Modeling file-system input traces via a two-level arrival process

Abstract

A method for analyzing, modeling and simulating a two-level arrival-counting process is presented. ThM method is particularly appropriate when the number of independent processes is large. The initial motivation for th~method was the need to analyze and represent computer file system trace data that involves activity on some 8,000 files. The method is also applicable to network trace data characterizing communication patterns between pairs of computers.Cluster analysis with a novel stopping rule is used to decompose the arrival process into groups.The resulting clusters can be characterized using the time between clusters, the time between arrivals within clusters, and the size of each cluster.Each of these three components is then analyzed as a univariate problem.The effectiveness of this method is measured by comparing the output of a simulation driven by the original trace data to the output of the same simulation driven by the input model.

Autonomic Storage System Based on Automatic Learning

“…With regard to application model, some works have been proposed in characterizations and modeling of I/O access pattern [9][10][11][12][13][14]. Most of these studies were made at the file system level.…”

Numerical Methods for Fitting and Simulating Autoregressive-to-Anything Processes

“…For example, the sizes of the demands on an inventory system in successive periods are often dependent because a large demand in one period implies that fewer items will be needed in the following period. Ware et al [13] observed that the times between file accesses on a computer network frequently exhibit burstiness, as characterized by a sequence of short interaccess times followed by one or more long ones. Similarly, Melamed et al [9] observed autocorrelation in sequences of compressed video frame bitrates.…”