Aggregation of stochastic automata networks with replicas

Aggregation of stochastic automata networks with replicas

We present techniques for computing the solution of large Markov chain models whose generators can be represented in the form of a generalized tensor algebra, such as Stochastic Automata Networks (SAN). Many large systems include a number of replications of identical components. This paper exploits replication by aggregating similar components. This leads to a state space reduction, based on lu...

Stochastic Automata Networks

Preconditioning for Stochastic Automata Networks

LANGVILLE, AMY N. Preconditioning for Stochastic Automata Networks. (Under the direction of William J. Stewart.) Many very large Markov chains can be modeled efficiently as Stochastic Automata Networks (SANs). A SAN is composed of individual automata that, for the most part, act independently, requiring only infrequent interaction. SANs represent the generator matrix Q of the underlying Markov ...

Stochastic Automata Networks ( SAN ) - Modellingand

This article describes the use of Stochastic Automata Networks (SAN) as a modelling tool. A SAN model consists of some individual stochastic automata that act more or less independently of each other. An automata is represented by a number of states and probabilistic rules that govern the manner in which it moves from one state to the next. The state of a SAN is given by the state of each of it...

Modeling Finite Capacity Queueing Networks with Stochastic Automata Networks