Split Queue Time Warp and a Flexible Distributed Simulation System

Simulation belongs to the oldest computer applications: using a model for quasi-empirical studies is a cost-effecive and sometimes unique way of analysing a real sytem and getting a basis for decisions. A more recent purpose is to build virtual environments for training or entertainment. There is a variety of modeling approaches and computational techniques. Discrete event simulation, which is our subject here, considers the dynamics of the object system as a sequence of instantaneous state transformations called events. (Queueing systems are a classic example, with events like a job entering or leaving a queue.) In this abstraction, nothing happens between event times, so that the simulation skips the intervals. Computation time and simulated time thus become independent concepts: the computer dedicates its time and efforts to the events – which, in reality, have no duration at all. This orthogonality has two important consequences. First, a computer simulation can be orders of magnitude faster or slower than the real thing; this depends on the frequency of events and their computational cost. Second, to make simulated time go on, there must always be a future event to continue with. Event processing therefore has the additional obligation to deduce subsequent events from the current state of affairs. (In a queueing example, the event of a job entering service may imply leaving it some definite time later.) Such future events are then managed in the event list (calendar, agenda, . . . ), a priority queue of what-when pairs ordered by time-stamps, where the foremost entry defines the current event and the current time.