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

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dc.contributor.advisor Menasce, Daniel A.
dc.contributor.author Bardhan, Shouvik
dc.creator Bardhan, Shouvik
dc.date.accessioned 2015-07-29T18:42:48Z
dc.date.available 2015-07-29T18:42:48Z
dc.date.issued 2015
dc.identifier.uri https://hdl.handle.net/1920/9694
dc.description.abstract Over 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.extent 161 pages
dc.language.iso en
dc.rights Copyright 2015 Shouvik Bardhan
dc.subject Computer science en_US
dc.subject Hadoop en_US
dc.subject MapReduce en_US
dc.subject Multi-core machines en_US
dc.subject Queuing theory en_US
dc.subject Scheduling en_US
dc.title Design and Modeling of Schedulers for Multi-Task Jobs on Computer Clusters
dc.type Dissertation en
thesis.degree.level Doctoral en
thesis.degree.discipline Computer Science en
thesis.degree.grantor George Mason University en


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