Measurement and dynamical analysis of computer performance data

Authors:
Zachary Alexander;Todd Mytkowicz;Amer Diwan;Elizabeth Bradley
Affiliations:
University of Colorado, Boulder, CO;University of Colorado, Boulder, CO;University of Colorado, Boulder, CO;University of Colorado, Boulder, CO
Venue:
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
Year:
2010

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Abstract

In this paper we give a detailed description of a new methodology—nonlinear time series analysis—for computer performance data. This methodology has been used successfully in prior work [1,9]. In this paper, we analyze the theoretical underpinnings of this new methodology as it applies to our understanding of computer performance. By doing so, we demonstrate that using nonlinear time series analysis techniques on computer performance data is sound. Furthermore, we examine the results of blindly applying these techniques to computer performance data when we do not validate their assumptions and suggest future work to navigate these obstacles.