An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or compu...
William E. Allcock, Joseph Bester, John Bresnahan,...
As the practice of science moves beyond the single investigator due to the complexity of the problems that now dominate science, large collaborative and multi-institutional teams ...
Data replication is a key issue in a Data Grid and can be managed in different ways and at different levels of granularity: for example, at the file level or object level. In the ...
We propose a semi-automated method for redeploying bioinformatic databases indexed in a Web portal as a decentralized, semantically integrated and service-oriented Data Grid. We g...
The UK Department of Trade and Industry (DTI) funded BRIDGES project (Biomedical Research Informatics Delivered by Grid Enabled Services) has developed a Grid infrastructure to su...
Developing Data Grids has increasingly become a major concern to make Grids attractive for a wide range of data-intensive applications. Storage subsystems are most likely to be a ...
Data Grids have been adopted as the next-generation platform by many scientific communities that need to share, access, transport, process and manage large data collections distri...
Replication is a technique used in Data Grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereb...
Data is typically replicated in a Data Grid to improve the job response time and data availability. Strategies for data replication in a Data Grid have previously been proposed, b...