The Data Grid provides a scalable infrastructure for storage resources and data distribution management. It also supports a variety of scientific applications that require access to large amounts of data with various quality of service requirements. Replication is the process of storing data in different locations to reduce access latency, improve data locality, and increase robustness, scalability and performance for distributed applications. It is the core mechanism of the Data Grid in that it enables scalable and efficient sharing of large volumes of data.

This paper focuses on finding the fastest and most reliable replica retrieval method in the Data Grid. For fast retrieval, we inspected, implemented, and tested various retrieval approaches, such as uniform, greedy, probe-based, latest-based, mean-based, and median-based. Experiments show that probe-based retrieval is the most appropriate approach for the Data Grid. For reliable retrieval, we introduce the recursive scheduling mechanism, which provides fault tolerant retrieval by rescheduling a failed subtransferring. Finally, we implemented ReCon (Replica Convoy) on Globus Toolkit version 4. The result is a fast and reliable replica retrieval service for the Data Grid.