Design and Modeling of Schedulers for Multi-Task Jobs on Computer Clusters

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dc.contributor.advisorMenasce, Daniel A.
dc.contributor.authorBardhan, Shouvik
dc.creatorBardhan, Shouvik
dc.date.accessioned2015-07-29T18:42:48Z
dc.date.available2015-07-29T18:42:48Z
dc.date.issued2015
dc.description.abstractOver the course of the last decade, a tremendous amount of information has been generated, collected, and eventually stored on modern server scale computers. This ongoing process led to the coinage of the term "Big Data," a concept that the industry uses to describe the all-encompassing activities of storing and processing this petabyte scale data. Stakeholders, academics, and technologists are trying to extract actionable intelligence from this huge volume of data, while massive clusters of computers are now being used to process the continually expanding amount of information.
dc.format.extent161 pages
dc.identifier.urihttps://hdl.handle.net/1920/9694
dc.language.isoen
dc.rightsCopyright 2015 Shouvik Bardhan
dc.subjectComputer science
dc.subjectHadoop
dc.subjectMapReduce
dc.subjectMulti-core machines
dc.subjectQueuing theory
dc.subjectScheduling
dc.titleDesign and Modeling of Schedulers for Multi-Task Jobs on Computer Clusters
dc.typeDissertation
thesis.degree.disciplineComputer Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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