Intelligent agent enabled genetic ant algorithm for P2P resource discovery

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Rapid resource discovery in P2P networks is a challenging problem because users search for different resources at different times, and, nodes and their resources can vary dynamically as nodes join and leave the network. Traditional resource discovery techniques such as flooding generate enormous amounts of traffic, while improved P2P resource discovery mechanisms such as distributed hash tables(DHT) introduce additional overhead for maintaining content hashes on different nodes. In contrast, self-adaptive systems such as ant algorithms provide a suitable paradigm for controlled dissemination of P2P query messages. In this paper, we describe an evolutionary ant algorithm for rapidly discovering resources in a P2P network.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages213-220
Number of pages8
DOIs
StatePublished - 2005
EventThird International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2004 - New York, NY, United States
Duration: Jul 19 2004Jul 19 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3601 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceThird International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2004
CountryUnited States
CityNew York, NY
Period7/19/047/19/04

Keywords

  • Adaptive systems
  • Ant algorithm
  • Genetic algorithm
  • Peer-to-peer systems
  • Software agents

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Dasgupta, P. (2005). Intelligent agent enabled genetic ant algorithm for P2P resource discovery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 213-220). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3601 LNAI). https://doi.org/10.1007/11574781_20