Hot Random Off-Loading: A Hybrid Storage System with Dynamic Data Migration

Random accesses are generally harmful to performance in hard disk drives due to more dramatic mechanical movement. This paper 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. Experiments demonstrate that HRO improves the overall I/O throughput up to 39% and the latency up to 23%.