Peer-to-Peer Networking and Applications

, Volume 3, Issue 1, pp 17–26 | Cite as

User selfishness vs. file availability in P2P file-sharing systems: Evolutionary game theoretic approach



In a Peer-to-Peer (P2P) file-sharing system, a node finds and retrieves its desired file. If multiple nodes cache the same file to provide others, we can achieve a dependable file-sharing system with low latency and high file availability. However, a node has to spend costs, e.g., processing load or storage capacity, on caching a file. Consequently, a node may selfishly behave and hesitate to cache a file. In such a case, unpopular files are likely to disappear from the system. In this paper, we aim to reveal whether effective caching in the whole system emerges from autonomous and selfish node behavior. We discuss relationship between selfish node behavior and system dynamics by using evolutionary game theory. Through theoretic analysis, we show that a file-sharing system can be robust to file disappearance depending on a cost and demand model for caching even if nodes behave selfishly. Furthermore, we also conduct several simulation-based analysis in terms of network structures, evolving network, load balancing, and system stability. As a result, we demonstrate that a file-sharing system with good properties, i.e., robustness to file disappearance, low search latency, well load-balancing, and high stability, can be achieved independent of network structures and dynamics.


Peer-to-Peer (P2P) file-sharing system Evolutionary game theory Selfish node behavior 


  1. 1.
    Sasabe M, Wakamiya N, Murata M (2007) A caching algorithm using evolutionary game theory in a file-sharing system. In: Proceedings of IEEE symposium on computers and communications (ISCC’07). IEEE, Piscataway, pp 631–636CrossRefGoogle Scholar
  2. 2.
    Gummadi KP, Dunn RJ, Saroiu S, Gribble SD, Levy HM, Zahorjan J (2003) Measurement, modeling, and analysis of a peer-to-peer file-sharing workload. In: Proceedings of SOSP 2003. ACM, New York, pp 314–329CrossRefGoogle Scholar
  3. 3.
    Rowstron A, Druschel P (2001) Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility. In: Proceedings of SOSP 2001. ACM, New York, pp 188–201CrossRefGoogle Scholar
  4. 4.
    Adar E, Huberman BA (2000) Free riding on Gnutella. Technical Report Xerox PARCGoogle Scholar
  5. 5.
    Chun BG, Chaudhuri K, Wee H, Barreno M, Papadimitriou CH, Kubiatowicz J (2004) Selfish caching in distributed systems: a game-theoretic analysis. In: Proceedings of the twenty-thrid annual ACM symposium on principles of distributed computing (PODC’04). Aveiro, pp 21–30Google Scholar
  6. 6.
    Ranganathan K, Ripeanu M, Sarin A, Foster I (2004) Incentive mechanisms for large collaborative resource sharing. In: Proceedings of the 2004 IEEE international symposium on cluster computing and the grid (CCGRID’04). IEEE, Washington, DC, pp 1–8Google Scholar
  7. 7.
    Yu-Kwong Ricky Kwok VKNL (2007) Wireless internet and mobile computing. Wiley, New YorkGoogle Scholar
  8. 8.
    Freenet (2009) Freenet homepage.
  9. 9.
    Fu F, Liu L, Wang L (2007) Evolutionary prisoner’s dilemma on heterogeneous newman-watts small-world network. Eur Phys J, B-Cond Matter Complex Syst 56(4):367–372CrossRefGoogle Scholar
  10. 10.
    Hales D, Arteconi S (2006) SLACER: a self-organizing protocol for coordination in peer-to-peer networks. IEEE Intell Syst 21(2):29–35. doi:10.1109/MIS.2006.35 CrossRefGoogle Scholar
  11. 11.
    Ohtsuki H, Nowak M (2008) Evolutionary stability on graphs. J Theor Biol 251(4):698–707CrossRefMathSciNetGoogle Scholar
  12. 12.
    Santos F, Pacheco J, Lenaerts T (2006) Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proc Natl Acad Sci 103(9):3490–3494CrossRefGoogle Scholar
  13. 13.
    Weibull JW (1997) Evolutionary game theory. MIT, CambridgeGoogle Scholar
  14. 14.
    Pacheco JM, Santos FC (2004) Network dependence of the dilemmas of cooperation. In: Proceedings of CNET 2004. Aveiro, pp 90–100Google Scholar
  15. 15.
    Santos FC, Pacheco JM (2006) A new route to the evolution of cooperation. J Evol Biol 19(3):726–733CrossRefGoogle Scholar
  16. 16.
    Hauert C, Doebeli M (2004) Spatial structure often inhibits the evolution of cooperation in the snowdrift game. Nature 428:611–612CrossRefGoogle Scholar
  17. 17.
    Gyorgy S, Gabor F (2007) Evolutionary games on graphs. Phys Rep 446:97–216CrossRefMathSciNetGoogle Scholar
  18. 18.
    Wilensky U (1999) NetLogo.
  19. 19.
    Medina A, Lakhina A, Matta I, Byers J (2001) BRITE: an approach to universal topology generation. In: Proceedings of the ninth international symposium in modeling, analysis and simulation of computer and telecommunication systems (MASCOTS’01). IEEE Computer Society, Washington, DC, pp 346–354CrossRefGoogle Scholar
  20. 20.
    Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512CrossRefMathSciNetGoogle Scholar
  21. 21.
    Waxman BM (1988) Routing of multipoint connections. IEEE J Sel Areas Commun 6(9):1617–1622CrossRefGoogle Scholar
  22. 22.
    Sarshar N, Boykin O, Roychowdhury V (2006) Scalable percolation search on complex networks. Theor Comp Sci 355(1):48–64MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science + Business Media, LLC 2009

Authors and Affiliations

  • Masahiro Sasabe
    • 1
  • Naoki Wakamiya
    • 2
  • Masayuki Murata
    • 2
  1. 1.Graduate School of EngineeringOsaka UniversitySuita-shiJapan
  2. 2.Graduate School of Information Science and TechnologyOsaka UniversitySuita-shiJapan

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