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Heuristics for Uninformed Search Algorithms in Unstructured P2P Networks Inspired by Self-Organizing Social Insect Models

  • Prithviraj Dasgupta
  • Erik Antonson
Part of the IFIP – The International Federation for Information Processing book series (IFIPAICT, volume 268)

Abstract

We consider the problem of rapidly searching for resources or files in a distributed, unstructured, peer-to-peer file sharing network. Unstructured p2p network protocols such as Gnutella use a flooding-based mechanism for resource searching that generates considerable traffic in the network for each search query. When the searching activity by users in a p2p network is high, the traffic generated from the search requests could ensue congestion and result in increased search latency and poor performance in the entire network. To address this problem, we describe a resource search algorithm for p2p networks inspired by the stigmergetic behavior of ants while searching for food. Ants are used to encapsulate a search query initiated by a user in the p2p network. To search for the resource corresponding to their search query among the nodes of the network, each ant associates a certain amount of virtual pheromone with the nodes it visits. Later on, ants searching for resources use the amount and type of pheromone associated by previous ants with each node along their search path to direct the search query towards nodes that have a higher probability of resulting in the success for the search. We have tested our algorithm extensively within a simulated p2p network. Our simulation results show that our ant-based heuristics perform better than a completely uninformed or blind search that requires similar message overhead for each search query. When compared to a flooding-based mechanism, although the ant based search heuristic performs less efficiently under certain circumstances, it is capable of reducing the message overhead per search query by an exponential amount with respect to the flooding-based mechanism.

Keywords

Swarm intelligence software agents peer-to-peer networks resource searching 

References

  1. 1.
    . H. Van Dyke Parunak, and S Brueckner : Swarming Coordination of Multiple UAVs for Collaborative Sensing. In: Proc. 2nd AIAA ’Unmanned Unlimited’ Systems Conference, San Diego, CA, (2003).Google Scholar
  2. 2.
    . O. Babaoglu, H. Meling and A. Montresor: Anthill:A framework for the development of agent-based peer-to-peer systems. In: Proc. 22nd International Conference on Distributed Computing Systems (ICDCS), pp. 15-22, (2002).Google Scholar
  3. 3.
    . Abraham, C. Grosan, V. Ramos (eds.): Swarm Intelligence in Data Mining,”Studies in Computational Intelligence , vol. 34, Springer, (2006).Google Scholar
  4. 4.
    . E. Bonabeau. , M. Dorigo, G. Theraulaz: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, 1999.Google Scholar
  5. 5.
    G. Di Caro and M. Dorigo: AntNet: Distributed Stigmergetic Control for Communications Networks. Journal of Artificial Intelligence Research, vol. 9, pp. 317-365, (1998).zbMATHGoogle Scholar
  6. 6.
    . Fast Track, URL http://www.fasttrack.com
  7. 7.
    . Gnutella, URL http://www.gnutella.com
  8. 8.
    . Kazaa, URL http://www.kazaa.com
  9. 9.
    . Napster Inc., URL http://www.napster.com
  10. 10.
    S. Saroiu, P. Gummadi, S. Gribble: Measuring and analyzing the characteristics of Napster and Gnutella hosts. Multimedia Systems, vol. 9 no.2, pp 170-184, (2003).CrossRefGoogle Scholar
  11. 11.
    . B. Yang and H. Garcia-Molina: Designing a super-peer network. Proc. 19th International Conference on Data Engineering (ICDE), pp. 49-62, (2003).Google Scholar
  12. 12.
    . I. Stoica, R. Morris, D. Karger, F. Kaashoek, and H. Balakrishnan: Chord: A peer-to-peer lookup service for internet applications. In: Proc. ACM SIGCOMM Conference, pp. 149- 160, (2001).Google Scholar
  13. 13.
    . J. Kubiatowicz, et al.: OceanStore: An Architecture for Global-Scale Persistent Storage. In: Proc. ACM ASPLOS, pp. 190-201, (2000).Google Scholar
  14. 14.
    . P. Dasgupta: Improving Peer-to-Peer Resource Discovery Using Mobile Agent Based Referrals. In: Proc. 2nd Workshop on Agent Enabled P2P Computing, pp. 41-54, (2003).Google Scholar
  15. 15.
    . J. Montgomery, and M. Randall: Anti-pheromone as a tool for better exploration of search space. In: Lecture Notes in Computer Science, vol. 2463, Springer-Verlag, pp. 100-110, (2002).Google Scholar

Copyright information

© International Federation for Information Processing 2008

Authors and Affiliations

  • Prithviraj Dasgupta
    • 1
  • Erik Antonson
    • 1
  1. 1.Computer Science DepartmentUniversity of NebraskaOmahaUSA

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