IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Dynamic replication algorithms for the multi-tier Data Grid
Future Generation Computer Systems - Special issue: Parallel computing technologies
Multiple Job Scheduling in a Connection-Limited Data Parallel System
IEEE Transactions on Parallel and Distributed Systems
A taxonomy of Data Grids for distributed data sharing, management, and processing
ACM Computing Surveys (CSUR)
The impact of data replication on job scheduling performance in the Data Grid
Future Generation Computer Systems
Implications of virtualization on grids for high energy physics applications
Journal of Parallel and Distributed Computing - 19th International parallel and distributed processing symposium
Supporting mobile multimedia applications in MAPGrid
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
Gridification of collaborative audiovisual organizations through the MediaGrid framework
Future Generation Computer Systems
Intelligent data staging with overlapped execution of grid applications
Future Generation Computer Systems
An analytical model for performance evaluation in a computational grid
CHINA HPC '07 Proceedings of the 2007 Asian technology information program's (ATIP's) 3rd workshop on High performance computing in China: solution approaches to impediments for high performance computing
Multi-Replication with Intelligent Staging in Data-Intensive Grid Applications
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Dynamic replication algorithms for the multi-tier Data Grid
Future Generation Computer Systems - Special issue: Parallel computing technologies
The impact of data replication on job scheduling performance in the Data Grid
Future Generation Computer Systems
Emergent algorithms for replica location and selection in data grid
Future Generation Computer Systems
Improving job scheduling performance with parallel access to replicas in Data Grid environment
The Journal of Supercomputing
Heuristic-based scheduling to maximize throughput of data-intensive grid applications
IWDC'04 Proceedings of the 6th international conference on Distributed Computing
A deadline and budget constrained scheduling algorithm for escience applications on data grids
ICA3PP'05 Proceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing
Combining data replication algorithms and job scheduling heuristics in the data grid
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Modeling machine availability in enterprise and wide-area distributed computing environments
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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Data Grid is a Grid environment for ubiquitous access and analysis of large-scale data. Because Data Grid is in the early stages of development, the performance of its petabyte-scale models in a realistic data processing setting has not been well investigated. By enhancing our Bricks Grid simulator to accomodated Data Grid scenarios, we investigate and compare the performance of the different Data Grid models. These are categorized mainly as either central or tier models; they employ various scheduling and replication strategies under realistic assumptions of job processing for CERN LHC experiments on the Grid Datafarm system. Our results show that the central model is efficient but that the tier model, with its greater resources and its speculative class of background replication policies, are quite effective and achieve higher performance, while each tier is smaller than the central model.