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.
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horvath
2014-09-17