IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v64y2017i1d10.1007_s11235-016-0161-7.html
   My bibliography  Save this article

A stochastic approximation resource allocation approach for HD live streaming

Author

Listed:
  • Seyedakbar Mostafavi

    (Yazd University)

  • Mehdi Dehghan

    (Amirkabir University of Technology (Tehran Polytechnic))

Abstract

One of the current issues in the peer-to-peer streaming systems is to supply sufficient upload bandwidth for continuous streaming of high-quality video channels. The helpers as upload bandwidth boosters can improve the streaming capacity of system, so that the imbalance of upload bandwidth between different video channel overlays is compensated. With the deployment of helpers as an intermediate level between server and peers, building and maintaining the optimal peer-helper topology becomes a challenging task since the one-directional nature of video streaming from the helpers to users makes the well-known reciprocity-based algorithms useless. Because of selfish behavior of peers and lack of a central authority among them, selection of helpers requires implicit coordination. In this paper, we design a decentralized, stochastic approximation helper selection mechanism which is adaptable to supply and demand pattern of various video channels. Our regret-tracking-based solution for allowing peers to strategically exploit their shared resources is guaranteed to converge to the correlated equilibria (CE) among the helper selection strategies. Online convergence to the set of CE is achieved through the regret-tracking algorithm which tracks the equilibrium in the presence of stochastic dynamics of helpers’ bandwidth. The resulting CE can help to select proper cooperation policies. Simulation results demonstrate that our algorithm achieves good convergence, load distribution on helpers and sustainable streaming rates for peers.

Suggested Citation

  • Seyedakbar Mostafavi & Mehdi Dehghan, 2017. "A stochastic approximation resource allocation approach for HD live streaming," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(1), pages 87-101, January.
    • Handle: RePEc:spr:telsys:v:64:y:2017:i:1:d:10.1007_s11235-016-0161-7
    DOI: 10.1007/s11235-016-0161-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-016-0161-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-016-0161-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aumann, Robert J, 1987. "Correlated Equilibrium as an Expression of Bayesian Rationality," Econometrica, Econometric Society, vol. 55(1), pages 1-18, January.
    2. Milchtaich, Igal, 1996. "Congestion Games with Player-Specific Payoff Functions," Games and Economic Behavior, Elsevier, vol. 13(1), pages 111-124, March.
    3. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shiyong Li & Wei Sun & Huan Liu, 2022. "Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation," Operational Research, Springer, vol. 22(3), pages 2605-2630, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ehud Lehrer & Eilon Solan, 2007. "Learning to play partially-specified equilibrium," Levine's Working Paper Archive 122247000000001436, David K. Levine.
    2. Lenzo, Justin & Sarver, Todd, 2006. "Correlated equilibrium in evolutionary models with subpopulations," Games and Economic Behavior, Elsevier, vol. 56(2), pages 271-284, August.
    3. Fook Wai Kong & Polyxeni-Margarita Kleniati & Berç Rustem, 2012. "Computation of Correlated Equilibrium with Global-Optimal Expected Social Welfare," Journal of Optimization Theory and Applications, Springer, vol. 153(1), pages 237-261, April.
    4. Ozdogan, Ayca & Saglam, Ismail, 2021. "Correlated equilibrium under costly disobedience," Mathematical Social Sciences, Elsevier, vol. 114(C), pages 98-104.
    5. Lars P. Metzger, 2018. "Evolution and correlated equilibrium," Journal of Evolutionary Economics, Springer, vol. 28(2), pages 333-346, April.
    6. Foster, Dean P. & Vohra, Rakesh V., 1997. "Calibrated Learning and Correlated Equilibrium," Games and Economic Behavior, Elsevier, vol. 21(1-2), pages 40-55, October.
    7. Friedman, Daniel & Rabanal, Jean Paul & Rud, Olga A. & Zhao, Shuchen, 2022. "On the empirical relevance of correlated equilibrium," Journal of Economic Theory, Elsevier, vol. 205(C).
    8. Arifovic, Jasmina & Boitnott, Joshua F. & Duffy, John, 2019. "Learning correlated equilibria: An evolutionary approach," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 171-190.
    9. Moulin, Herve & Ray, Indrajit & Sen Gupta, Sonali, 2014. "Improving Nash by coarse correlation," Journal of Economic Theory, Elsevier, vol. 150(C), pages 852-865.
    10. Kets, Willemien & Kager, Wouter & Sandroni, Alvaro, 2022. "The value of a coordination game," Journal of Economic Theory, Elsevier, vol. 201(C).
    11. Rabah Amir & Sergei Belkov & Igor V. Evstigneev, 2017. "Correlated equilibrium in a nutshell," Theory and Decision, Springer, vol. 83(4), pages 457-468, December.
    12. Soham R. Phade & Venkat Anantharam, 2023. "Learning in Games with Cumulative Prospect Theoretic Preferences," Dynamic Games and Applications, Springer, vol. 13(1), pages 265-306, March.
    13. Giraud, Gael & Rochon, Celine, 2002. "Consistent collusion-proofness and correlation in exchange economies," Journal of Mathematical Economics, Elsevier, vol. 38(4), pages 441-463, December.
    14. Alejandro Lee-Penagos, 2016. "Learning to Coordinate: Co-Evolution and Correlated Equilibrium," Discussion Papers 2016-11, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    15. Yuval Heller & Eyal Winter, 2016. "Rule Rationality," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(3), pages 997-1026, August.
    16. Timothy N. Cason & Tridib Sharma & Radovan Vadovic, 2019. "Corelated beliefs: Predicting outcomes in 2X2 games," Purdue University Economics Working Papers 1321, Purdue University, Department of Economics.
    17. Giovanni Di Bartolomeo & Debora Di Gioacchino, 2005. "Fiscal-Monetary Policy Coordination And Debt Management: A Two Stage Dynamic Analysis," Macroeconomics 0504024, University Library of Munich, Germany.
    18. Soham R. Phade & Venkat Anantharam, 2019. "On the Geometry of Nash and Correlated Equilibria with Cumulative Prospect Theoretic Preferences," Decision Analysis, INFORMS, vol. 16(2), pages 142-156, June.
    19. Holly P. Borowski & Jason R. Marden & Jeff S. Shamma, 2019. "Learning to Play Efficient Coarse Correlated Equilibria," Dynamic Games and Applications, Springer, vol. 9(1), pages 24-46, March.
    20. Kam-Chau Wong & Chongmin Kim, 2004. "Evolutionarily Stable Correlation," Econometric Society 2004 Far Eastern Meetings 495, Econometric Society.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:64:y:2017:i:1:d:10.1007_s11235-016-0161-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.