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Distributing Page Rank for Peer to Peer Systems

Author(s):

G. Yesupriya , Rajah Serfoni Govt. College (Autonomous); C. Muruganandam, Rajah Serfoni Govt. College (Autonomous)

Keywords:

P2P, Distributed Page Rank

Abstract

Page Rank is extensively used for ranking web pages in order of relevance by mostly all search engines world-wide. There are many algorithms for page ranking such as Google Page Rank algorithm, Hyperlink-Induced Topic Search (HITS) algorithm etc. Some search engine uses link structure based page ranking algorithm while some uses content based. The page ranking algorithm reflects the popularity of a web page in its page rank score. But with the growing requirements of ordering more and more relevant web pages, the traditional page rank algorithm undergoes several enhancements and improvements. The main aim of this paper is to discuss the various existing page ranking algorithms and the modification done to the standard page rank algorithm. This paper defines and describes a fully distributed implementation of Google’s highly effective Page rank 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 page ranks as new documents are entered into or deleted from the network. Incremental update enables continuously accurate page ranks whereas the currently centralized web crawl and computation over Internet documents requires several days. This suggests possible applicability of the distributed algorithm to page rank computations as a replacement for the centralized web crawler based implementation for Internet documents. A complete solution of the distributed page rank computation for an in place 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.

Other Details

Paper ID: IJSRDV4I50744
Published in: Volume : 4, Issue : 5
Publication Date: 01/08/2016
Page(s): 1322-1324

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