Fat-trees: universal networks for hardware-efficient supercomputing
IEEE Transactions on Computers
Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Simulation of Dynamic Grid Replication Strategies in OptorSim
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Giggle: a framework for constructing scalable replica location services
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
A Decentralized, Adaptive Replica Location Mechanism
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Data Replication Strategies in Grid Environments
ICA3PP '02 Proceedings of the Fifth International Conference on Algorithms and Architectures for Parallel Processing
Evaluating Scheduling and Replica Optimisation Strategies in OptorSim
GRID '03 Proceedings of the 4th International Workshop on Grid Computing
A Peer-to-Peer Replica Location Service Based on a Distributed Hash Table
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Emergent algorithms for replica location and selection in data grid
Future Generation Computer Systems
A Decentralized Deployment Strategy and Performance Evaluation of LCG File Catalog Service
Journal of Grid Computing
Replica creation strategy based on quantum evolutionary algorithm in data gird
Knowledge-Based Systems
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Data grid replication is critical for improving the performance of data intensive applications. Most of the used techniques for data replication use Replica Location Services (RLS) to resolve the logical name of files to its physical locations. An example of such service is Giggle, which can be found in the OGSA/Globus architecture. Classical algorithms also need some catalog and optimization services. For example, the EGEE DataGrid project, based in Globus open source components, implements for this purpose the Replica Optimization Service (ROS) and the Replica Metadata Catalog (RMC). In this paper we propose a new approach for improving the performance of Data grid replication. With this aim, we apply Emergent Artificial Intelligence (EAI) techniques to data replication. The paper describes a new algorithm for replica selection in grid environments based on a PSO-LRU (Particle Swarm Optimization) approach. For evaluating this technique we have implemented a grid simulator called SiCoGrid. The simulation results presented in the paper demonstrate that the new technique improve the performance compared with traditional solutions.