  Scenario-aware dataflow (SADF) is a prominent tool for modeling and analysis
of dynamic embedded dataflow applications. In SADF the application is
represented as a finite collection of synchronous dataflow (SDF) graphs, each
of which represents one possible application behaviour or scenario. A finite
state machine (FSM) specifies the possible orders of scenario occurrences. The
SADF model renders the tightest possible performance guarantees, but is limited
by its finiteness. This means that from a practical point of view, it can only
handle dynamic dataflow applications that are characterized by a reasonably
sized set of possible behaviours or scenarios. In this paper we remove this
limitation for a class of SADF graphs by means of SADF model parametrization in
terms of graph port rates and actor execution times. First, we formally define
the semantics of the model relevant for throughput analysis based on (max,+)
linear system theory and (max,+) automata. Second, by generalizing some of the
existing results, we give the algorithms for worst-case throughput analysis of
parametric rate and parametric actor execution time acyclic SADF graphs with a
fully connected, possibly infinite state transition system. Third, we
demonstrate our approach on a few realistic applications from digital signal
processing (DSP) domain mapped onto an embedded multi-processor architecture.
