In data grids, many distributed scientific and engineering applications often require access
to a large amount of data (terabytes or petabytes). Data access time depends on bandwidth …

Scientific applications require sophisticated data management capabilities. We present the
Data Replication Service (DRS), one of a planned set of higher-level data management …

DIRAC (distributed infrastructure with remote agent control) has been developed by the
CERN LHCb physics experiment to facilitate large scale simulation and user analysis tasks …

Distributed computing systems employ replication to improve overall system robustness,
scalability, and performance. A replica location service (RLS) offers a mechanism to …

In data-intensive distributed systems, replication is the most widely used approach to offer
high data availability, low bandwidth consumption, increased fault-tolerance and improved …

A Data Grid is a wide area computing infrastructure that employs Grid technologies to
provide storage capacity and processing power to applications that handle very large …

Grid technology offers the potential for providing secure access to remote services, thereby
promoting scientific collaborations in an unprecedented scale. Grid Resource Management …

Data replication is one of the best known strategies to achieve high levels of availability and
fault tolerance, as well as minimal access times for large, distributed user communities using …

The vision of Grid computing is to facilitate worldwide resource sharing among distributed
collaborations. With the help of numerous national and international Grid projects, this vision …

Peer-to-peer systems offer attractive system management properties, including the ability of
components that join the network to self-organize; scalability up to tens of thousands of …