Distributed randomized pagerank algorithms based on web aggregation over unreliable channels

Hideaki Ishii; Roberto Tempo; Er-Wei Bai

doi:10.1109/CDC.2010.5718041

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Conference proceeding

Distributed randomized pagerank algorithms based on web aggregation over unreliable channels

Hideaki Ishii, Roberto Tempo and Er-Wei Bai

49th IEEE Conference on Decision and Control (CDC), Vol.No, pp.6602-6607

12/2010

DOI: 10.1109/CDC.2010.5718041

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Abstract

The PageRank algorithm employed at Google assigns a measure of importance to each web page for rankings in search results. In our recent papers, we have proposed a distributed randomized approach for this algorithm, where web pages are treated as agents computing their own PageRank by communicating with linked pages. Here, we focus on the effects of unreliability in the communication and, in particular, model the random data losses as an outcome of Markov chains. By generalizing the aggregated PageRank computation previously developed, we provide a distributed scheme along with analyses on its convergence properties.

Approximation algorithms

Convergence

Distributed algorithms

Distributed computation

Eigenvalues and eigenfunctions

Electronic mail

Markov processes

Multi-agent consensus

PageRank algorithm

Randomization

Stochastic matrices

Unreliable channels

Web pages

Details

Title: Subtitle: Distributed randomized pagerank algorithms based on web aggregation over unreliable channels
Creators: Hideaki Ishii - Tokyo Institute of Technology
Roberto Tempo - Politecnico di Torino
Er-Wei Bai - University of Iowa
Resource Type: Conference proceeding
Publication Details: 49th IEEE Conference on Decision and Control (CDC), Vol.No, pp.6602-6607
DOI: 10.1109/CDC.2010.5718041
ISSN: 0191-2216
Publisher: IEEE
Language: English
Date published: 12/2010
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984197302302771

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