Log-structured cache: Trading hit-rate for storage performance (and winning) in mobile devices

Browser caches are typically designed to maximize hit rates - if all other factors are held equal, then the highest hit rate will result in the highest performance. However, if the performance of the underlying cache storage (i.e. the file system) varies with differing workloads, then these other factors may in fact not be equal when comparing different cache strategies. Mobile systems such as smart phones are typically equipped with low-speed flash storage, and suffer severe degradation in file system performance under sufficiently random write workloads. A cache implementation which performs random writes will thus spend more time reading and writing its cache, possibly resulting in lower overall system performance than a lower-hit-rate implementation which achieves higher storage performance. We present a log-structured browser cache, generating almost purely sequential writes, and in which cleaning is efficiently performed by cache eviction. An implementation of this cache for the Chromium browser on Android was developed; using captured user browsing traces we test the log-structured cache and compare its performance to the existing Chromium implementation. We achieve a ten-fold performance improvement in basic cache operations (as measured on a Nexus 7 tablet), while in the worst case increasing miss rate by less than 3% (from 65% to 68%). For network bandwidths of 1Mb/s or higher the increased cache performance more than makes up for the decrease in hit rate; the effect is more pronounced when examining 95^th percentile delays.