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.

Many areas of science currently use computing resources as a important part of their research, and many research groups adopt cluster architecture to use them efficiently and manage them easily. Therefore, faulttolerance becomes a very important property for the computing resources. However, fault-tolerant systems have not yet been widely adopted because they are either hard to deploy, hard to use, hard to manage, hard to maintain, or hard to justify. This paper proposes a practical fault-tolerant system for eScience infrastructures. Our system uses checkpoint/ restart mechanism for fault-tolerance, and provides a easy mechanism to integrate with Grid services widely used in eScience. Additionally, we run rigorous tests using scientific applications to verify that our system can be used in clusters. We also describe improvements made to our system to solve various problems that arose when deploying it on a cluster. The experimental results show that not only does our system conform to various types of running environment well, but that it can also be practically deployed in clusters.

Advances in network technology and computing power have inspired the emergence of high-performance cluster computing systems. While cluster management and hardware highavailability tools are readily available, practical and easily deployable fault-tolerant systems have not been successfully adopted commercially. We present a fault-tolerant system, Multiple fault-tolerant MPI over Myrinet (M3), that differs in notable respects from other proposed fault-tolerant systems in the literature. M3 is built on top of Myrinet since it is regarded as one of the best solutions for highperformance networks and is widely used in cluster computing systems because it can provide a high-speed switching network that is an inevitable ingredient in interconnecting clusters of workstations or PCs. M^3 is a user-transparent checkpointing system for multiple fault-tolerant MPI implementation that is primarily based on the coordinated checkpointing protocol. M3 supports three critical functionalities that are necessary for faulttolerance: a light-weight failure detection mechanism, dynamic process management that includes process migration, and a consistent checkpoint and recovery mechanism. The features of M are that it requires no modifications of application code and that it preserves much of the high performance characteristics of Myrinet. This paper describes the architecture of M3, its detailed design principles and comprehensive implementation issues. We also propose practical solutions for those involved in constructing highly available cluster systems for parallel programming systems. Experimental results substantiate our assertion that M3 can be a good candidate for practically deployable fault-tolerant systems in very-large and high-performance Myrinet clusters and that its protocol can be applied to a wide variety of parallel communication libraries without difficulty.