Small is big: Functionally partitioned file caching in virtualized environments

Abstract

File cache management is among the most important factors affecting the performance of a cloud computing system. To achieve higher economies of scale, virtual machines are often overcommitted, which creates high memory pressure. Thus it is essential to eliminate duplicate data in the host and guest caches to boost performance. Existing cache deduplication solutions are based on complex algorithms, or incur high runtime overhead, and therefore are not widely applicable. In this paper we present a simple and lightweight mechanism based on functional partitioning. In our mechanism, the responsibility of each cache becomes smaller: the host only caches data in base images and a VM guest only caches its own “private data”, which is generated after the VM has started. As a result, the overall effective cache size becomes bigger. Our method requires very small change to existing software (15 lines of new/modified code) to achieves big performance improvements - more than 40% performance gains in high memory pressure settings.