Generalizing lookahead-behavioral prediction in distributed simulation

One of the key factors for efficiency in distributed simulation is the detection of model-inherent concurrency, which is related on the prediction of the future behavior of each logical simulation process. We present a generalization of traditional approaches to behavioral prediction which provides more accurate predictions in general and a high degree of scalability in terms of computational and communication overhead. We give a sequential implementation, prove its correctness using concepts from the analysis of real time process networks and then show how these results can be used in distributed simulation.