Large-scale optimization for data placement problem

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dc.contributor.authorAnsari, Lazima
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorGaur, Daya
dc.date.accessioned2017-11-15T18:30:52Z
dc.date.available2017-11-15T18:30:52Z
dc.date.issued2017
dc.degree.levelMastersen_US
dc.description.abstractLarge-scale optimization of combinatorial problems is one of the most challenging areas. These problems are characterized by large sets of data (variables and constraints). In this thesis, we study large-scale optimization of the data placement problem with zero storage cost. The goal in the data placement problem is to find the placement of data objects in a set of fixed capacity caches in a network to optimize the latency of access. Data placement problem arises naturally in the design of content distribution networks. We report on an empirical study of the upper bound and the lower bound of this problem for large sized instances. We also study a semi-Lagrangean relaxation of a closely related k-median problem. In this thesis, we study the theory and practice of approximation algorithm for the data placement problem and the k-median problem.en_US
dc.embargoNoen_US
dc.identifier.urihttps://hdl.handle.net/10133/4980
dc.language.isoen_USen_US
dc.proquest.subject0984en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : Universtiy of Lethbridge, Department of Mathematics and Computer Scienceen_US
dc.publisher.departmentDepartment of Mathematics and Computer Scienceen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectdata placement problemen_US
dc.subjectk-median problemen_US
dc.subjectLagrangean relaxationen_US
dc.subjectlarge-scale optimizationen_US
dc.subjectlatency of accessen_US
dc.subjectzero storage costen_US
dc.titleLarge-scale optimization for data placement problemen_US
dc.typeThesisen_US
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