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Game theory and Lyapunov optimization for cloud-based content delivery networks with Device-to-Device and UAV-enabled caching

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posted on 2024-10-09, 15:26 authored by Alia AsheralievaAlia Asheralieva, Dusit Niyato
The paper considers a cloud-based Content Delivery Network (CDN) with Device-to-Device (D2D) and Unmanned Aerial Vehicle (UAV) enabled caching. The network is managed by the operator that offers content transfer services to the set of Content Providers (CPs). A subscriber of any CP can receive its content either by first, cellular content transfer via a terrestrial Base Station (BS) or a UAV, or by second, D2D content transfer from another subscriber of this CP. Each CP aims to maximize its expected payoff defined as a reciprocal of the weighted sum of the expected content transfer cost and delay for its subscribers. The operator's objective is to maximize its long-term average revenue and stabilize the queuing system which represents the content transfer services. To model the interactions between the operator and the CPs, a novel framework is proposed that combines: first, cooperative game that enables the CPs to form coalitions in which all subscribers can exchange content via D2D links, thereby reducing content transfer costs and delays; second, Lyapunov optimization based dynamic channel and UAVs' activity allocation policy of the operator. Through analytical and numerical evaluations, it is proven that if the operator and each CP are rational, the network reaches a state where all the CPs are in the stable coalitional structure, whereas, the dynamic policy of the operator is optimal with the trade-off in the total queue backlog.

Funding

A*STAR-NTU-SUTD Joint Research Grant Call on Artificial Intelligence for the Future of Manufacturing RGANS1906

WASP/NTU: grant M4082187 (4080)

Singapore MOE Tier 1: grant 2017-T1-002-007 RG122/17

Singapore MOE Tier 2: grant MOE2014-T2-2-015 ARC4/15

Singapore NRF: grant 2015-NRF-ISF001-2277

Singapore EMA Energy Resilience: grant NRF2017EWT-EP003-041

History

School

  • Science

Department

  • Computer Science

Published in

IEEE Transactions on Vehicular Technology

Volume

68

Issue

10

Pages

10094 - 10110

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2019 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.

Acceptance date

2019-08-05

Publication date

2019-08-08

Copyright date

2019

ISSN

0018-9545

eISSN

1939-9359

Language

  • en

Depositor

Dr Alia Asheralieva. Deposit date: 29 May 2024