Peer-to-Peer Information Retrieval Based on Fields of Interest

  • Bertalan Forstner
  • Gergely Csúcs
  • Imre Kelényi
  • Hassan Charaf

The task of efficient distributed information retrieval has been one of the most serious challenges in the history of information technology. With the spread of advanced mobile devices, the demand for an efficient file sharing protocol moved also into the mobile world. However, the mobile networks have special characteristics that should be taken into account when designing efficient resource sharing protocols for this area.

The performance of the Peer-to-Peer protocols can be increased with the use of semantic information gathered from the shared files. However, as the optimal solution for an unstructured network requires a full knowledge of the files available in the network, certain kinds of heuristic methods should be designed to increase the probability of successful queries, without large protocol overhead and network traffic. In this chapter, we will present how the network topology can be quickly improved to increase hit rate with an appropriate protocol and algorithm using Bayesian process based on local decisions that infers from the fields of interest owned by the nodes.


Candidate Node Answer Ratio Protocol Extension Local Cooperation Distribute Information Retrieval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    H. Assadi. Construction of a regional ontology from text and its use within a documentary system. In Proc. of International Conference on Formal Ontology and Information Systems, (FOIS-98), Amsterdam, 1998. IOS Press.Google Scholar
  2. 2.
    James O. Berger. Statistical Decision Theory and Bayesian Analysis. Springer, second edition edition, 1985.Google Scholar
  3. 3.
    Hanhua Chen, Hai Jin, and Xiaomin Ning. Semantic peer-to-peer overlay for efficient content locating. In Proc. of MEGA’06, Harbin, China, Januar 2006. Google Scholar
  4. 4.
    Christiane Fellbaum. WordNet, An Electronic Lexical Database. MIT Press, 1998. ISBN 978-0-262-06197-1.MATHGoogle Scholar
  5. 5.
    B. Forstner. An analytic model for peer-to-peer systems with semantic overlay network. In Proc. of AACS’06 Workshop, Budapest, Hungary, 2006.Google Scholar
  6. 6.
    B. Forstner, G. Csúcs, K. Marossy, and H. Charaf. Evaluating performance of peer-to-peer protocols with an advanced simulator. In Proc. of Parallel And Distributed Computing And Networks PDCN2005, Innsbruck, Austria, February 2005.Google Scholar
  7. 7.
    Bertalan Forstner and Hassan Charaf. Modeling peer-to-peer networks with interest-based clusters. Transactions on Enformatika, Systems Sciences and Engineering, 8(2):38-43, Oktober 2005.Google Scholar
  8. 8.
    The gnutella protocol homepage.
  9. 9.
    Sam Joseph. P2p metadata search layers. In Proc. of Second International Workshop on Agents and Peer-to-Peer Computing (AP2PC 2003), 2003.Google Scholar
  10. 10.
    J. -U. Kietz, A. Maedche, and R. Volz. Semi-automatic ontology acquisition from a corporate intranet. In Proc. of Learning Language in Logic Workshop (LLL-2000), New Brunswick, N. J., 2000. IOS Press.Google Scholar
  11. 11.
    S. Shashidhar Merugu and E. Zegura. Adding structure to unstructured peer-to-peer networks: the use of small-world graphs. Journal of Parallel and Distributed Computing, 65(2):142-153, Februar 2005.MATHCrossRefGoogle Scholar
  12. 12.
    Resnik P. Semantic similarity in taxonomy: An information-based measure and its application problems of ambiguity in natural language. Journal of Artificial Intelligence Research, 11:95-130, 1999.MATHGoogle Scholar
  13. 13.
    Sylvia Ratnasamy, Paul Francis, Mark Handley, RichardKarp, and Scott Shenker. A scalable content-addressable network. In Proc. of SIGCOMM’2001, August 2001.Google Scholar
  14. 14.
    A. Rowstron and P. Druschel. Storage management and caching in past, a large-scale, persistent peer-to-peer storage utility. In Proc. of SOSP’01, 2001.Google Scholar
  15. 15.
    K. Sripanidkulchai, B. Maggs, and H. Zhang. Efficient content location using interest-based locality in peer-topeer systems. In Proc. of Infocom 2003, 2003.Google Scholar
  16. 16.
    Ion Stoica, Robert Morris, David Karger, Frans Kaashoek, and Hari Balakrish-nan. Chord: A scalable peer-topeer lookup service for internet applications. In Proc. of SIGCOMM’2001, August 2001.Google Scholar
  17. 17.
    The symella application homepage.
  18. 18.
    B. Yang and H. Garcia-Molina. Efficient search in peer-to-peer networks. In Proceedings of the 22nd International Conference on Distributed Computing Sys-tems (ICDCS), July 2002.Google Scholar
  19. 19.
    Ben Y. Zhao, John Kubiatowicz, and Anthony Joseph. Tapestry: An in-frastructure for fault-tolerant wide-area location and routing. Technical Report UCB/CSD-01-1141, University of California at Berkeley, Computer Science Department, 2001.Google Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • Bertalan Forstner
    • 1
  • Gergely Csúcs
    • 1
  • Imre Kelényi
    • 1
  • Hassan Charaf
    • 1
  1. 1.Budapest University of Technology and EconomicsHungary

Personalised recommendations