Event Graph
Posted by MOSIMTEC LLC
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An Event Graph is a graphical representation of a discrete system for which a static simulation algorithm can work on. It is an intermediary step between system specification and simulation implementation. An Event Graph represents a system, based on the events that progress the system state with nodes and directed edges. The value in the creation of an Event Graph comes with the addition of the simulation clock component and the readability of the graph. Most other methods for representing systems take into account process logic, but fail to include the time component.

 

There are some modelers that use the Event Graph as a stepping stone between a flowchart representation of system logic and the discrete event simulation implementation. Since the Event Graph takes the perspective of an event scheduling engine in a system representation, it is very easy to catch incorrect assumptions before any software implementation has begun. This could save, and has saved myself, countless hours of debugging and can create credibility for the modeler when showing system understanding. I have referenced these graphs in my own work during the verification process to ensure my implementation was correct to my understanding. My recommendation on when to use an Event Graph is use them when you want to be certain you have all the needed information during the modeling approach portion of a specification, since it will provide credibility and also iron out any incorrect assumptions.

 

However, the Event Graph is not limited to creating simulation algorithms. While its main use is in the development of simulations, the game development industry also benefits significantly from the usage of a modified Event Graph, by removing the time component to fit the graph to their needs. In Unreal Engine 5, the event graph is used to create blocks of code to be executed at the firing of an event, and schedule or cancel the events connected via the directed edges. Being that the event graph is multidisciplinary and very powerful wherever used, the value comes in how the creator of the graph utilizes them for their specific problem.

 

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