Deriving performance-relevant infrastructure properties through model-based experiments with Ginpex

Autor(en)
Michael Hauck and Michael Kuperberg and Nikolaus Huber and Ralf Reussner
Zeitschrift
Software & Systems Modeling
Jahr
2013
Seiten
1-21
Verlag
Springer-Verlag
Abstract
To predict the performance of an application, it is crucial to consider the performance of the underlying infrastructure. Thus, to yield accurate prediction results, performance-relevant properties and behaviour of the infrastructure have to be integrated into performance models. However, capturing these properties is a cumbersome and error-prone task, as it requires carefully engineered measurements and experiments. Existing approaches for creating infrastructure performance models require manual coding of these experiments, or ignore the detailed properties in the models. The contribution of this paper is the Ginpex approach, which introduces goal-oriented and model-based specification and generation of executable performance experiments for automatically detecting and quantifying performance-relevant infrastructure properties. Ginpex provides a metamodel for experiment specification and comes with predefined experiment templates that provide automated experiment execution on the target platform and also automate the evaluation of the experiment results. We evaluate Ginpex using three case studies, where experiments are executed to quantify various infrastructure properties.
Link
http://dx.doi.org/10.1007/s10270-013-0335-7
DOI
10.1007/s10270-013-0335-7
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Eingetragen von
Ralf Reussner