N. Trcka, S. Georgievska, J. Markovski, S. Andova and E.P. de Vink
Performance Analysis of Chi Models using Discrete-Time Probabilistic 
Reward Graphs

We propose the model of discrete-time probabilistic reward graphs (TPRGs) for
performance analysis of systems exhibiting discrete deterministic time delays
and probabilistic behavior, via their interpretation as discrete-time Markov
reward chains.  We build on the Chi-environment, a full-fledged platform for
qualitative and quantitative analysis of timed systems based on the modeling
language Chi. The extension proposed in this paper is based on timed branching
bisimulation reduction followed by inclusion of probabilities and rewards. The
approach is applied in an industrial case study of a turntable drilling system.
The resulting performance measures are shown to be comparable to those obtained
by two other methods of the Chi-environment, viz. simulation and
continuous-time Markovian analysis.