Computer Science Department
School of Computer Science, Carnegie Mellon University


A Two-Tiered Software Architecture for
Automated Tuning of Disk Layouts

Brandon Salmon*, Eno Thereska*, Craig A.N. Soules, Gregory R. Ganger

April 2003

This reports has also appeared in the
First Workshop on Algorithms and Architectures for Self-Managing Systems,
in conjunction with the Federated Computing Research Conference (FCRC),
San Diego, CA. June 11, 2003.

Keywords: Disk layout, adaptive, self-managing, self-tuning, learning, automated tuning

Many heuristics have been developed for adapting on-disk data layouts to expected and observed workload charac-teristics. This paper describes a two-tiered software architecture for cleanly and extensibly combining such heuristics. In this architecture, each heuristic is implemented independently and an adaptive combiner merges their suggestions based on how well they work in the given environment. The result is a simpler and more robust system for automated tuning of disk layouts, and a useful blueprint for other complex tuning problems such as cache management, scheduling, data migration, and so forth.

12 pages

*Department of Electrical and Computer Engineering, Carnegie Mellon University

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