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 …

“Grid” computing has emerged as an important new field, distinguished from conventional
distributed computing by its focus on large-scale resource sharing, innovative applications …

This paper describes the Pegasus framework that can be used to map complex scientific
workflows onto distributed resources. Pegasus enables users to represent the workflows at …

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

A lot of scientific data is not obtained from measurements but rather derived from other data
by the application of computational procedures. We hypothesize that explicit representation …

In this paper we describe the Pegasus system that can map complex workflows onto the
Grid. Pegasus takes an abstract description of a workflow and finds the appropriate data and …

In this paper we address the problem of automatically generating job workflows for the Grid.
These workflows describe the execution of a complex application built from individual …

In" grids" and" collaboratories", we find distributed communities of resource providers and
resource consumers, within which often complex and dynamic policies govern who can use …

We advocate a novel approach to grid computing that is based on a combination of" classic"
operating system level virtual machines (VMs) and middleware mechanisms to manage VMs …

Todays scientific applications have huge data requirements which continue to increase
drastically every year. These data are generally accessed by many users from all across the …