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The Data Grid: Towards an Architecture for the Distributed Management and Analysis of Large Scientific Datasets (1999)
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| Venue: | JOURNAL OF NETWORK AND COMPUTER APPLICATIONS |
| Citations: | 469 - 40 self |
BibTeX
@ARTICLE{Chervenak99thedata,
author = {Ann Chervenak and Ian Foster and Carl Kesselman and Charles Salisbury and Steven Tuecke},
title = {The Data Grid: Towards an Architecture for the Distributed Management and Analysis of Large Scientific Datasets},
journal = {JOURNAL OF NETWORK AND COMPUTER APPLICATIONS},
year = {1999},
volume = {23},
pages = {187--200}
}
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Abstract
In an increasing number of scientific disciplines, large data collections are emerging as important community resources. In this paper, we introduce design principles for a data management architecture called the Data Grid. We describe two basic services that we believe are fundamental to the design of a data grid, namely, storage systems and metadata management. Next, we explain how these services can be used to develop higher-level services for replica management and replica selection. We conclude by describing our initial implementation of data grid functionality.
Keyphrases
data grid large scientific datasets distributed management storage system important community resource data grid functionality replica management design principle higher-level service data management architecture large data collection scientific discipline replica selection initial implementation basic service metadata management
