SETI@HOME—massively distributed computing for SETI
Computing in Science and Engineering
The End-to-End Performance Effects of Parallel TCP Sockets on a Lossy Wide-Area Network
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
An Evaluation of Object-Based Data Transfers on High Performance Networks
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Bulk data transfer forecasts and the implications to grid scheduling
Bulk data transfer forecasts and the implications to grid scheduling
Stork: Making Data Placement a First Class Citizen in the Grid
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Modeling and Taming Parallel TCP on the Wide Area Network
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
The Globus Striped GridFTP Framework and Server
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Dynamically tuning level of parallelism in wide area data transfers
DADC '08 Proceedings of the 2008 international workshop on Data-aware distributed computing
A new paradigm: Data-aware scheduling in grid computing
Future Generation Computer Systems
Secure, Performance-Oriented Data Management for nanoCMOS Electronics
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
| Hi-index | 0.00 |
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.