The Community for Technology Leaders
High-Performance Distributed Computing, International Symposium on (2003)
Seattle, Washington
June 22, 2003 to June 24, 2003
ISSN: 1082-8907
ISBN: 0-7695-1965-2
pp: 58
Karthikeyan Sankaralingam , University of Texas at Austin
Simha Sethumadhavan , University of Texas at Austin
James C. Browne , University of Texas at Austin
<p>This paper de.nes and describes a fully distributed implementation of Google?s highly effective Pagerank algorithm, for "peer to peer" (P2P) systems. The implementation is based on chaotic (asynchronous) iterative solution of linear systems. The P2P implementation also enables incremental computation of pageranks as new documents are entered into or deleted from the network. Incremental update enables continuously accurate pageranks whereas the currently centralized web crawl and computation over Internet documents requires several days. This suggests possible applicability of the distributed algorithm to pagerank computations as a replacement for the centralized web crawler based implementation for Internet documents. A complete solution of the distributed pagerank computation for an inplace network converges rapidly (1% accuracy in 10 iterations) for large systems although the time for an iteration may be long. The incremental computation resulting from addition of a single document converges extremely rapidly, typically requiring update path lengths of under 15 nodes even for large networks and very accurate solutions.</p> <p>This implementation of Pagerank provides a uniform ranking scheme for documents in P2P systems, and its integration with P2P keyword search provides one solution to the network traf.c problems engendered by return of document hits. In basic P2P keyword search, all the document hits must be returned to the querying node causing large network traffic. An incremental keyword search algorithm for P2P keyword search where document hits are sorted by pagerank, and incrementally returned to the querying node is proposed and evaluated. Integration of this algorithm into P2P keyword search can produce dramatic benefit both in terms of effectiveness for users and decrease in network traffic. The incremental search algorithm provided approximately a ten-fold reduction in network traffic for two-word and three-word queries.</p>

J. C. Browne, S. Sethumadhavan and K. Sankaralingam, "Distributed Pagerank for P2P Systems," High-Performance Distributed Computing, International Symposium on(HPDC), Seattle, Washington, 2003, pp. 58.
159 ms
(Ver 3.3 (11022016))