A discrete-event simulation tool for the analysis of simultaneous events

Discrete-event simulation is a very popular technique for the performance evaluation of systems, and in widespread use in network simulation tools. It is well known, however, that discrete-event simulation suffers from the problem of simultaneous events: Different execution orders of events with identical timestamps may lead to different simulation results. Current simulation tools apply tie-breaking mechanisms which order simultaneous events for execution. While this is an accepted solution, a legitimate question is: Why should only a single simulation result be selected, and other possible results be ignored? In this paper, we argue that confidence in simulation results may be increased by analyzing the impact of simultaneous events. We present a branching mechanism which examines different execution orders of simultaneous events, and may be used in conjunction with, or as an alternative to tie-breaking rules. We have developed a new simulation tool, MOOSE, which provides branching mechanisms for both sequential and distributed discrete-event simulation. While MOOSE has originally been developed for network simulation, it is fully usable as a general simulation tool.