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Issue No. 04 - October-December (2010 vol. 7)
ISSN: 1545-5971
pp: 366-380
Shravan Gaonkar , University of Illinois, Urbana-Champaign, Urbana
Kimberly Keeton , Hewlett-Packard Laboratories, Palo Alto
Arif Merchant , Hewlett-Packard Laboratories, Palo Alto
William H. Sanders , University of Illinois, Urbana-Champaign, Urbana
The costs of data loss and unavailability can be large, so businesses use many data protection techniques such as remote mirroring, snapshots, and backups to guard against failures. Choosing an appropriate combination of techniques is difficult because there are numerous approaches for protecting data and allocating resources. Storage system architects typically use ad hoc techniques, often resulting in overengineered expensive solutions or underprovisioned inadequate ones. In contrast, this paper presents a principled automated approach for designing dependable storage solutions for multiple applications in shared environments. Our contributions include search heuristics for intelligent exploration of the large design space and modeling techniques for capturing interactions between applications during recovery. Using realistic storage system requirements, we show that our design tool produces designs that cost up to two times less in initial outlays and expected data penalties than the designs produced by an emulated human design process. Additionally, we compare our design tool to a random search heuristic and a genetic algorithm metaheuristic, and show that our approach consistently produces better designs for the cases we have studied. Finally, we study the sensitivity of our design tool to several input parameters.
Data protection techniques, design space exploration, discrete-event simulation, genetic algorithm, search heuristic, storage system design.

S. Gaonkar, K. Keeton, A. Merchant and W. H. Sanders, "Designing Dependable Storage Solutions for Shared Application Environments," in IEEE Transactions on Dependable and Secure Computing, vol. 7, no. , pp. 366-380, 2008.
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