research-article

Incentivizing Sharing in Realtime D2D Streaming Networks: A Mean Field Game Perspective

Authors:

Rajarshi Bhattacharyya,

Srinivas Shakkottai,

Vijay SubramanianAuthors Info & Claims

IEEE/ACM Transactions on Networking (TON), Volume 25, Issue 1

Pages 3 - 17

https://doi.org/10.1109/TNET.2016.2562028

Published: 01 February 2017 Publication History

Abstract

We consider the problem of streaming live content to a cluster of co-located wireless devices that have both an expensive unicast base-station-to-device B2D interface, as well as an inexpensive broadcast device-to-device D2D interface, which can be used simultaneously. Our setting is a streaming system that uses a block-by-block random linear coding approach to achieve a target percentage of on-time deliveries with minimal B2D usage. Our goal is to design an incentive framework that would promote such cooperation across devices, while ensuring good quality of service. Based on the ideas drawn from truth-telling auctions, we design a mechanism that achieves this goal via appropriate transfers monetary payments or rebates in a setting with a large number of devices, and with peer arrivals and departures. Here, we show that a mean field game can be used to accurately approximate our system. Furthermore, the complexity of calculating the best responses under this regime is low. We implement the proposed system on an Android testbed, and illustrate its efficient performance using real world experiments.

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cover image IEEE/ACM Transactions on Networking

IEEE/ACM Transactions on Networking Volume 25, Issue 1

February 2017

636 pages

ISSN:1063-6692

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Copyright © 2017.

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IEEE Press

Publication History

Published: 01 February 2017

Published in TON Volume 25, Issue 1

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Cited By

Wang YYang CLi TMi XLi LHan Z(2024)A Survey on Mean-Field Game for Dynamic Management and Control in Space-Air-Ground NetworkIEEE Communications Surveys & Tutorials10.1109/COMST.2024.339336926:4(2798-2835)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1109/COMST.2024.3393369
Liu XChen XBi QLiang WLi JZhang Z(2023)Blockchain-based distributed operation and incentive solution for P-RANComputer Communications10.1016/j.comcom.2022.11.008198:C(77-84)Online publication date: 15-Jan-2023
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https://dl.acm.org/doi/10.1155/2022/2238643
Narasimha DShakkottai SYing L(2019)A Mean Field Game Analysis of Distributed MAC in Ultra-Dense Multichannel Wireless NetworksProceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing10.1145/3323679.3326498(1-10)Online publication date: 2-Jul-2019
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Li JXia BGeng XMing HShakkottai SSubramanian VXie L(2018)Mean Field Games in Nudge Systems for Societal NetworksACM Transactions on Modeling and Performance Evaluation of Computing Systems10.1145/32320763:4(1-31)Online publication date: 31-Aug-2018
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Fu XWang JQi QLiao JLi T(2018)Incentive Mechanisms for Resource Scaling-out Game of Stream Big Data AnalyticsJournal of Grid Computing10.1007/s10723-018-9458-y16:4(569-585)Online publication date: 1-Dec-2018
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Huang JHuang SXing CGrygiel KCerny TKim SWang W(2017)When D2D Meets Network CodingProceedings of the International Conference on Research in Adaptive and Convergent Systems10.1145/3129676.3129689(146-151)Online publication date: 20-Sep-2017
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Cao JPang YLi X(2017)Learning Multilayer Channel Features for Pedestrian DetectionIEEE Transactions on Image Processing10.1109/TIP.2017.269422426:7(3210-3220)Online publication date: 1-Jul-2017
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Yang CZhang YLi JHan Z(2017)Power Control Mean Field Game with Dominator in Ultra-Dense Small Cell NetworksGLOBECOM 2017 - 2017 IEEE Global Communications Conference10.1109/GLOCOM.2017.8254552(1-6)Online publication date: 4-Dec-2017
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