Rare Event Provoking Simulation Techniques

Importance sampling is the rare event provoking technique that is most frequently used for speed-up simulation of dependability and traffic models. Due to its sensitivity to the parameter settings, it is not yet ready for practical use. There exists a number of approaches for finding optimal, or at least good, parameters. The applicability of these and necessary extensions are discussed with reference to the typical characteristics of state models used for simulation. In dependability models failure biasing is applied to guarantee a bounded relative error. It is more flexible with respect to the model characteristics, but less efficient, than the heuristic based on large deviation theory used in queuing models. This heuristic puts severe restrictions on the model, particularly considering state models with state space of more than 1 dimension. This paper proposes a technique that is rather efficient for simulation of state models with irregular and -dimensional state spaces. Constant rate models are discussed in detail.