A Two-Tiered Software Architecture for Automated Tuning of Disk Layouts
First Workshop on Algorithms and Architectures for Self-Managing Systems. In conjunction with Federated Computing Research Conference (FCRC). San Diego, CA. June 11, 2003. Supercedes Carnegie Mellon University SCS Technical Report CMU-CS-03-130.
Brandon Salmon, Eno Thereska, Craig A. N. Soules, Gregory R. Ganger
Dept. Electrical and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA 15213
Many heuristics have been developed for adapting on-disk data layouts to expected and observed workload characteristics. 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.
KEYWORDS: disk layout, adaptive, self-managing, self-tuning, learning, automated tuning