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Finite State Machine (FSM)
Finite State Machine (FSM) models contain sets of states, inputs, outputs, output
functions, and next-state functions. Embedded applications are described as a set of
states and input values, which can activate a transition from one state to another.
FSMs are usually used for modeling the control-
ow dominated systems. To avoid
limitations of the classical FMS, researchers have proposed several derivatives of
the FSM. Some of these extensions are used in several tools such as SOLAR (Ismail
et al.
1994
), Hierarchical Concurrent FSM (HCFSM) (Reynari et al.
2001
) and Co-
design Finite State Machine (CFSM) (Cloute et al.
1999
).
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Discrete-Event Systems
In a Discrete-Event System, the occurrence of discrete asynchronous events triggers
the transitioning from one state to another. An event is de
ned as an instantaneous
action, and has a timestamp representation when the event took place. Events are
sorted globally according to their time of arrival. A signal is de
ned as a set of
events, and it is the main method of communication between processes (Stoy and
Zebo
1994
). Discrete Event modeling is often used for hardware simulation. For
example, both Verilog and VHDL use Discrete Event modeling as the underlying
model of Computation. Discrete Event modeling is expensive since it requires all
events according to their timestamp.
Petri Nets
Petri Nets is widely used for modeling systems. Petri Nets consists of places, tokens
and transitions where token are stored in places. Transition causes tokens are stored
in places. Transition causes tokens to be produced and consumed. Petri Nets sup-
ports concurrency and is asynchronous; however, they lack the ability to model
hierarchy. Therefore, it can be dif
cult to use Petri Nets to model complex systems
due to its lack of hierarchy. Variation of Petri Nets has been devised to address the
lack of hierarchy, such as the Hierarchal Petri Nets (HPNs) proposed by Dittrich.
Hierarchical Petri Nets (HPNs) supports hierarchy in addition to maintaining the
major Petri Net
s features such as concurrency and asynchronously. HPNs use
directed graphs as the underlying model. HPNs are suitable for modeling complex
systems since they support both concurrency and hierarchy.
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Data Flow Graphs
Data Flow Graphs (DFG) systems are speci
ed using a directed graph where nodes
(actors) represent inputs, outputs and operations and edges represent data paths
between nodes (Reynari et al.
2001
). The main usage of Data Flow is for modeling
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