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A new paradigm: Data-aware scheduling in grid computing
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DOI：10.1016/j.future.2008.09.006.png)
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Efficient and reliable access to large-scale data sources and archiving destinations in a widely distributed computing environment brings new challenges. The insufficiency of the traditional systems and existing CPU-oriented batch schedulers in addressing these challenges has yielded a new emerging era: data-aware schedulers. In this article, we discuss the limitations of the traditional CPU-oriented batch schedulers in handling the challenging data management problem of large-scale distributed applications: give our vision for the new paradigm in data-intensive scheduling: and elaborate on our case study: the Stork data placement scheduler. (C) 2008 Elsevier B.V. All rights reserved.
Keyword:
Grid computing
Data-intensive applications
Data-aware scheduling
Data placement
Stork
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