Modelling very large systems that consist of many similar components can lead to state space explosion. A continuous approximation of the system can be used to avoid this problem. In the stochastic process algebra PEPA, models with large numbers of identical components can be approximated in a continuous fashion by a set of coupled ordinary differential equations (ODEs). Similarly, timed continuous Petri nets can be used to approximate behaviour via ODEs where there are many servers. These two approaches are compared and infinite and finite server semantics are considered.
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