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
Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs) have been proposed as a fram...
Markov reward models (MRMs) are commonly used for the performance, dependability, and performability...
Markov chains (and their extensions with rewards) have been widely used to determine performance, de...
The performability distribution is the distribution of ac-cumulated reward in a Markov reward model ...
Since the introduction by John F. Meyer in 1980, various algorithms have been proposed to evaluate t...
This paper describes efficient procedures for model checking Markov reward models, that allow us to ...
SIGLECNRS 14802 E / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc
Abstract-We propose, ifl this paper, a new algorithm to compute the performability distribution. Its...
A principal goal of computing system evaluation is the measurement of the system's ability to perfor...
This paper gives a bird's-eye view of the various ingredients that make up a modern, model-checking-...
AbstractContinuous-time Markov processes with a finite-state space are generally considered to model...
Markov-reward models, as extensions of continuous-time Markov chains, have received increased attent...
By combining in a novel way the randomization method with the stationary detection technique, we dev...
In this tutorial, we discuss several practical issues regarding specification and solution of depend...
Markov reward models have interesting modeling applications, particularly those addressing fault-tol...
Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs) have been proposed as a fram...
Markov reward models (MRMs) are commonly used for the performance, dependability, and performability...
Markov chains (and their extensions with rewards) have been widely used to determine performance, de...
The performability distribution is the distribution of ac-cumulated reward in a Markov reward model ...
Since the introduction by John F. Meyer in 1980, various algorithms have been proposed to evaluate t...
This paper describes efficient procedures for model checking Markov reward models, that allow us to ...
SIGLECNRS 14802 E / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc
Abstract-We propose, ifl this paper, a new algorithm to compute the performability distribution. Its...
A principal goal of computing system evaluation is the measurement of the system's ability to perfor...
This paper gives a bird's-eye view of the various ingredients that make up a modern, model-checking-...
AbstractContinuous-time Markov processes with a finite-state space are generally considered to model...
Markov-reward models, as extensions of continuous-time Markov chains, have received increased attent...
By combining in a novel way the randomization method with the stationary detection technique, we dev...
In this tutorial, we discuss several practical issues regarding specification and solution of depend...
Markov reward models have interesting modeling applications, particularly those addressing fault-tol...
Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs) have been proposed as a fram...
Markov reward models (MRMs) are commonly used for the performance, dependability, and performability...
Markov chains (and their extensions with rewards) have been widely used to determine performance, de...