Learn More
Emerging high-performance applications require the ability to exploit diverse, geographically distributed resources. These applications use high-speed networks to integrate supercomputers, large databases, archival storage devices, advanced visualiza-tion devices, and/or scientiic instruments to form networked virtual supercomputers or metacomputers. While(More)
“Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high performance orientation. In this article, the authors define this new field. First, they review the “Grid problem,” which is defined as flexible, secure,(More)
State-of-the-art and emerging scientiic applications require fast access to large quantities of data and commensurately fast computational resources. Both resources and data are often distributed in a wide-area network with components administered locally and independently. Computations may involve hundreds of processes that must be able to acquire(More)
Grid technologies enable large-scale sharing of resources within formal or informal consortia of individuals and/or institutions: what are sometimes called virtual organizations. In these settings, the discovery, characterization , and monitoring of resources, services, and computations can be challenging due to the considerable diversity , large numbers,(More)
Metacomputing systems are intended to support remote and/or concurrent use of geographically distributed computational resources. Resource management in such systems is complicated by ve concerns that do not typically arise in other situations: site autonomy and heterogeneous substrates at the resources, and application requirements for policy(More)
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 which resources for which purpose. We propose a new approach to the representation, maintenance, and enforcement of such policies that provides a scalable mechanism for(More)
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 an abstract level without needing to worry about the particulars of the target execution systems. The paper describes general issues in mapping applications and the functionality of(More)
In an increasing number of scientific disciplines, large data collections are emerging as important community resources. In this paper, we introduce design principles for a data management architecture called the data grid. We describe two basic services that we believe are fundamental to the design of a data grid, namely, storage systems and metadata(More)
Grid computing is concerned with the sharing and coordinated use of diverse resources in distributed "virtual organizations. " The dynamic and multi-institutional nature of these environments introduces challenging security issues that demand new technical approaches. In particular, one must deal with diverse local mechanisms, support dynamic creation of(More)