Probabilistic Model Checking for Energy-Utility Analysis

  • Christel Baier
  • Clemens Dubslaff
  • Joachim Klein
  • Sascha Klüppelholz
  • Sascha Wunderlich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8464)


In the context of a multi-disciplinary project, where we contribute with formal methods for reasoning about energy-awareness and other quantitative aspects of low-level resource management protocols, we made a series of interesting observations on the strengths and limitations of probabilistic model checking. To our surprise, the operating-system experts identified several relevant quantitative measures that are not supported by state-of-the-art probabilistic model checkers. Most notably are conditional probabilities and quantiles. Both are standard in mathematics and statistics, but research on them in the context of probabilistic model checking is rare. Another deficit of standard probabilistic model-checking techniques was the lack of methods for establishing properties imposing constraints on the energy-utility ratio.

In this article, we will present formalizations of the above mentioned quantitative measures, illustrate their significance by means of examples and sketch computation methods that we developed in our recent work.


Markov Chain Model Check Markov Decision Process Reward Function Linear Temporal Logic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Christel Baier
    • 1
  • Clemens Dubslaff
    • 1
  • Joachim Klein
    • 1
  • Sascha Klüppelholz
    • 1
  • Sascha Wunderlich
    • 1
  1. 1.Institute for Theoretical Computer ScienceTechnische Universität DresdenGermany

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