A generally applicable discretization method for computing the transient distribution of the cumulative reward in a continuous-time Markov chain is presented. A key feature of the algorithm is an error estimate for speeding up the calculations. The algorithm is easy to program and is numerically stable
Today many formalisms exist for specifying complex Markov chains. In contrast, formalisms for specif...
International audienceIn this paper we study the numerical approximation of the optimal long-run ave...
International audienceWe analyze the moments of the accumulated reward over the interval (0,t) in a ...
Markov reward models have interesting modeling applications, particularly those addressing fault-tol...
Abstract—Rewarded homogeneous continuous-time Markov chain (CTMC) models can be used to analyze perf...
In this thesis, the problem of computing the cumulative distribution function (cdf) of the random ti...
Rewarded homogeneous continuous-time Markov chain (CTMC) models can be used to analyze performance, ...
By combining in a novel way the randomization method with the stationary detection technique, we dev...
Abstract.The computation of transient probabilities for continuous-time Markov chains often employs ...
In this paper we generalize a method (called regenerative randomization) for the transient solution ...
Randomization is a well-known numerical method for the transient analysis of continuous-time Markov ...
We analyze the moments of the accumulated reward over the interval (0, t) in a continuous-time Marko...
This thesis attempts to bring together two different approaches to the modeling of event driven syst...
Best Paper Award, 7th. International Conference on Peformance Evaluation methodologies and tools, Va...
Today many formalisms exist for specifying complex Markov chains. In contrast, formalisms for specif...
International audienceIn this paper we study the numerical approximation of the optimal long-run ave...
International audienceWe analyze the moments of the accumulated reward over the interval (0,t) in a ...
Markov reward models have interesting modeling applications, particularly those addressing fault-tol...
Abstract—Rewarded homogeneous continuous-time Markov chain (CTMC) models can be used to analyze perf...
In this thesis, the problem of computing the cumulative distribution function (cdf) of the random ti...
Rewarded homogeneous continuous-time Markov chain (CTMC) models can be used to analyze performance, ...
By combining in a novel way the randomization method with the stationary detection technique, we dev...
Abstract.The computation of transient probabilities for continuous-time Markov chains often employs ...
In this paper we generalize a method (called regenerative randomization) for the transient solution ...
Randomization is a well-known numerical method for the transient analysis of continuous-time Markov ...
We analyze the moments of the accumulated reward over the interval (0, t) in a continuous-time Marko...
This thesis attempts to bring together two different approaches to the modeling of event driven syst...
Best Paper Award, 7th. International Conference on Peformance Evaluation methodologies and tools, Va...
Today many formalisms exist for specifying complex Markov chains. In contrast, formalisms for specif...
International audienceIn this paper we study the numerical approximation of the optimal long-run ave...
International audienceWe analyze the moments of the accumulated reward over the interval (0,t) in a ...
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