Author

Lin Lin

Date of Award

2011

Level of Access

Campus-Only Thesis

Degree Name

Master of Science (MS)

Department

Computer Engineering

Advisor

Yifeng Zhu

Second Committee Member

Richard Eason

Third Committee Member

Bruce Segee

Abstract

Random accesses generally impact performance in hard disk drives due to more dramatic mechanical movement. This thesis presents the design, implementation, and evaluation of Hot Random Off-loading (HRO), a self-optimizing hybrid storage system that uses a fast and small SSD as a by-passable cache to hard disks, with a goal to serve a majority of random I/O accesses from the fast SSD. HRO dynamically estimates the performance benefits based on history access patterns, especially the randomness and the hotness, of individual files, and then uses a 0-1 knapsack model to allocate or migrate files between the hard disks and the SSD. HRO can effectively identify files that are more frequently and randomly accessed and place these files on the SSD. We implement a prototype of HRO in Linux and our implementation is transparent to the rest of the storage stack, including applications and file systems. We evaluate its performance by directly replaying three real-world traces on our prototype. These experiments compre-hensively demonstrate HROs effectiveness in improving overall I/O performance.

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