020-12-15
Appears in Collections:Computing
Electrical and Electronic Engineering