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- W207201224 abstract "Data Grids have become the de facto platform for the next generation of eScience experiments that will be carried out through large collaborations spread around the world. As the number of entities within a data grid increases, scheduling of applications in order to make the most efficient use of the available resources such as computational, storage and network facilities becomes a challenge. Previous work has suggested a computational economy metaphor for resource management within compute and data grids. However, the issue of scheduling jobs that require distributed data within an economy-based data grid has not been studied in detail so far. In this paper, we present a model and an algorithm for economy-based scheduling of distributed data intensive applications on data grids. The model takes into account the costs and times for transferring datasets required for a job from different data hosts to the compute resource on which the job will be executed and for its processing. The algorithm builds a resource set for a job that minimizes the cost or time depending on the user’s preferences. We evaluate the algorithm on a Data Grid testbed and present the results." @default.
- W207201224 created "2016-06-24" @default.
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- W207201224 date "2004-01-01" @default.
- W207201224 modified "2023-09-26" @default.
- W207201224 title "An Economy-based Algorithm for Scheduling Data-Intensive Applications on Global Grids" @default.
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