Abstract
The event horizon is a very important concept that is useful for both parallel and sequential discrete-event simulations. By exploiting the event horizon, parallel simulations can process events in a manner that is risk-free (i.e., no antimessages) in adaptable “breathing” time cycles with variable time widths. Additionally, exploiting the event horizon can greatly reduce the event list management overhead that is common to virtually all discrete-event simulations. This paper develops an analytic model describing the event horizon from first principles using equilibrium considerations and the hold model (where each event, when consumed, generates a single new event with future-time statistics described by a known probability function). Exponential and Beta-density functions are used to verify the mathematics presented in this paper.
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