Text compression
File and Object Replication in Data Grids
Cluster Computing
Identifying Dynamic Replication Strategies for a High-Performance Data Grid
GRID '01 Proceedings of the Second International Workshop on Grid Computing
The Case for Efficient File Access Pattern Modeling
HOTOS '99 Proceedings of the The Seventh Workshop on Hot Topics in Operating Systems
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Complete and fragmented replica selection and retrieval in Data Grids
Future Generation Computer Systems
Popularity-Driven Dynamic Replica Placement in Hierarchical Data Grids
PDCAT '08 Proceedings of the 2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies
Future Generation Computer Systems
Dynamic replication algorithms for the multi-tier Data Grid
Future Generation Computer Systems - Special issue: Parallel computing technologies
The complexity of static data replication in data grids
Parallel Computing
FIRE: A File Reunion Based Data Replication Strategy for Data Grids
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Dynamic replication in a data grid using a Modified BHR Region Based Algorithm
Future Generation Computer Systems
PHFS: A dynamic replication method, to decrease access latency in the multi-tier data grid
Future Generation Computer Systems
Algorithms for automatic data replication in grid environment
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
Enhanced Dynamic Hierarchical Replication and Weighted Scheduling Strategy in Data Grid
Journal of Parallel and Distributed Computing
Job scheduling and dynamic data replication in data grid environment
The Journal of Supercomputing
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In recent years, grid technology has had such a fast growth that it has been used in many scientific experiments and research centers. A large number of storage elements and computational resources are combined to generate a grid which gives us shared access to extra computing power. In particular, data grid deals with data intensive applications and provides intensive resources across widely distributed communities. Data replication is an efficient way for distributing replicas among the data grids, making it possible to access similar data in different locations of the data grid. Replication reduces data access time and improves the performance of the system. In this paper, we propose a new dynamic data replication algorithm named PDDRA that optimizes the traditional algorithms. Our proposed algorithm is based on an assumption: members in a VO (Virtual Organization) have similar interests in files. Based on this assumption and also file access history, PDDRA predicts future needs of grid sites and pre-fetches a sequence of files to the requester grid site, so the next time that this site needs a file, it will be locally available. This will considerably reduce access latency, response time and bandwidth consumption. PDDRA consists of three phases: storing file access patterns, requesting a file and performing replication and pre-fetching and replacement. The algorithm was tested using a grid simulator, OptorSim developed by European Data Grid projects. The simulation results show that our proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, effective network usage, total number of replications, hit ratio and percentage of storage filled.