An Automated Approach for CreatingWorkload Models From Server Log Data

A4 Conference proceedings


Internal Authors/Editors


Publication Details

List of Authors: Fredrik Abbors, Dragos Truscan, Tanwir Ahmad
Editors: Andreas Holzinger, Therese Libourel, Leszek Maciaszek, Stephen Mellor
Place: scitepress.org
Publication year: 2014
Publisher: SCITEPRESS Science And Technology Publications
Book title: Proceedings of the 9th International Conference on Software Engineering and Application
Start page: 14
End page: 25
ISBN: 978-989-758-036-9


Abstract

We present a tool-supported approach for creating workload models from historical web access log data. The
resulting workload models are stochastic, represented as Probabilistic Timed Automata (PTA), and describe
how users interact with the system. Such models allow one to analyze different user profiles and to mimic
real user behavior as closely as possible when generating workload. We provide an experiment to validate the
approach.
We present a tool-supported approach for creating workload models from historical web access log data. The resulting workload models are stochastic, represented as Probabilistic Timed Automata (PTA), and describe how users interact with the system. Such models allow one to analyze different user profiles and to mimic real user behavior as closely as possible when generating workload. We provide an experiment to validate the approach.


Keywords

Log file analysis, Performance testing, Probabilistic Timed Automata, Workload model generation,


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Last updated on 2019-18-10 at 02:44