Abstract. We study an optimization problem that arises in the context of data placement in a multimedia storage system. We are given a collection of M multimedia objects (data objects) that need to be assigned to a storage system consisting of N disks d 1 , d 2 . . . , d N . We are also given sets U 1 , U 2 , . . . , U M such that U i is the set of clients seeking the ith data object. Each disk d j is characterized by two parameters, namely, its storage capacity C j which indicates the maximum number of data objects that may be assigned to it, and a load capacity L j which indicates the maximum number of clients that it can serve. The goal is to find a placement of data objects to 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. We show that an algorithm developed by Shachnai and Tamir Thurimella, Department of Computer Science, University of Denver, CO, e-mail: ramki@cs.du.edu; A. Zhu, e-mail: Google Inc., Mountain View, CA 94043; anzhu@cs.stanford.edu. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 ( data placement achieves the best possible absolute bound regarding the number of clients that can always be satisfied. We also show how to implement the algorithm so that it has a running time of O((N + M) log (N + M) ). In addition, we design a polynomial-time approximation scheme, solving an open problem posed in the same paper.
In REF , the authors deploy a polynomial time approximation schema for data placement problem in homogeneous and uniform ratio storage systems.
Approximation algorithms for data placement on parallel disks
TALG
Computer Science