Clustering in the Cloud: Clustring Algorithms to Hadoop Map/Reduce Framework

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dc.contributor.authorWang, Xuan
dc.date.accessioned2010-05-19T10:03:29Z
dc.date.available2012-02-24T10:03:42Z
dc.date.issued2010-05-04
dc.description.abstractCloud computing has gained an increasing popularity over the years for its great potentials. It is a logical and forward-thinking solution for addressing key business demands. Cloud computing truly represents what enterprise IT always needs: a way to increase capacity or add capabilities on the fly without investing in new infrastructure, training new personnel, or licensing new software. Cloud computing encompasses any subscription-based or pay-per-use service that, in real time over the Internet, extends IT's existing capabilities. This study investigates how clustering algorithms in data mining can benefit from running in the "Cloud".
dc.description.departmentComputer Science
dc.formatText
dc.format.extent14 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationWang, X. (2010). Clustering in the cloud (Report No. TXSTATE-CS-TR-2010-24). Texas State University-San Marcos, Department of Computer Science.
dc.identifier.urihttps://hdl.handle.net/10877/2597
dc.language.isoen
dc.subjecthadoop
dc.subjectmapreduce
dc.subjectAmazon EC2
dc.subjectclustering
dc.subjectKmeans
dc.subjectalgorithms
dc.subjectcloud computing
dc.subjectframework
dc.subjectclustering algorithms
dc.subjectdata mining
dc.subjectComputer Science
dc.titleClustering in the Cloud: Clustring Algorithms to Hadoop Map/Reduce Framework
dc.typeTechnical Report

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