2003The International Journal of High Performance Computing ApplicationsRequires access

Optorsim: A Grid Simulator for Studying Dynamic Data Replication Strategies

W. H. Bell, David G. Cameron, Paul Millar, Luigi Capozza, Kurt Stockinger, Floriano Zini

Open publisher page 344 citations

Abstract

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.

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What this paper is about

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.

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OpenAlex reports 344 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

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.

Key concepts: Replication (statistics), Computer science, Grid, Data grid, Distributed computing, Modular design, Process (computing), Grid computing

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