Petri nets with discrete phase timing: A bridge between stochastic and functional analysis

The addition of timing specification in Petri Nets (PN) has followed two main lines: intervals for functional analysis or stochastic durations for performance and dependability analysis. The present paper proposes a novel technique to analyze time or stochastic PN models based on discretization. This technique can be seen as a bridge between the world of functional analysis and the world of stochastic analysis. The proposed discretization technique is based on the definition of a new construct called Discrete Phase Type Timing - DPT that can represent a discrete cumulative density function (cdf) over a finite support (or a deterministic cdf) as well as an interval with non-deterministic choice (or a deterministic duration). In both views, a preemption policy can be assigned and a strong (the transition must fire when the interval expires) or a weak (the transition can fire when the interval expires) firing semantics. The paper introduces the DPT construct and shows how the expanded state space can be built up resorting to a compositional approach based on Kronecker algebra. With this technique a functional model can be quantified by adding probability measures over the firing intervals without modifying the (compositional) structure of the PN model.