Distributed Pagerank for P2P Systems

This paper defines 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 d...

• Type: Conference
• Year: 2003
• Where: HPDC
• Authors: Karthikeyan Sankaralingam, Simha Sethumadhavan, James C. Browne
• Keywords: Distributed And Parallel Computing, HPDC 2003, Incremental, Network Traffic, P2P Keyword Search