.<F3.733e+05> Data placement in shared-nothing database systems has been studied extensively in the past and various placement algorithms have been proposed. However, there is no consensus on the most efficient data placement algorithm and placement is still performed manually by a database administrator with periodic reorganization to correct mistakes. This paper presents the first comprehensive simulation study of data placement issues in a shared-nothing system. The results show that current hardware technology trends have significantly changed the performance tradeoffs considered in past studies. A simplistic data placement strategy based on the new results is developed and shown to perform well for a variety of workloads.<F7.947e+05> Key words:<F3.733e+05> Declustering -- Disk allocation -- Resource allocation -- Resource scheduling<F7.947e+05> 1 Introduction<F3.733e+05> The last decade has seen a significant change in the characteristics of database applications. The demands of...

This work addresses a files allocation problem (FAP) in distributed computing systems. This FAP attempts to minimize the expected data transfer time for a specific program that must access several data files from non-perfect computer sites. We assume that communication capacity can be reserved; hence, the data transmission behavior is modeled as a many-to-one multi-commodity flow problem. A new critical-cut method is proposed to solve this reduced multi-commodity flow problem. Based on this method, two algorithms which use branch-and-bound are proposed for this FAP. The proposed algorithms are able to allocate data files having single copies or multiple replicated copies. Simulation results are presented to demonstrate the performance of the algorithms.