Abstract

File prefetching is an effective technique for improving file access performance. In this paper, we present a file prefetching mechanism that is based on on-line analytic modeling of interesting system events and is transparent to higher levels. The mechanism, incorporated into a client's file cache manager, seeks to build semantic structures that capture the intrinsic correlations between file accesses. It then heuristically uses these structures to represent distinct file usage patterns and exploits them to prefetch files from a file server. We show results of a simulation study and of a working implementation. Measurements suggest that our method can predict future file accesses with an accuracy around 90%, that it can reduce cache miss rate by up to 47% and application latency by up to 40%. Our method imposes little overhead, even under antagonistic circumstances. 1 Introduction This paper reports the effectiveness of a predictive file prefetching technique that operates automat...

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