Self-Organization Approach of Communities for P2P Networks

  • Kazuhiro Kojima
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3144)


Locating contents is an essential function, but it presents a very difficult and challenging problem for large-scale Peer-to-Peer (P2P) systems. Many P2P systems, protocols, architectures, and search strategies are proposed for this problem. In this paper, we focus on the self-organization of a community structure based on user preferences for P2P systems. We propose these methods to improve P2P search performance: 1) Extended Pong, 2) Pong Proxy, 3) QRP with Firework 4) Backward Learning, and 5) Community Self-Organization Algorithm. We evaluate the performance of the self-organized community network through simulations. These results show that the self-organized community network maintains a high query hit rate without overflow.


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  1. 1.
  2. 2.
    Clarke, I., Sandberg, O., Wiley, B., Hong, T.W.: Freenet: A distributed anonymous information storage and retrieval system. In: Proc. the OCSI Workshop on Design Issues in Anonymity and Unobservability (2000)Google Scholar
  3. 3.
    Milgram, S.: The Small-World Problem. Psychology Today 1, 60–67 (1967)Google Scholar
  4. 4.
    Bloom, B.: Space/time trade-offs in hash coding with allowable errors. Communications of the ACM 13(7), 422–426 (1970)zbMATHCrossRefGoogle Scholar
  5. 5.
    Mitzenmacher, M.: Compressed Bloom Filters. In: Proc. of the 20th ACM Symposium on Principles of Distributed Computing (2001)Google Scholar
  6. 6.
    Rohrs, C.: Query Routing for the Gnutella Network,
  7. 7.
    Wessels, D.: Squid,
  8. 8.
    Fan, L., Cao, P., Almeida, J., Broder, A.: Summary cache: A scalable wide-area Web cache sharing protocol. IEEE/ACM Transactions on Networking 8(3), 281–293 (2000)CrossRefGoogle Scholar
  9. 9.
    Rousskov, A., Wessels, D.: Cache digests. Computer Networks and ISDN Systems 30(22-23), 2155–2168 (1998)CrossRefGoogle Scholar
  10. 10.
    Matsuo, Y., Ishizuka, M.: Keyword Extraction from a Document using Word Cooccurrence Statistical Information (in Japanese). Trans. of the Japanese Society for Artificial Intelligence 17(3), 217–223 (2002)CrossRefGoogle Scholar
  11. 11.
    Adar, E., Huberman, B.A.: Free Riding on Gnutella. First Monday 5(10) (2000)Google Scholar
  12. 12.
  13. 13.
    Zhao, B., Kubuatowicz, J., Joseph, A.: Tapestry: An Infrastructure for Wide-area fault-tolerant Location and Routing. University of California, Berkeley Computer Science Division, Technical Report, UCB/CSD-01-1141 (2001)Google Scholar
  14. 14.
    Rowstron, A., Druschel, P.: Pastry: Scalable, decentralized object location and routing for a large-scale peer-to-peer system. In: Proc. of the 18th IFIP/ACM International Conference on Distributed System Platforms (2001)Google Scholar
  15. 15.
    Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., Balakrishnan, H.: Chord: A Scalable Peer-to-peer Look-up Service for Internet Application. In: Proc. of the ACM SIGCOMM Conference (2001)Google Scholar
  16. 16.
    Ratnasamy, S., Francis, P., Handley, M., Karp, R.: A Scalable Content-Addressable Network. In: Proc. of the ACM SIGCOMM Conference (2001)Google Scholar
  17. 17.
    Watts, D.J.: Small-Worlds. Princeton University Press, Princeton (1999)Google Scholar
  18. 18.
    Albert, R., Jeong, H., Barabási, A.-L.: Error and attack tolerance of complex networks. Nature 406, 378–381 (2000)CrossRefGoogle Scholar
  19. 19.
    Davidsen, J., Ebel, H., Bornholdt, S.: Emergence of a Small World form Local Interactions: Modeling Acquaintance Networks. Physical Review Letters 88(12), 128701 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kazuhiro Kojima
    • 1
  1. 1.AISTTsukubaJapan

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