On Obtaining Global Information in a Peer-to-Peer Fully Distributed Environment

  • Márk Jelasity
  • Mike Preuß
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2400)


Networking solutions which do not depend on central services and where the components posses only partial information are robust and scalable but obtaining global information like e.g. the size of the network raises serious problems, especially in the case of very large systems. We consider a specific type of fully distributed peer-to-peer (P2P) environment with many interesting existing and potential applications. We suggest solutions for estimating network size and detecting partitioning, and we give estimations for the time complexity of global search in this environment. Our methods rely only on locally available (but continuously refreshed) partial information.


Network Size Central Service Global Search Partial Information Global Information 
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  1. 1.
    A. Demers, D. Greene, C. Hauser, W. Irish, J. Larson, S. Shenker, H. Sturgis, D. Swinehart, and D. Terry. Epidemic algorithms for replicated database management. In Proceedings of the 6th Annual ACM Symposium on Principles of Distributed Computing (PODC’87), pages 1–12, Vancouver, Aug. 1987. ACM.Google Scholar
  2. 2.
  3. 3.
    P. Druschel and A. Rowstron. Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility. In Proceedings of the 18th ACM Symposium on Operating Systems Principles (SOSP), Banff, Canada, 2001. ACM.Google Scholar
  4. 4.
  5. 5.
    M. Jelasity, M. Preuß, and B. Paechter. A scalable and robust framework for distributed applications. Accepted for publication in the Proceedings of the 2002 Congress on Evolutionary Computation (CEC2002).Google Scholar
  6. 6.
    M. Jelasity, M. Preuß, M. van Steen, and B. Paechter. Maintaining connectivity in a scalable and robust distributed environment. Accepted for publication in the Proceedings of the 2nd IEEE International Symposium on Cluster Computing and the Grid (CCGrid2002), May 21–24, 2002, Berlin, Germany.Google Scholar
  7. 7.
    A.-M. Kermarrec, L. Massoulie, and A. J. Ganesh. Probablistic reliable dissemination in large-scale systems. Submitted for publication, available as
  8. 8.
    B. Paechter, T. Back, M. Schoenauer, M. Sebag, A. E. Eiben, J. J. Merelo, and T. C. Foga-rty. A distributed resoucre evolutionary algorithm machine (DREAM). In Proceedings of the Congress on Evolutionary Computation 2000 (CEC2000), pages 951–958. IEEE, IEEE Press, 2000.Google Scholar
  9. 9.

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Márk Jelasity
    • 1
    • 2
  • Mike Preuß
    • 3
  1. 1.Dept. of AIFree Univ. of AmsterdamHungary
  2. 2.RGAIUniv. of SzegedHungary
  3. 3.Dept. of Computer ScienceUniv. of DortmundHungary

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