Data grid is a distributed collection of storage and computational resources that are not
bounded within a geophysical location. It is a fast growing area of research and providing …

One major challenge in data grids is how to provide good and timely access to huge amount
of data in distributed locations, given the high latency of interconnection networks. Dynamic …

Replicating for performance constitutes an important issue in large–scale data management
systems. In this context, a significant number of replication strategies have been proposed …

Grid Computing is a type of parallel and distributed systems that is designed to provide
reliable access to data and computational resources in wide area networks. These …

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

Data replication is the creation and maintenance of multiple copies of the same data.
Replication is used in Data Grid to enhance data availability and fault tolerance. One of the …

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 …

Grid computing is emerging as a key part of the infrastructure for a wide range of disciplines
in science and engineering, including astronomy, high energy physics, molecular biology …

Data replication is used in Data Grid to enhance data availability and fault tolerance.
However, replication should be used wisely because the storage size of each node reside …

In data grids, data replication on variant nodes can change some problems such as
response time and availability. Also, in data replication, there are some challenges to finding …