Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Data management and transfer in high-performance computational grid environments
Parallel Computing - Parallel data-intensive algorithms and applications
Giggle: a framework for constructing scalable replica location services
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Evaluation of an Economy-Based File Replication Strategy for a Data Grid
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
MSS '01 Proceedings of the Eighteenth IEEE Symposium on Mass Storage Systems and Technologies
Simulation of Dynamic Data Replication Strategies in Data Grids
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
An on-line replication strategy to increase availability in Data Grids
Future Generation Computer Systems
The impact of data replication on job scheduling performance in the Data Grid
Future Generation Computer Systems
A survey of dynamic replication strategies for improving data availability in data grids
Future Generation Computer Systems
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The term grid computing refers to the emerging computational and networking infrastructure that is designed to provide pervasive and reliable access to data and computational resources over wide area network, across organizational domains. Grid computing has the potential to support different kinds of applications such as high energy physics, climate simulation astronomy and earth sciences. These applications handle large data sets that need to be used among different grid sites. Data Grids support data-intensive applications in wide area grid systems. To speed up data access, data grid systems replicate data in multiple locations so a user can access the data from a nearby site. The motivation of replication is that replication can improve data availability, data access performance, and load balancing. In this paper a new Dynamic Replication Algorithm (DRA) is proposed. DRA improves data availability by replicating files to different locations within the cluster, where a cluster is a network topological space where the sites are located closely and by storing the replica in the most popular site. Data access performance is increased by minimizing the job execution time and minimizing the network usage. It is implemented by using a data grid simulator, OptorSim Developed by European Data Grid projects.