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Issue title: ISPDC 2010
Article type: Research Article
Authors: Kosar, Tevfik; ; ; | Akturk, Ismail | Balman, Mehmet | Wang, Xinqi;
Affiliations: Department of Computer Science and Engineering, State University of New York, Buffalo, NY, USA | Department of Computer Science, Louisiana State University, Baton Rouge, LA, USA | Center for Computation and Technology, Louisiana State University, Baton Rouge, LA, USA | Department of Computer Engineering, Bilkent University, Ankara, Turkey | Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Note: [] Corresponding author: Tevfik Kosar, Department of Computer Science and Engineering, State University of New York, Buffalo, NY, USA. E-mail: [email protected].
Abstract: Modern collaborative science has placed increasing burden on data management infrastructure to handle the increasingly large data archives generated. Beside functionality, reliability and availability are also key factors in delivering a data management system that can efficiently and effectively meet the challenges posed and compounded by the unbounded increase in the size of data generated by scientific applications. We have developed a reliable and efficient distributed data storage system, PetaShare, which spans multiple institutions across the state of Louisiana. At the back-end, PetaShare provides a unified name space and efficient data movement across geographically distributed storage sites. At the front-end, it provides light-weight clients the enable easy, transparent and scalable access. In PetaShare, we have designed and implemented an asynchronously replicated multi-master metadata system for enhanced reliability and availability, and an advanced buffering system for improved data transfer performance. In this paper, we present the details of our design and implementation, show performance results, and describe our experience in developing a reliable and efficient distributed data management system for data-intensive science.
Keywords: Distributed data storage, metadata management, asynchronous replication, advanced buffer, reliability, performance, data-intensive science, PetaShare
DOI: 10.3233/SPR-2011-0317
Journal: Scientific Programming, vol. 19, no. 1, pp. 27-43, 2011
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