xxx Mining-based File Caching in a Hybrid Storage System

In this work, we propose a new mining-based file caching scheme for a hybrid storage disk system. In particular, we focus our efforts on reducing the latency of launching applications. The proposed scheme identifies the correlated file accesses in a file access sequence via sequential pattern mining algorithm. Our scheme caches corre-lated files together to maximize the caching efficiency. The correlated files are extracted from the access patterns through the proposed mining scheme, which consists of three steps: frequent pattern based file extraction, cluster moving gap based file sort, and fre-quency and size based file prioritization. The extracted correlated files are relocated to a SSD during idle time. DiskSim and NANDSim are used to evaluate the proposed scheme, called Informed Mining. The proposed scheme is compared with a disk only scheme and five other mining based file relocation schemes: Mining based file reloca-tion scheme (Miner), minimum distance based file relocation scheme (Min_Dist), fre-quency-based relocation scheme (Fre), size-based relocation scheme (Size), and one that relocates files with highest value of (file size * file access number) first to the SSD (Fr*Sz). From the simulation based experiment, launch time is reduced by about 50% using only 10 % of sum of all file sizes accessed during a launch of an application