An Automated Approach for CreatingWorkload Models From Server Log Data

A4 Konferenspublikationer


Interna författare/redaktörer


Publikationens författare: Fredrik Abbors, Dragos Truscan, Tanwir Ahmad
Redaktörer: Andreas Holzinger, Therese Libourel, Leszek Maciaszek, Stephen Mellor
Förlagsort: scitepress.org
Publiceringsår: 2014
Förläggare: SCITEPRESS Science And Technology Publications
Moderpublikationens namn: Proceedings of the 9th International Conference on Software Engineering and Application
Artikelns första sida, sidnummer: 14
Artikelns sista sida, sidnummer: 25
ISBN: 978-989-758-036-9


Abstrakt

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.


Nyckelord

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


Dokument


Senast uppdaterad 2020-02-04 vid 08:12