An Automated Approach for CreatingWorkload Models From Server Log Data

Fredrik Abbors, Dragos Truscan, Tanwir Ahmad

    Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

    3 Citations (Scopus)

    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.
    Original languageUndefined/Unknown
    Title of host publicationProceedings of the 9th International Conference on Software Engineering and Application
    EditorsAndreas Holzinger, Therese Libourel, Leszek Maciaszek, Stephen Mellor
    PublisherSCITEPRESS Science And Technology Publications
    Pages14–25
    ISBN (Print)978-989-758-036-9
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    Eventconference; 2014-08-29; 2014-08-31 - Vienna
    Duration: 29 Aug 201431 Aug 2014

    Conference

    Conferenceconference; 2014-08-29; 2014-08-31
    Period29/08/1431/08/14

    Keywords

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

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