Notice of Violation of IEEE Publication Principles An adaptive routing mechanism for P2P resource discovery
Luca Gatani, Giuseppe Lo Re, Salvatore Gaglio · 2005
Notice of Violation of IEEE Publication Principles"An Adaptive Routing Mechanism for P2P Resource Discovery,"by L. Gatani, G. Lo Re, S. Gaglio.,in the Proceedings of the IEEE International Symposium on Cluster Computing and the Grid, 2005. CCGrid 2005. pp. 205-212 Vol. 1, 9-12 May 2005After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.This paper contains substantial duplication of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:6S: "Distributing Crawling and Searching Across Web Peers"By Filippo Menczer, Ruj Akavipat and Le-Shin Wuavailable at the following URL: http://www.informatics.indiana.edu/research/publications/6S.pdfThe key to the usability of large-scale decentralize peer-to-peer (P2P) systems, and one of the most challenge design aspects, is efficient mechanism for distributed resource discovery. Unstructured P2P networks are very attractive because they do not suffer the limitations of centralized systems an the drawbacks of highly structured approaches. However the search algorithms are usually based on simple flooding scheme generating large loads on the network participants. In this paper to address this major limitation, we present the design an evaluation of an innovative searching protocol in unstructured P2P networks. The approach aims at dynamically adapting the network topology to peers' interests, on the basis of a peer neighbor selection algorithm. Each peer builds and maintains profiles of other peers, describing their interests and resources. Given a query, it is consequently routed according to the predicted match with other peers' profiles. Experimental evaluation shows that the approach is able to exploit query interactions among users, in order to dynamically group peer nodes in clusters containing peers with shared interests and organized into a small world topology.