Using Utility to Provision Storage Systems

6th USENIX Conference on File and Storage Technologies (FAST '08). Feb. 26-29, 2008. San Jose, CA. Supercedes Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-07-106, September 2007.

John D. Strunk, Eno Thereska, Christos Faloutsos, Gregory R. Ganger

School of Computer Science
Dept. Electrical and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA 15213

Provisioning a storage system requires balancing the costs of the solution with the benefits that the solution will provide. Previous provisioning approaches have started with a fixed set of requirements and the goal of automatically finding minimum cost solutions to meet them. Those approaches neglect the cost-benefit analysis of the purchasing decision. Purchasing a storage system involves an extensive set of trade-offs between metrics such as purchase cost, performance, reliability, availability, power, etc. Increases in one metric have consequences for others, and failing to account for these trade-offs can lead to a poor return on the storage investment. Using a collection of storage acquisition and provisioning scenarios, we show that utility functions enable this cost-benefit structure to be conveyed to an automated provisioning tool, enabling the tool to make appropriate trade-offs between different system metrics including performance, data protection, and purchase cost.

KEYWORDS: utility, storage provisioning, utility-based provisioning, cluster-based storage, genetic algorithms

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