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Moments analysis in Markov reward models
, 2007
"... HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. appor t de r echerche
Thèmes COM et NUM — Systèmes communicants et Systèmes numériques
"... apport de recherche ISSN 02496399 ISRN INRIA/RR6339FR+ENGMoments analysis in Markov reward models ..."
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apport de recherche ISSN 02496399 ISRN INRIA/RR6339FR+ENGMoments analysis in Markov reward models
of Generalized Stochastic Petri Nets. Its capabilities range from
"... Abstract—MARCIE is a multithreaded tool for the analysis ..."
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The performability tool P’ility
"... The performability distribution is the distribution of accumulated reward in a Markov reward model (MRM) with state reward rates. Since its introduction, several algorithms for the numerical evaluation of the performability distribution have been proposed. Many of these algorithms only solve speci ..."
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The performability distribution is the distribution of accumulated reward in a Markov reward model (MRM) with state reward rates. Since its introduction, several algorithms for the numerical evaluation of the performability distribution have been proposed. Many of these algorithms only solve specialised MRMs, for example, with only 0 and 1 as reward rates or compute the expected value of the accumulated reward. The P’ility tool implements four algorithms that allow for the computation of the performability distribution in its full generality. 1 Performability The concept of performability as the joint evaluation of performance and dependability has been introduced by Meyer in 1980 [5]. One way to evaluate performability uses Markov reward models (MRMs): CTMCs equipped with reward rates. The reward rates represent cost or bonus, or can be employed to mark states (01 rewards). Reward accumulates over time; its distribution Pr{Y (t) 6 y} is also called the performability distribution. Many performability measures are directly derived from this distribution [9]. The performability distribution is described by the set of hyperbolic partial differential equations [6] ∂Υ(t, y)