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

We propose the model of discrete-time probabilistic reward graphs 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 a tailored inclusion of probabilities and
rewards. The approach is applied in an industrial case study of a
turntable drill. The resulting performance measures are shown to be
comparable to those obtained by existent methods of the
chi-environment, viz. simulation and continuous-time Markovian
analysis.