Discrete Event Modeling and Simulation

In general, a DE scheduler processes events in chronological order. Therefore, a good DE scheduler needs a fast implementation of the global sorted event queue. The currently implemented DE scheduler uses a calendar queue data structure to sort events. This data structure provides an efficient priority queue implementation. The complexity is O(1) in both enqueue and dequeue operations). When events are produced, they are enqueued into the queue. At each iteration, events with oldest time stamp are dequeued and the current time of the simulation is advanced. The actor that consumes these events may produce additional events with time stamp greater than or equal to the current time (i.e. causality constraint).

Much of the sophistication in the scheduling implementation of this domain is on how we handle simultaneous events properly. The chosen approach is to assign priorities to input ports. Input ports that are more 'up-stream' with respect to the 'data flow' have higher priority. More specifically, a partial order relation graph is created with respect to the 'data flow' and the Ptolemy II graph package is used to perform topological sort on it.

For future work, since Ptolemy also emphasizes on heterogeneity, it is interesting to investigate the interaction between DE and other domains in Ptolemy II. Performance issues will also be investigated.