Future Generation Computer Systems - Special issue on metacomputing
The Kangaroo Approach to Data Movement on the Grid
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
Enabling the Co-Allocation of Grid Data Transfers
GRID '03 Proceedings of the 4th International Workshop on Grid Computing
Downloading Replicated, Wide-Area Files - A Framework and Empirical Evaluation
NCA '04 Proceedings of the Network Computing and Applications, Third IEEE International Symposium
The Livny and Plank-Beck Problems: Studies in Data Movement on the Computational Grid
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
The Globus Striped GridFTP Framework and Server
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
A taxonomy of Data Grids for distributed data sharing, management, and processing
ACM Computing Surveys (CSUR)
A Transparent Distributed Shared Memory for Clustered Symmetric Multiprocessors
The Journal of Supercomputing
A multi-layer resource reconfiguration framework for grid computing
Proceedings of the 4th international workshop on Middleware for grid computing
Production Storage Resource Broker Data Grids
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
Complete and fragmented replica selection and retrieval in Data Grids
Future Generation Computer Systems
A grid-enabled software distributed shared memory system on a wide area network
Future Generation Computer Systems
Efficient reuse of replicated parallel data segments in computational grids
Future Generation Computer Systems
A replicated file system for Grid computing
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing: Future Trends (MGC2006)
Replica selection on co-allocation data grids
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
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Grid data sharing systems usually provide a data-intensive application with either a pre-staging mechanism or an on-demand access mechanism to access shared data. Pre-staging systems simultaneously download an entire shared file from multiple data sources even when only a tiny file fragment is required. Such systems consume unnecessary data transmission time and storage space. On-demand access systems, on the other hand, download only the required fragments from a single data source. Such systems unfortunately do not fully exploit available network bandwidth. This paper presents a data sharing system, designated as the On-Demand data Co-Allocation (ODCA). ODCA facilitates an unmodified legacy applications to transparently access shared data by using native I/O system calls. ODCA transfers only the necessary fragments on user demand, thereby reducing data transmission time, avoiding wasted network bandwidth and wasted storage space. Moreover, ODCA reduces data waiting time by downloading the file fragments from multiple data sources. Experimental results show ODCA successfully reduces turnaround time in data-intensive applications.