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Distinct Value Estimation By Sampling On Unstructured Peer To Peer Networks

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Distinct Value Estimation By Sampling On Unstructured Peer To Peer Networks

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dc.contributor.author Joseph, Zubin Matthew en_US
dc.date.accessioned 2008-04-22T02:41:18Z
dc.date.available 2008-04-22T02:41:18Z
dc.date.issued 2008-04-22T02:41:18Z
dc.date.submitted November 2007 en_US
dc.identifier.other DISS-1906 en_US
dc.identifier.uri http://hdl.handle.net/10106/721
dc.description.abstract Peer-to-Peer networks have become very popular on the Internet, with millions of peers all over the world sharing large volumes of data. The sheer scale of these networks has made it difficult to gather statistics that could be used for building new features. This thesis presents a technique of obtaining estimations of the number of distinct values matching a query on the network. The method is then analyzed by considering simulation results that demonstrate its effectiveness and flexibility in supporting a variety of queries and applications. en_US
dc.description.sponsorship Das, Gautam en_US
dc.language.iso EN en_US
dc.publisher Computer Science & Engineering en_US
dc.title Distinct Value Estimation By Sampling On Unstructured Peer To Peer Networks en_US
dc.type M.S. en_US
dc.contributor.committeeChair Das, Gautam en_US
dc.degree.department Computer Science & Engineering en_US
dc.degree.discipline Computer Science & Engineering en_US
dc.degree.grantor University of Texas at Arlington en_US
dc.degree.level masters en_US
dc.degree.name M.S. en_US
dc.identifier.externalLink https://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=178
dc.identifier.externalLinkDescription Link to Research Profiles

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