文件存取预测的随机方法

Jehan-Francois Pâris, A. Amer, D. Long
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引用次数: 17

摘要

大多数现有的文件访问预测研究本质上是实验性的,并且依赖于跟踪驱动模拟来预测所研究方案的性能。我们提出了文件访问预测的一阶马尔可夫分析,讨论了它的局限性,并展示了如何使用它来估计文件访问预测器的性能,如第一后继者,最后后继者,稳定后继者和best -k- of-n。我们将这些分析结果与对几个文件跟踪执行的实验测量结果进行比较,发现特定的工作负载(实际上是单个文件)可能表现出非常不同的非平稳性水平。总体而言,至少60%的访问请求在至少一个月内保持稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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