# Transient analysis of networks of stochastic timed automata using stochastic state classes

## P. Ballarini, N. Bertrand, A. Horváth, M. Paolieri, E. Vicario

**Abstract:** Stochastic Timed Automata (STA) associate logical locations with
continuous, generally distributed sojourn times. In this paper, we
introduce Networks of Stochastic Timed Automata (NSTA), where the
components interact with each other by message broadcasts. This
results in an underlying stochastic process whose state is made of the
vector of logical locations, the remaining sojourn times, and the
value of clocks. We characterize this general state space Markov
process through transient stochastic state classes that sample the
state and the absolute age after each event. This provides an
algorithmic approach to transient analysis of NSTA models, with fairly
general termination conditions which we characterize with respect to
structural properties of individual components that can be checked
through straightforward algorithms.

Stochastic ProcessesTheory

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