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In both e-business and e-science, we often need to integrate services across distributed, heterogeneous, dynamic " virtual organizations " formed from the disparate resources within a single enterprise and/or from external resource sharing and service provider relationships. This integration can be technically challenging because of the need to achieve(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)
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)
In recent years, there has been a dramatic increase in the amount of available computing and storage resources. Yet f e w have been able to exploit these resources in an aggregated form. We present the Condor-G system, which leverages software from Globus arid Condor to allow users to harness multi-domain resources as if they all belong to one personal(More)
An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or computed data. Such applications arise, for example, in experimental physics, where the data in question is generated by accelerators, and in simulation science, where the data is(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)