A stochastic approach to file access prediction

Most existing studies of file access prediction are experimental in nature and rely on trace driven simulation to predict the performance of the schemes being investigated. We present a first order Markov analysis of file access prediction, discuss its limitations and show how it can be used to estimate the performance of file access predictors, such as First Successor, Last Successor, Stable Successor and Best-k-out-of-n. We compare these analytical results with experimental measurements performed on several file traces and find out that specific workloads, and indeed individual files, can exhibit very different levels of non-stationarity. Overall, at least 60 percent of access requests appear to remain stable over at least a month.

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