Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
article

Coordination of cooperation policies in a peer-to-peer system using swarm-based RL

Published: 01 March 2012 Publication History
  • Get Citation Alerts
  • Abstract

    The performance of a system of interacting peers depends strongly on their individual resource contributions. In this paper, we have devised a self-organized coordination mechanism for cooperation policy setting of rational peers that have only partial views of the whole peer-to-peer system in order to improve the overall welfare of the system. The proposed mechanism is based on a distributed Reinforcement Learning (RL) approach and sets cooperation policies of the peers through their self-organized interactions by exchanging the local value functions among the neighbors. We demonstrate that a Pareto optimal equilibrium emerges in the system from fair cooperation of the constituent peers.

    References

    [1]
    Cooperation through self-similar social networks. ACM Transactions on Autonomous and Adaptive Systems (TAAS). v5 i1.
    [2]
    Comparing economic incentives in peer-to-peer networks. Computer Networks. v46 i1. 113-146.
    [3]
    Incentives for content availability in memory-less peer-to-peer file sharing systems. ACM SIG on Ecommerce. v5 i4. 11-20.
    [4]
    The complexity of decentralized control of Markov decision processes. Mathematics of Operations Research. v27 i4. 819-840.
    [5]
    Buragohain C, Agrawal D, Suri S. A game theoretic framework for incentives in p2p systems, in: Proceedings of international conference on peer-to-peer computing, Sweden; 2003. p. 48-56.
    [6]
    A comprehensive survey of multiagent reinforcement learning. IEEE Transactions on Systems, Man, and Cybernetics-PART C: Applications and Reviews. v38 i2.
    [7]
    Overcoming free-riding behavior in peer-to-peer systems. ACM SIGecom Exchanges. v5 i4. 41-50.
    [8]
    Feldman M, Lai K, Stoica I, Chuang J. Robust incentive techniques for peer-to-peer networks, in: Proceedings of ACM conference on electronic commerce, NY, USA; 2004. p. 102-11.
    [9]
    Service differentiated peer selection: an incentive mechanism for peer-to-peer media streaming. IEEE Transactions on Multimedia. v8 i3. 610-621.
    [10]
    The science of self-organization and adaptivity. In: Knowledge management, organizational intelligence and learning, and complexity. The encyclopedia of life support systems, EOLSS Publishers.
    [11]
    Kennedy J, Eberhart R. Particle swarm optimization, in: Proceedings of IEEE international conference on neural networks, WA, Australia; 1995. p. 1942-8.
    [12]
    Swarm intelligence. Morgan Kaufmann Academic Press.
    [13]
    Lai K, Feldman M, Stoica I, Chuang J. Incentives for cooperation in peer-to-peer networks, in: Proceedings of the workshop on economics of peer-to-peer systems, CA, USA; 2003.
    [14]
    Incentivized peer-assisted streaming for on-demand services. IEEE Transactions on Parallel and Distributed Systems. v21 i9. 1354-1367.
    [15]
    Liu H, Abraham A, Badr Y. Neighbor selection in peer-to-peer overlay networks: a swarm intelligence approach. Computer Communications and Networks 2010;4:405-31.
    [16]
    Incentive schemes in peer-to-peer networks. Theoretical Economics. v9 i1.
    [17]
    Luther K, Bye R, Alpcan T, Muller A, Albayrak S. A cooperative AIS framework for intrusion detection, in: Proceedings of the international conference on communications, Glasgow; 2007. p. 1409-16.
    [18]
    Incentive and service differentiation in p2p networks: a game theoretic approach. IEEE/ACM Transactions on Networking. v14 i5. 978-991.
    [19]
    Game theory: analysis of conflict. Harvard University Press, Cambridge.
    [20]
    A global contribution approach to maintain fairness in p2p networks. IEEE Transactions on Parallel and Distributed Systems. v21 i6. 812-826.
    [21]
    Cooperative multi-agent learning: the state of the art. Autonomous Agents and Multi-Agent Systems. v11. 387-434.
    [22]
    Coalition-based resource reciprocation strategies for p2p multimedia broadcasting. Transactions on Broadcasting. v54 i3. 557-567.
    [23]
    A framework for foresighted resource reciprocation in p2p networks. IEEE Transactions on Multimedia. v11 i1. 101-116.
    [24]
    The art and science of negotiation. Harvard University Press, Cambridge.
    [25]
    Decision Analysis: Introductory Readings on Choices Under Uncertainty. McGraw Hill.
    [26]
    Ranganathan K. Incentive mechanisms for large collaborative resource sharing, in: Proceedings of IEEE international symposium on cluster computing and the grid, Chicago, IL, USA; 2004. p. 1-8.
    [27]
    A self-adaptive ant colony system for semantic query routing problem in p2p networks. Computación y Sistemas. v13 i4. 433-448.
    [28]
    Reputation-based resource allocation in p2p systems of rational users. IEEE Transactions on Parallel and Distributed Systems. v21 i4. 466-479.
    [29]
    Robust and efficient incentives for cooperative content distribution. IEEE/ACM Transactions on Networking. v17 i6. 1766-1779.
    [30]
    Reinforcement learning: an introduction. MIT Press.
    [31]
    A payment-based incentive and service differentiation scheme for peer-to-peer streaming broadcast. IEEE Transactions on Parallel and Distributed Systems. v19 i7. 940-953.
    [32]
    Stochastic optimization for content sharing in p2p systems. IEEE Transactions on Multimedia. v10 i1. 132-144.
    [33]
    Performance of peer-to-peer networks-service capacity and role of resource sharing policies. Performance Evaluation in P2P Computing Systems. v63 i3. 175-194.

    Cited By

    View all
    • (2023)Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature ReviewACM Computing Surveys10.1145/357858155:14s(1-69)Online publication date: 24-Jan-2023
    • (2016)Game theoretic bandwidth procurement mechanisms in live P2P streaming systemsMultimedia Tools and Applications10.1007/s11042-015-2771-675:14(8545-8568)Online publication date: 1-Jul-2016

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image Journal of Network and Computer Applications
    Journal of Network and Computer Applications  Volume 35, Issue 2
    March, 2012
    349 pages

    Publisher

    Academic Press Ltd.

    United Kingdom

    Publication History

    Published: 01 March 2012

    Author Tags

    1. Distributed decision making
    2. Pareto optimality
    3. Particle swarm optimization
    4. Q-learning
    5. Rational peers

    Qualifiers

    • Article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 28 Jul 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2023)Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature ReviewACM Computing Surveys10.1145/357858155:14s(1-69)Online publication date: 24-Jan-2023
    • (2016)Game theoretic bandwidth procurement mechanisms in live P2P streaming systemsMultimedia Tools and Applications10.1007/s11042-015-2771-675:14(8545-8568)Online publication date: 1-Jul-2016

    View Options

    View options

    Get Access

    Login options

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media