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Moving huge scientific datasets over the Internet

Authors :
Rajkumar Kettimuthu
Wantao Liu
Brian Tieman
Ian Foster
Source :
Concurrency and Computation: Practice and Experience. 23:2404-2420
Publication Year :
2011
Publisher :
Wiley, 2011.

Abstract

Modern scientific experiments can generate hundreds of gigabytes to terabytes or even petabytes of data that may be maintained in large numbers of relatively small files. Frequently, these data must be disseminated to remote collaborators or computational centers for data analysis. Moving this dataset with high performance and strong robustness and providing a simple interface for users are challenging tasks. We present a data transfer framework comprising a high-performance data transfer library based on GridFTP, an extensible data scheduler with four data scheduling policies, and a GUI that allows users to transfer their dataset easily, reliably, and securely. This system incorporates automatic tuning mechanisms to select at runtime the number of concurrent threads to be used for transfers. Also included are restart mechanisms for handling client, network, and server failures. Experimental results indicate that our data transfer system can significantly improve data transfer performance and can recover well from failures. Copyright © 2011 John Wiley & Sons, Ltd.

Details

ISSN :
15320626
Volume :
23
Database :
OpenAIRE
Journal :
Concurrency and Computation: Practice and Experience
Accession number :
edsair.doi...........9426ed57d7f253ca78179d57895ab987
Full Text :
https://doi.org/10.1002/cpe.1779