In data grids scientific and business applications produce huge volume of data which needs
to be transferred among the distributed and heterogeneous nodes of data grids. Data …

With the development of grid computing, Data Grid, as an important branch of Grid
Computing focuses on supporting an efficient management mechanism for controlled …

Data replication techniques are used in data grid to reduce makespan, storage
consumption, access latency and network bandwidth. Data replication enhances data …

Data grids deal with a huge amount of data regularly. It is a fundamental challenge to ensure
efficient accesses to such widely distributed data sets. Creating replicas to a suitable site by …

The data grid technology, which uses the scale of the Internet to provide storage capability
for the mass data, has become one of the hot research topics. The high latency of the …

The term grid computing refers to the emerging computational and networking infrastructure
that is designed to provide pervasive and reliable access to data and computational …

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 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, but …

Summary In Data Grid systems, quick data access is a challenging issue due to the high
latency. The failure of requests is one of the most common matters in these systems that has …

In recent years data grids have been deployed and grown in many scientific experiments
and data centers. The deployment of such environments has allowed grid users to gain …