Peer-to-Peer (P2P) file sharing is one of key technologies for achieving attractive P2P multimedia social networking. In P2P file-sharing systems, file availability is improved by cooperative users who cache and share files. Note that file caching carries costs such as storage consumption and processing load. In addition, users have different degrees of cooperativity in file caching and they are in different surrounding environments arising from the topological structure of P2P networks. With evolutionary game theory, this paper evaluates the performance of P2P file sharing systems in such heterogeneous environments. Using micro-macro dynamics, we analyze the impact of the heterogeneity of user selfishness on the file availability and system stability. Further, through simulation experiments with agent-based dynamics, we reveal how other aspects, for example, synchronization among nodes and topological structure, affect the system performance. Both analytical and simulation results show that the environmental heterogeneity contributes to the file availability and system stability. 1. Introduction File sharing is one of key technologies for achieving attractive multimedia social networking. Each user treasures multimedia contents, for example, video and music, in his/her own terminal and they are shared with other users. Since the number of users continues to increase and user terminals become more heterogeneous with the development of mobile technologies, it is desirable to achieve file sharing in a form of peer-to-peer (P2P) systems, which are self-organized and scalable without any specific infrastructure. To realize effective P2P file-sharing, two key issues should be considered: User selfishness and heterogeneity. Since each node participating in the system is a user's terminal, it is controlled by the user. In general, each user is selfish and hesitates to actively share files due to costs for file caching, such as storage consumption, processing load, and bandwidth consumption [1]. On the other hand, the heterogeneity of user environments can be classified into self environments and surrounding environments. Each user potentially has a cooperative degree in file caching, depending on its terminal performance, access link capacity, and sense of value to the file, a On the other hand, the surrounding environment is represented as the connectivity relationship between nodes, which is determined by the topological structure of P2P networks. Each user has to determine its behavior so as to maximize its own benefit, taking account of the behavior of its
References
[1]
E. Adar and B. A. Huberman, “Free riding on Gnutella,” Tech. Rep., Xerox PARC, Palo Alto, Calif, USA, 2000.
[2]
J. W. Weibull, Evolutionary Game Theory, MIT Press, Cambridge, Mass, USA, 1997.
[3]
S. Iwanaga and A. Namatame, “The Compexity of Collective Decision,” Journal of Nonlinear Dynamics and Control, vol. 6, no. 2, pp. 137–158, 2002.
[4]
G. Szabó and G. Fáth, “Evolutionary games on graphs,” Physics Reports, vol. 446, no. 4–6, pp. 97–216, 2007.
S. Saroiu, P. K. Gummadi, and S. D. Gribble, “A measurement study of peer-to-peer file sharing systems,” in Proceedings of the Multimedia Computing and Networking (MMCN '02), pp. 156–170, San Jose, Calif, USA, January 2002.
[10]
K. P. Gummadi, R. J. Dunn, S. Saroiu, S. D. Gribble, H. M. Levy, and J. Zahorjan, “Measurement, modeling, and analysis of a peer-to-peer file-sharing workload,” in Proceedigs of the ACM Symposium on Operating Systems Principles (SOSP '03), pp. 314–329, New York, NY, USA, 2003.
[11]
J. Pouwelse, P. Garbacki, D. Epema, and H. Sips, “The Bittorrent P2P file-sharing system: measurements and analysis,” in Proceedings of the 4th International Workshop on Peer-to-Peer Systems (IPTPS '05), vol. 3640 of Lecture Notes in Computer Science, pp. 205–216, Springer, New York, NY, USA, February 2005.
[12]
D. Hughes, G. Coulson, and J. Walkerdine, “Free riding on Gnutella revisited: the bell tolls?” IEEE Distributed Systems Online, vol. 6, no. 6, 2005.
[13]
B.-G. Chun, K. Chaudhuri, H. Wee, M. Barreno, C. H. Papadimitriou, and J. Kubiatowicz, “Selfish caching in distributed systems: a game-theoretic analysis,” in Proceedings of the 23rd Annual ACM Symposium on Principles of Distributed Computing (PODC '04), pp. 21–30, St. John's, Canada, July 2004.
[14]
K. Ranganathan, M. Ripeanu, A. Sarin, and I. Foster, “Incentive mechanisms for large collaborative resource sharing,” in Proceedings of IEEE International Symposium on Cluster Computing and the Grid (CCGRID '04), pp. 1–8, Washington, DC, USA, 2004.
[15]
Freenet, http://freenetproject.org/index.html.
[16]
F. Fu, L.-H. Liu, and L. Wang, “Evolutionary Prisoner's Dilemma on heterogeneous Newman-Watts small-world network,” European Physical Journal B, vol. 56, no. 4, pp. 367–372, 2007.
[17]
H. Ohtsuki and M. A. Nowak, “Evolutionary stability on graphs,” Journal of Theoretical Biology, vol. 251, no. 4, pp. 698–707, 2008.
[18]
F. C. Santos, J. M. Pacheco, and T. Lenaerts, “Evolutionary dynamics of social dilemmas in structured heterogeneous populations,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 9, pp. 3490–3494, 2006.
[19]
D. Hales and S. Arteconi, “SLACER: a self-organizing protocol for coordination in peer-to-peer networks,” IEEE Intelligent Systems, vol. 21, no. 2, pp. 29–35, 2006.
[20]
M. Sasabe, N. Wakamiya, and M. Murata, “User selfishness vs. file availability in P2P file-sharing systems: evolutionary game theoretic approach,” Peer to Peer Networking and Applications, 2009, http://www.springerlink.com/content/n5gv715v18834lj2/.
[21]
D. Hales and S. Arteconi, “Motifs in evolving cooperative networks look like protein structure networks,” Networks and Heterogeneous Media, vol. 3, no. 2, pp. 239–249, 2008.
[22]
B. M. Waxman, “Routing of multipoint connections,” IEEE Journal on Selected Areas in Communications, vol. 6, no. 9, pp. 1617–1622, 1988.
[23]
A.-L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science, vol. 286, no. 5439, pp. 509–512, 1999.
[24]
C. T. Kelley, “Solving nonlinear equations with Newton's method,” in Fundamentals of Algorithms, SIAM, Philadelphia, Pa, USA, 2003.
[25]
S. N. Elaydi, An Introduction to Difference Equations, Springer, New York, NY, USA, 2nd edition, 1991.
[26]
U. Wilensky, NetLogo, 1999, http://ccl.northwestern.edu/netlogo.
[27]
A. Medina, A. Lakhina, I. Matta, and J. Byers, “BRITE: an approach to universal topology generation,” in Proceedings of the 9th IEEE International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS '01), pp. 346–353, Washington, DC, USA, 2001.
