Approximation Algorithms for Data Placement on Parallel Disks

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dc.contributor.authorGolubchik, L.
dc.contributor.authorKhanna, Sanjeev
dc.contributor.authorKhuller, S.
dc.contributor.authorThurimella, R.
dc.contributor.authorZhu, An
dc.date2023-05-16T22:32:42.000
dc.date.accessioned2023-05-22T12:46:45Z
dc.date.available2023-05-22T12:46:45Z
dc.date.issued2000-01-01
dc.date.submitted2005-07-07T12:31:06-07:00
dc.description.abstractWe study an optimization problem that arises in the context of data placement in multimedia storage systems. We are given a collection of M multimedia data objects that need to be assigned to a storage system consisting of N disks d1,d2,...,dN. We are also given sets U1,U2,...,UM such that Ui is the set of clients requesting the ith data object. Each disk dj is characterized by two parameters, namely, its storage capacity Cj which indicates the maximum number of data objects that may be assigned to it, and a load capacity Lj which indicates the maximum number of clients that it can serve. The goal is to find a placement of data objects on disks and an assignment of clients to disks so as to maximize the total number of clients served, subject to the capacity constraints of the storage system. We study this data placement problem for two natural classes of storage systems, namely, homogeneous and uniform ratio. Our first main result is a tight upper and lower bound on the number of items that can always be packed for any input instance to homogeneous as well as uniform ratio storage systems. We show that an algorithm given in [11] for data placement, achieves this bound. Our second main result is a polynomial time approximation scheme for the data placement problem in homogeneous and uniform ratio storage systems, answering an open question of [11]. Finally, we also study the problem from an empirical perspective.
dc.description.commentsPostprint version. Copyright ACM, 2000. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 11th Annual Symposium on Discrete Algorithms 2000 (SODA 2000), pages 223-232. Publisher URL: http://portal.acm.org/citation.cfm?id=338255
dc.description.commentsPostprint version. Copyright ACM, 2000. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 11th Annual Symposium on Discrete Algorithms 2000 (SODA 2000), pages 223-232. Publisher URL: http://portal.acm.org/citation.cfm?id=338255
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/6248
dc.legacy.articleid1211
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1211&context=cis_papers&unstamped=1
dc.source.issue212
dc.source.journalDepartmental Papers (CIS)
dc.source.statuspublished
dc.titleApproximation Algorithms for Data Placement on Parallel Disks
dc.typePresentation
digcom.contributor.authorGolubchik, L.
digcom.contributor.authorisAuthorOfPublication|email:sanjeev@cis.upenn.edu|institution:University of Pennsylvania|Khanna, Sanjeev
digcom.contributor.authorKhuller, S.
digcom.contributor.authorThurimella, R.
digcom.contributor.authorZhu, An
digcom.identifiercis_papers/212
digcom.identifier.contextkey82652
digcom.identifier.submissionpathcis_papers/212
digcom.typeconference
dspace.entity.typePublication
relation.isAuthorOfPublication6dba9e69-9dec-4ccb-b783-4aafb448170b
relation.isAuthorOfPublication.latestForDiscovery6dba9e69-9dec-4ccb-b783-4aafb448170b
upenn.schoolDepartmentCenterDepartmental Papers (CIS)
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