Giggle: a framework for constructing scalable replica location services
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
MSS '01 Proceedings of the Eighteenth IEEE Symposium on Mass Storage Systems and Technologies
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
A Peer-to-Peer Replica Location Service Based on a Distributed Hash Table
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Replica Placement in Data Grid: Considering Utility and Risk
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01
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One of the challenges in data replication is to select the candidate sites to place replicas. We use the p-median and p-center models to address the replica placement problem. In our problem, the p-median model finds the locations of p candidate sites to place a replica to optimize the total (or average) response time. The p-center model hosts replicas to p candidate sites by minimizing the maximum response time among sites. A Grid environment is highly dynamic so placing a replica by considering one objective, i.e., optimize average response time or optimize maximum response time, may not be always a good choice. We propose a multi-objective model that considers the objectives of p-median and p-center simultaneously to select the candidate sites that will host replicas. Simulation results demonstrate that the multi-objective model outperforms single objective models in dynamic environments such as Data Grids.