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The file allocation problem--A queueing network optimization approach

dc.contributor.authorSrinivasan, Mandyam M.en_US
dc.contributor.authorKant, Krishnaen_US
dc.date.accessioned2006-04-07T20:02:15Z
dc.date.available2006-04-07T20:02:15Z
dc.date.issued1987en_US
dc.identifier.citationSrinivasan, M. M., Kant, K. (1987)."The file allocation problem--A queueing network optimization approach." Computers &amp; Operations Research 14(5): 349-361. <http://hdl.handle.net/2027.42/26948>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6VC5-48M3022-7J/2/93fc4d11c9b81a316fe27ac2baa3b659en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/26948
dc.description.abstractA set of customers use a connected network of computer installations, each accessing the network from a particular node. These customers share information contained in a set of data files. A typical customer's need is characterized by a request requiring a subset of these files being accessed in a Markovian sequence. The cycle time for this customer is the total time taken on the average to complete his request sequence. The objective is to locate a single copy of each of the files in such a way that a weighted sum of these response times is minimized. The problem is modelled as a Closed Queueing Network optimization problem. Models are developed for both single and multiple chain cases. An incremental analysis approach is used to solve the single chain case. For the multiple chain case, it is shown how this model approximates to a set partitioning problem under certain conditions. Efficient heuristics are developed to solve this partitioning problem. With certain simplifying assumptions, the associated communication problem is then included in the model.en_US
dc.format.extent1227962 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleThe file allocation problem--A queueing network optimization approachen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelManagementen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelBusinessen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, MI 48109-2117, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Computer Science, The Pennsylvania State University, University Park, PA 16802, U.S.A.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/26948/1/0000514.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0305-0548(87)90032-3en_US
dc.identifier.sourceComputers &amp; Operations Researchen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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