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On Developing Data Grid Workflows using Storage Resource Broker (SRB) and Kepler

This document explores the development of data grid workflows using the Storage Resource Broker (SRB) and Kepler. Key features include the logical namespace that ensures location and protocol transparency, support for data federation across multiple administrative domains, and metadata cataloging via MCAT, which enhances data discoverability. The integration of container support allows for bulk replication and transfer of data, while APIs such as InQ, SCommand, and others facilitate seamless data operations. Ideal for researchers looking to automate data flow within diverse computational environments.

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On Developing Data Grid Workflows using Storage Resource Broker (SRB) and Kepler

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  1. On Developing Data Grid Workflows using Storage Resource Broker (SRB) and Kepler Tim H. Wong - UC Davis Efrat Frank - SDSC Bertram Ludäscher - UC Davis

  2. Users MCAT Windows FS Unix FS Unix FS Unix FS SDSC Storage Resource Broker • Logical Namespace. Provides location and protocol transparency • Federation Support (Zone SRB). Support multiple administrative domains and data integration. • Metadata catalog (MCAT). Allows users to find information using metadata. • Container. Support bulk replicate and transfer. • API: InQ, SCommand, Matrix, Kepler MCAT UC Davis Zone SDSC Zone

  3. DB2 DB2 Users Processing Publishing Windows FS Unix FS Unix FS Unix FS Unix FS Oracle Data Grid Workflows with Kepler • Design and implement the automation of data flow using Kepler SRB actors and PN / SDF director Retrieving

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