  The Globus Data Grid architecture provides a scalable infrastructure for the
management of storage resources and data that are distributed across Grid
environments. These services are designed to support a variety of scientific
applications, ranging from high-energy physics to computational genomics, that
require access to large amounts of data (terabytes or even petabytes) with
varied quality of service requirements. By layering on a set of core services,
such as data transport, security, and replica cataloging, one can construct
various higher-level services. In this paper, we discuss the design and
implementation of a high-level replica selection service that uses information
regarding replica location and user preferences to guide selection from among
storage replica alternatives. We first present a basic replica selection
service design, then show how dynamic information collected using Globus
information service capabilities concerning storage system properties can help
improve and optimize the selection process. We demonstrate the use of Condor's
ClassAds resource description and matchmaking mechanism as an efficient tool
for representing and matching storage resource capabilities and policies
against application requirements.
