DRIVE: Using implicit caching hints to achieve disk I/O reduction in virtualized environments

Abstract

Co-hosting of virtualized applications results in similar content across multiple blocks on disk, which are fetched into memory (the host's page cache). Content similarity can be harnessed both to avoid duplicate disk I/O requests that fetch the same content repeatedly, as well as to prevent multiple occurrences of duplicate content in cache. Typically, caches store the most recently or frequently accessed blocks to reduce the number of disk read accesses. These caches are referenced by block number, and can not recognize content similarity across multiple blocks. Existing work in memory deduplication merges cache pages after multiple identical blocks have already been fetched from disk into cache, while existing work in I/O deduplication reserves a portion of the host-cache to be maintained as a content-aware cache. We propose a disk I/O reduction system for the virtualization environment that addresses the dual problems of duplicate I/O and duplicate content in the host-cache, without being invasive. We build a disk read-access optimization called DRIVE, that identifies content similarity across multiple blocks, and performs hint-based read I/O redirection to improve cache effectiveness, thus reducing the number of disk reads further. A metadata store is maintained based on the virtual machine's disk accesses and implicit caching hints are collected for future read I/O redirection. The read I/O redirection is performed from within the virtual block device in the virtualized system, to manipulate the entire host-cache as a content-deduplicated cache implicitly. Our trace-based evaluation using a custom simulator, reveals that DRIVE always performs equal to or better than the Vanilla system, achieving up to 20% better cache-hit ratios and reducing the number of disk reads by up to 80%. The results also indicate that our system is able to achieve up to 97% content deduplication in the host-cache.