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VALUETOOLS 2007
INTER-PERF 2007NSTOOLS 2007GAMECOMM 2007SMCTOOLS 2007
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    SMCTOOLS

    1st International ICST Workshop on Tools for solving Structured Markov Chains

    Performance evaluation methodologies based on structured Markov chains have taken a more prominent role over the last two decades. During this time, due to the strong exploitation of the involved structures, the techniques used to assess the performance measures of interest have advanced significan…

    Performance evaluation methodologies based on structured Markov chains have taken a more prominent role over the last two decades. During this time, due to the strong exploitation of the involved structures, the techniques used to assess the performance measures of interest have advanced significantly in terms of their efficiency, while becoming more complex at the same time. This increased complexity often acts as an opposing force to a more wide spread use of these advanced methodologies. Making these novel techniques more accessible via a set of software tools is therefore essential to further promote their integration in the system design.

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    Editor(s): Peter Buchholz (University of Dortmund, Germany) and Tugrul Dayar (Bilkent University, Turkey)
    Publisher
    ICST
    ISBN
    978-963-9799-00-4
    Conference dates
    26th Oct 2007
    Location
    Nantes, France
    Appeared in EUDL
    2011-11-29

    Copyright © 2011–2021 ICST

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    • On the Properties of Acyclic Bilateral Phase Type Distributions

      Research Article in 1st International ICST Workshop on Tools for solving Structured Markov Chains

      András Horváth, Miklós Telek
    • Quantitative analysis of biochemical signalling pathways

      Research Article in 1st International ICST Workshop on Tools for solving Structured Markov Chains

      Jane Hillston
    • Split: a flexible and efficient algorithm to vector-descriptor product

      Research Article in 1st International ICST Workshop on Tools for solving Structured Markov Chains

      Ricardo M. Czekster, Paulo Fernandes, Jean-Marc Vincent, Thais Webber
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