Abstiact-Interval availability is a dependability measure de-fined by the fraction of thne during which a system is operational over a finite observation period. The computation of its distribu-tion allows the user to ensure that the probability that its system will achieve a given availability level is high enough. The system is assumed to be modeled as a Markov process with countable state space. We propose a new algorithm to compute the interval availability distribution. One of its main advantages is that, in some cases, it applies even to infinite state spaces. This is useful, for instance, in case of models taking into account contention with unbounded buffers. This important feature is illustrated on models of multiprocessor systems ...
Continuous-time Markov chains are commonly used for dependability modeling of repairable fault-toler...
Interval-valued discrete time Markov chains analysis Description Probabilistic model checking is a w...
International audienceThis paper describes how importance sampling can be applied to efficiently est...
Interval availability is a dependability measure defined by the fraction of time during which a syst...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Point availability and expected interval availability are dependability measures respectively define...
Point availability and expected interval availability are dependability measures respectively define...
The paper develops a method, called bounding regenerative transformation, for the computation with ...
Fault-tolerant systems are often modeled using (homogeneous) continuous time Markovchains (CTMCs). C...
Most existing studies of a system’s availability in the presence of epistemic uncertainties assume t...
Performance prediction of checkpointing systems in the presence of failures is a well-studied resear...
Continuous-time Markov chains are commonly used for dependability modeling of repairable fault-toler...
Continuous-time Markov chains are commonly used for dependability modeling of repairable fault-toler...
Interval-valued discrete time Markov chains analysis Description Probabilistic model checking is a w...
International audienceThis paper describes how importance sampling can be applied to efficiently est...
Interval availability is a dependability measure defined by the fraction of time during which a syst...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Interval availability, defined as the fraction of time that a system is operational during a period ...
Point availability and expected interval availability are dependability measures respectively define...
Point availability and expected interval availability are dependability measures respectively define...
The paper develops a method, called bounding regenerative transformation, for the computation with ...
Fault-tolerant systems are often modeled using (homogeneous) continuous time Markovchains (CTMCs). C...
Most existing studies of a system’s availability in the presence of epistemic uncertainties assume t...
Performance prediction of checkpointing systems in the presence of failures is a well-studied resear...
Continuous-time Markov chains are commonly used for dependability modeling of repairable fault-toler...
Continuous-time Markov chains are commonly used for dependability modeling of repairable fault-toler...
Interval-valued discrete time Markov chains analysis Description Probabilistic model checking is a w...
International audienceThis paper describes how importance sampling can be applied to efficiently est...