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The behavior of a given DEVS model is a set of sequences of timed events including null events, called event segments, which make the model move from one state to another within a set of legal states. To define it this way, the concept of a set of illegal state as well a set of legal states needs to be introduced.

In addition, since the behavior of a given DEVS model needs to define how the state transition change both when time is passed by and when an event occurs, it has been described by a much general formalism, called general system [ZPK00]. In this article, we use a sub-class of General System formalism, called timed event system instead.

Depending on how the total state and the external state transition function of a DEVS model are defined, there are two ways to define the behavior of a DEVS model using Timed Event System. Since the behavior of a coupled DEVS model is defined as an atomic DEVS model, the behavior of coupled DEVS class is also defined by timed event system.

Suppose that a DEVS model, ${\displaystyle {\mathcal {M}}=<X,Y,S,s_{0},ta,\delta _{ext},\delta _{int},\lambda >}$ has

1. the external state transition ${\displaystyle \delta _{ext}:Q\times X\rightarrow S}$.
2. the total state set ${\displaystyle Q=\{(s,t_{e})|s\in S,t_{e}\in (\mathbb {T} \cap [0,ta(s)])\}}$ where ${\displaystyle t_{e}}$ denotes elapsed time since last event and ${\displaystyle \mathbb {T} =[0,\infty )}$ denotes the set of non-negative real numbers, and

Then the DEVS model, ${\displaystyle {\mathcal {M}}}$ is a Timed Event System ${\displaystyle {\mathcal {G}}=<Z,Q,Q_{0},Q_{A},\Delta >}$ where

• The event set ${\displaystyle Z=X\cup Y^{\phi }}$.
• The state set ${\displaystyle Q=Q_{A}\cup Q_{N}}$ where ${\displaystyle Q_{N}=\{{\bar {s}}\not \in S\}}$.
• The set of initial states ${\displaystyle \,Q_{0}=\{(s_{0},0)\}}$.
• The set of accepting states ${\displaystyle Q_{A}={\mathcal {M}}.Q.}$
• The set of state trajectories ${\displaystyle \Delta \subseteq Q\times \Omega _{Z,[t_{l},t_{u}]}\times Q}$ is defined for two different cases: ${\displaystyle q\in Q_{N}}$ and ${\displaystyle q\in Q_{A}}$. For a non-accepting state ${\displaystyle q\in Q_{N}}$, there is no change together with any even segment ${\displaystyle \omega \in \Omega _{Z,[t_{l},t_{u}]}}$ so ${\displaystyle (q,\omega ,q)\in \Delta .}$

For a total state ${\displaystyle q=(s,t_{e})\in Q_{A}}$ at time ${\displaystyle t\in \mathbb {T} }$ and an event segment ${\displaystyle \omega \in \Omega _{Z,[t_{l},t_{u}]}}$ as follows.

If unit event segment ${\displaystyle \omega }$ is the null event segment, i.e. ${\displaystyle \omega =\epsilon _{[t,t+dt]}}$

${\displaystyle \,(q,\omega ,(s,t_{e}+dt))\in \Delta .}$

If unit event segment ${\displaystyle \omega }$ is a timed event ${\displaystyle \omega =(x,t)}$ where the event is an input event ${\displaystyle x\in X}$,

${\displaystyle (q,\omega ,(\delta _{ext}(q,x),0))\in \Delta .}$

If unit event segment ${\displaystyle \omega }$ is a timed event ${\displaystyle \omega =(y,t)}$ where the event is an output event or the unobservable event ${\displaystyle y\in Y^{\phi }}$,

${\displaystyle {\begin{cases}(q,\omega ,(\delta _{int}(s),0))\in \Delta &{\textrm {if}}~t_{e}=ta(s),y=\lambda (s)\\(q,\omega ,{\bar {s}})&{\textrm {otherwise}}.\end{cases}}}$

Computer algorithms to simulate this view of behavior are available at Simulation Algorithms for Atomic DEVS.

Suppose that a DEVS model, ${\displaystyle {\mathcal {M}}=<X,Y,S,s_{0},ta,\delta _{ext},\delta _{int},\lambda >}$ has

1. the total state set ${\displaystyle Q=\{(s,t_{s},t_{e})|s\in S,t_{s}\in \mathbb {T} ^{\infty },t_{e}\in (\mathbb {T} \cap [0,t_{s}])\}}$ where ${\displaystyle t_{s}}$ denotes lifespan of state ${\displaystyle s}$, ${\displaystyle t_{e}}$ denotes elapsed time since last ${\displaystyle t_{s}}$update, and ${\displaystyle \mathbb {T} ^{\infty }=[0,\infty )\cup \{\infty \}}$ denotes the set of non-negative real numbers plus infinity,
2. the external state transition is ${\displaystyle \delta _{ext}:Q\times X\rightarrow S\times \{0,1\}}$.

Then the DEVS ${\displaystyle Q={\mathcal {D}}}$ is a timed event system ${\displaystyle {\mathcal {G}}=<Z,Q,Q_{0},Q_{A},\Delta >}$ where

• The event set ${\displaystyle Z=X\cup Y^{\phi }}$.
• The state set ${\displaystyle Q=Q_{A}\cup Q_{N}}$ where ${\displaystyle Q_{N}=\{{\bar {s}}\not \in S\}}$.
• The set of initial states${\displaystyle \,Q_{0}=\{(s_{0},ta(s_{0}),0)\}}$.
• The set of acceptance states ${\displaystyle Q_{A}={\mathcal {M}}.Q}$.
• The set of state trajectories ${\displaystyle \Delta \subseteq Q\times \Omega _{Z,[t_{l},t_{u}]}\times Q}$ is depending on two cases: ${\displaystyle q\in Q_{N}}$ and ${\displaystyle q\in Q_{A}}$. For a non-accepting state ${\displaystyle q\in Q_{N}}$, there is no changes together with any segment ${\displaystyle \omega \in \Omega _{Z,[t_{l},t_{u}]}}$ so ${\displaystyle (q,\omega ,q)\in \Delta .}$

For a total state ${\displaystyle q=(s,t_{s},t_{e})\in Q_{A}}$ at time ${\displaystyle t\in \mathbb {T} }$ and an event segment ${\displaystyle \omega \in \Omega _{Z,[t_{l},t_{u}]}}$ as follows.

If unit event segment ${\displaystyle \omega }$ is the null event segment, i.e. ${\displaystyle \omega =\epsilon _{[t,t+dt]}}$

${\displaystyle (q,\omega ,(s,t_{s},t_{e}+dt))\in \Delta .}$

If unit event segment ${\displaystyle \omega }$ is a timed event ${\displaystyle \omega =(x,t)}$ where the event is an input event ${\displaystyle x\in X}$,

${\displaystyle {\begin{cases}(q,\omega ,(s',ta(s'),0))\in \Delta &{\textrm {if}}~\delta _{ext}(s,t_{s},t_{e},x)=(s',1),\\(q,\omega ,(s',t_{s},t_{e}))\in \Delta &{\textrm {otherwise,i.e.}}~\delta _{ext}(s,t_{s},t_{e},x)=(s',0).\end{cases}}}$

If unit event segment ${\displaystyle \omega }$ is a timed event ${\displaystyle \omega =(y,t)}$ where the event is an output event or the unobservable event ${\displaystyle y\in Y^{\phi }}$,

${\displaystyle {\begin{cases}(q,\omega ,(s',ta(s'),0))\in \Delta &{\textrm {if}}~t_{e}=t_{s},y=\lambda (s),\delta _{int}(s)=s',\\(q,\omega ,{\bar {s}})\in \Delta &{\textrm {otherwise}}.\end{cases}}}$

Computer algorithms to simulate this view of behavior are available at Simulation Algorithms for Atomic DEVS.

View1 has been introduced by Zeigler [Zeigler84] in which given a total state ${\displaystyle q=(s,t_{e})\in Q}$ and

${\displaystyle \,ta(s)=\sigma }$

where ${\displaystyle \sigma }$ is the remaining time [Zeigler84] [ZPK00]. In other words, the set of partial states is indeed ${\displaystyle S=\{(d,\sigma )|d\in S',\sigma \in \mathbb {T} ^{\infty }\}}$ where ${\displaystyle S'}$ is a state set.

When a DEVS model receives an input event ${\displaystyle x\in X}$, View1 resets the elapsed time ${\displaystyle t_{e}}$ by zero, if the DEVS model needs to ignore ${\displaystyle x}$ in terms of the lifespan control, modellers have to update the remaining time

${\displaystyle \,\sigma =\sigma -t_{e}}$

in the external state transition function ${\displaystyle \delta _{ext}}$ that is the responsibility of the modellers.

Since the number of possible values of ${\displaystyle \sigma }$ is the same as the number of possible input events coming to the DEVS model, that is unlimited. As a result, the number of states ${\displaystyle s=(d,\sigma )\in S}$ is also unlimited that is the reason why View2 has been proposed.

If we don't care the finite-vertex reachability graph of a DEVS model, View1 has an advantage of simplicity for treating the elapsed time ${\displaystyle t_{e}=0}$ every time any input event arrives into the DEVS model. But disadvantage might be modelers of DEVS should know how to manage ${\displaystyle \sigma }$ as above, which is not explicitly explained in ${\displaystyle \delta _{ext}}$ itself but in ${\displaystyle \Delta }$.

View2 has been introduced by Hwang and Zeigler[HZ06][HZ07] in which given a total state ${\displaystyle q=(s,t_{s},t_{e})\in Q}$, the remaining time, ${\displaystyle \sigma }$ is computed as

${\displaystyle \,\sigma =t_{s}-t_{e}.}$

When a DEVS model receives an input event ${\displaystyle x\in X}$, View2 resets the elapsed time ${\displaystyle t_{e}}$ by zero only if ${\displaystyle \delta _{ext}(q,x)=(s',1)}$. If the DEVS model needs to ignore ${\displaystyle x}$ in terms of the lifespan control, modellers can use ${\displaystyle \delta _{ext}(q,x)=(s',0)}$.

Unlike View1, since the remaining time ${\displaystyle \sigma }$ is not component of ${\displaystyle S}$ in nature, if the number of states, i.e. ${\displaystyle |S|}$ is finite, we can draw a finite-vertex (as well as edge) state-transition diagram [HZ06][HZ07]. As a result, we can abstract behavior of such a DEVS-class network, for example SP-DEVS and FD-DEVS, as a finite-vertex graph, called reachability graph [HZ06][HZ07].

• DEVS
• Behavior of Coupled DEVS
• Simulation Algorithms for Atomic DEVS
• Simulation Algorithms for Coupled DEVS

• [Zeigler76] Bernard Zeigler (1976). Theory of Modeling and Simulation (first ed.). Wiley Interscience, New York.
• [Zeigler84] Bernard Zeigler (1984). Multifacetted Modeling and Discrete Event Simulation. Academic Press, London; Orlando. ISBN 978-0-12-778450-2.
• [ZKP00] Bernard Zeigler; Tag Gon Kim; Herbert Praehofer (2000). Theory of Modeling and Simulation (second ed.). Academic Press, New York. ISBN 978-0-12-778455-7.
• [HZ06] M. H. Hwang and Bernard Zeigler, ``A Reachable Graph of Finite and Deterministic DEVS Networks``, Proceedings of 2006 DEVS Symposium, pp48-56, Huntsville, Alabama, USA, (Available at https://web.archive.org/web/20120726134045/http://www.acims.arizona.edu/ and http://moonho.hwang.googlepages.com/publications)
• [HZ07] M.H. Hwang and Bernard Zeigler, ``Reachability Graph of Finite & Deterministic DEVS``, IEEE Transactions on Automation Science and Engineering, Volume 6, Issue 3, 2009, pp. 454–467, https://ieeexplore.ieee.org/document/5071137/;jsessionid=939E18A20B3B2411AA8CD012B44EE174?isnumber=5153598&arnumber=5071137&count=19&index=7