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Optimal Offloading Strategies for Edge-Computing via Mean-Field Games and Control

Cui, Kai ; Yilmaz, Mustafa Burak ; Tahir, Anam ; Klein, Anja ; Koeppl, Heinz (2024)
Optimal Offloading Strategies for Edge-Computing via Mean-Field Games and Control.
GLOBECOM 2022 - 2022 IEEE Global Communications Conference. Rio de Janeiro, Brazil (04.12.2022-08.12.2022)
doi: 10.26083/tuprints-00028855
Conference or Workshop Item, Secondary publication, Postprint

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Optimal Offloading Strategies for Edge-Computing via Mean-Field Games and Control
Language: English
Date: 17 December 2024
Place of Publication: Darmstadt
Year of primary publication: 2022
Place of primary publication: Piscataway, NJ
Publisher: IEEE
Book Title: GLOBECOM 2022 - 2022 IEEE Global Communications Conference
Event Title: GLOBECOM 2022 - 2022 IEEE Global Communications Conference
Event Location: Rio de Janeiro, Brazil
Event Dates: 04.12.2022-08.12.2022
DOI: 10.26083/tuprints-00028855
Corresponding Links:
Origin: Secondary publication service
Abstract:

The optimal offloading of tasks in heterogeneous edge-computing scenarios is of great practical interest, both in the selfish and fully cooperative setting. In practice, such systems are typically very large, rendering exact solutions in terms of cooperative optima or Nash equilibria intractable. For this purpose, we adopt a general mean-field formulation in order to solve the competitive and cooperative offloading problems in the limit of infinitely large systems. We give theoretical guarantees for the approximation properties of the limiting solution and solve the resulting mean-field problems numerically. Furthermore, we verify our solutions numerically and find that our approximations are accurate for systems with dozens of edge devices. As a result, we obtain a tractable approach to the design of offloading strategies in large edge-computing scenarios with many users.

Status: Postprint
URN: urn:nbn:de:tuda-tuprints-288553
Classification DDC: 000 Generalities, computers, information > 004 Computer science
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Communications Engineering
18 Department of Electrical Engineering and Information Technology > Self-Organizing Systems Lab
Date Deposited: 17 Dec 2024 09:50
Last Modified: 17 Dec 2024 09:51
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/28855
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