Hierarchical Stochastic Activity Networks: Formal Definitions and Behaviour

Stochastic activity networks (SANs) are a powerful and flexible extension of Petri nets. These models can be used for the modelling and analysis of various kinds and different aspects of distributed real-time systems. Similar to other classical extensions of Petri nets, SANs have some limitations for modelling complex and large-scale systems. In order to remove some of these limitations and provide high-level modelling constructs, we have defined a new extension for SANs, called hierarchical stochastic activity networks (HSANs). HSAN models provide a construct for composing a hierarchy of SAN submodels that is called macro activity. HSANs encapsulate hierarchies and a key benefit of these models is the possibility of automatic selection and usage of techniques for model construction with reduced state spaces by their modelling tools. In this paper, we will present the informal and formal definitions, behaviour and state process of HSANs. We will also introduce methods for the solution of HSAN models by state space analysis and discrete-event simulation techniques.