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Automatic data placement and replication in grids

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2 Author(s)
Ying Ding ; Department of Computer Science and Engineering, University of Nebraska - Lincoln, Lincoln, NE 68588-0115 ; Ying Lu

Data grids provide geographically distributed storage and computing resources for large data-intensive applications. To support fast data access and processing, effective data management is essential. In this paper, we propose two novel algorithms on data placement and data replication. We evaluate the algorithms through intensive simulations. Results show that the new algorithms achieve significant improvement in facilitating load balancing, reducing job response time, and saving network bandwidth.

Published in:

2009 International Conference on High Performance Computing (HiPC)

Date of Conference:

16-19 Dec. 2009