Data access latency is an important metric of system performance in data grid. By means of
efficient replication strategy, the amount of data transferred in a wide area network will …

Data grids provide distributed resources for dealing with large scale applications generating
huge volume of data that require to be efficiently managed, shared and analyzed. Data …

Data grid deals with data intensive applications, and provides the ability to access and
manage data intensive resources across widely distributed communities. Data replication …

Data grids provide large-scale geographically distributed data resources for data intensive
applications such as high energy physics and bioinformatics. Optimizing the use of data …

We propose a novel approach called Fair-Share Replication (FSR) to balance the work load
and storage resource usage of the replica servers in data grid. The approach takes into …

Dealing with a large amount of data makes the requirement for efficient data accesses more
critical in data grid. Through improving performance of data replication, job execution cost is …

One of the challenges for data replication in a Data Grid is to select the candidate sites that
will host the replicas of datasets. In our earlier research (Rahman et al., 2006, May; Rahman …

In data grid environments data-intensive applications require large amounts of data to
execute. Data transfer is a primary cause of job execution delay. In this paper we study smart …

The distributed and dynamic nature of grids present a number of challenging problems
distinguished from conventional distributed computing by its focus on large-scale resource …

Replication is a technique used in Data Grid environments that helps to reduce access
latency and network bandwidth utilization. Replication also increases data availability …