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Optorsim: A Grid Simulator for Studying Dynamic Data Replication Strategies

Computational grids process large, computationally intensive problems on small data sets. In contrast, data grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data,...

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Detalles Bibliográficos
Autores principales: Bell, William H, Cameron, David G, Millar, A Paul, Capozza, Luigi, Stockinger, Kurt, Zini, Floriano
Lenguaje:eng
Publicado: 2003
Materias:
Acceso en línea:https://dx.doi.org/10.1177/10943420030174005
http://cds.cern.ch/record/1976538
Descripción
Sumario:Computational grids process large, computationally intensive problems on small data sets. In contrast, data grids process large computational problems that in turn require evaluating, mining and producing large amounts of data. Replication, creating geographically disparate identical copies of data, is regarded as one of the major optimization techniques for reducing data access costs. In this paper, several replication algorithms are discussed. These algorithms were studied using the Grid simulator: OptorSim. OptorSim provides a modular framework within which optimization strategies can be studied under different Grid configurations. The goal is to explore the stability and transient behaviour of selected optimization techniques. We detail the design and implementation of OptorSim and analyze various replication algorithms based on different Grid workloads.