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 …

In this paper, we consider the problem of modeling machine availability in enterprise-area
and wide-area distributed computing settings. Using availability data gathered from three …

In the Data Grid environment, the primary goal of data replication is to shorten the data
access time experienced by the job and consequently reduce the job turnaround time. After …

Data replication is a common method used to improve the performance of data access in
distributed systems. In this paper, two dynamic replication algorithms, Simple Bottom-Up …

Storage clusters consisting of thousands of disk drives are now being used both for their
large capacity and high throughput. However, their reliability is far worse than that of smaller …

Data grid technology promises geographically distributed scientists to access and share
physically distributed resources such as compute resource, networks, storage, and most …

In data grid systems, data replication aims to increase availability, fault tolerance, load
balancing and scalability while reducing bandwidth consumption, and job execution time …

Cloud computing has emerged as a promising computational infrastructure for cost-efficient
workflow execution by provisioning on-demand resources in a pay-as-you-go manner. While …

In this paper, we present an algorithm for scheduling of distributed data intensive Bag-of-
Task applications on Data Grids that have costs associated with requesting, transferring and …

To provide performance access to data from high‐energy physics experiments such as the
Large Hadron Collider (LHC), controlled replication of files among grid sites is required …