Storage Resource Broker

Storage Resource Broker (SRB) is data grid management computer software used in computational science research projects. SRB is a logical distributed file system based on a client-server architecture which presents users with a single global logical namespace or file hierarchy.[1] Essentially, the software enables a user to use a single mechanism to work with multiple data sources.

Description

SRB provides a uniform interface to heterogeneous computer data storage resources over a network. As part of this, it implements a logical namespace (distinct from physical file names) and maintains metadata on data-objects (files), users, groups, resources, collections, and other items in an SRB metadata catalog (MCAT) stored in a relational database management system.[2] System and user-defined metadata can be queried to locate files based on attributes as well as by name. SRB runs on various versions of Unix, Linux, and Microsoft Windows.

The SRB system is middleware in the sense that it is built on top of other major software packages (various storage systems, real-time data sources, a relational database management system, etc.) and it has callable library functions that can be utilized by higher level software. However, it is more complete than many middleware software systems as it implements a comprehensive distributed data management environment, including various end-user client applications. It has features to support the management and collaborative (and controlled) sharing, publication, replication, transfer, and preservation of distributed data collections.[3]

SRB is sometimes used in conjunction with computational grid computing systems, such as Globus Alliance, and can utilize the Globus Alliance Grid Security Infrastructure (GSI) authentication system.

SRB can store and retrieve data in archival storage systems such as the High Performance Storage System and SAM-FS, on disk file systems (Unix, Linux, or Windows), as binary large objects or tabular data in relational database management systems, and on tape libraries.

SRB was used since 1997. In 2008 the SRB was estimated to be managing over two petabytes of data.

While licensed, SRB source distributions are freely available to academic and non-profit organizations. Nirvana SRB, a commercial version of SRB, featured capabilities specifically adapted to government and commercial use.[4]

History

SRB development began in 1995, through the cooperative efforts of General Atomics, the Data Intensive Cyber Environments Group (DICE), and the San Diego Supercomputer Center (SDSC) at the University of California, San Diego (UCSD) with the support of the National Science Foundation (NSF).

SRB builds on the work of Reagan Moore. Moore, a doctorate in plasma physics from UCSD and former computational plasma physicist at General Atomics, joined the San Diego Supercomputer Center at its inception.[5] A project for a distributed object computation testbed was funded by DARPA and the US Patent and Trademark Office in 1998 and 1999.[6]

In 2003, General Atomics was granted an exclusive license from UCSD to develop SRB for commercial applications.[7] New versions were announced in 2008 and 2012.[8][9]

The integrated Rule-Oriented Data management System (iRODS) is a follow-on project of the SDSC SRB team (which became the Data Intensive Cyber Environments group), and largely replaced the use of SRB. iRODS is based on SRB concepts but was completely re-written, includes a highly-configurable rule engine at its core and is fully open source. Conferences in 2011 included demonstrations of iRODS.[10]

References
  1. "What is the SRB". SRB wiki. 16 May 2006. Archived from the original on 2 July 2013. Retrieved 17 July 2013.
  2. Baru, Chaitanya; Moore, Reagan; Rajasekar, Arcot; Wan, Michael (2010). "The SDSC storage resource broker". CASCON First Decade High Impact Papers: 189–200. CiteSeerX 10.1.1.203.4142. doi:10.1145/1925805.1925816. (Reprint from November 30 – December 3, 1998)
  3. Baru, Chaitanya; Moore, Reagan; Rajasekar, Arcot; Wan, Michael (2010). "The SDSC storage resource broker". CASCON First Decade High Impact Papers: 189–200. CiteSeerX 10.1.1.203.4142. doi:10.1145/1925805.1925816. (Reprint from November 30 – December 3, 1998)
  4. "Nirvana Storage - Home of the Storage Resource Broker (SRB)". web site. Archived from the original on 2008-07-24. Retrieved 17 July 2013.
  5. "San Diego Business Journal", 29 September 2003
  6. "Digging Into Data: Q&A with Reagan Moore". SDSC web site. Archived from the original on 2 July 2013. Retrieved 17 July 2013.
  7. "General Atomics Acquires Exclusive License from UCSD for Commercialization of Unique Data Management Software". Press release. General Atomics. 22 September 2003. Retrieved 17 July 2013.
  8. "General Atomics, Nirvana Division releases SRB 2008". Press release. General Atomics. 29 July 2008. Retrieved 17 July 2013.
  9. "Nirvana SRB 2012 R3® Is Enhanced With Significant Caching Performance, Synchronization and Database Migration Improvements". Press release. General Atomics. 5 November 2012. Retrieved 17 July 2013.
  10. Conway, Mike; Moore, Reagan; Rajasekar, Arcot; Nief, Jean-Yves (2011). Demonstration of Policy-Guided Data Preservation Using iRODS. Proceedings of the 2011 IEEE International Symposium on Policies for Distributed Systems and Networks. pp. 173–174. doi:10.1109/POLICY.2011.17. ISBN 978-0-7695-4330-7.
  • Moore, R. (July 2006). "Building Preservation Environments with Data Grid Technology". American Archivist. 69 (1): 139–158. doi:10.17723/aarc.69.1.176p51l2w5278567.
  • Moore, R.; A. Rajasekar; M. Wan (April 2006). "Storage Resource Broker Global Data Grids". Fourteenth NASA Goddard / Twenty-third IEEE Conference on Mass Storage Systems and Technologies. NASA / IEEE MSST2006.
  • Rajasekar, A.; M. Wan; R. Moore; W. Schroeder (May 2006). "A Prototype Rule-based Distributed Data Management System". HPDC Workshop on Next Generation Distributed Data Management. Paris, France.
  • Rajasekar, A.; M. Wan; R. Moore (March 2009). "Event Processing in Policy Oriented Data Grids". Proceedings of Intelligent Event Processing AAAI Spring Symposium. Stanford, California: 61–66.
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