Length-Based Blocking and Local Estimations in Distributed Simulation: A Case Study
Résumé
This work investigates the use of a preventive length-based blocking strategy associated with local estimations. A logical process must block until the length of its input queue becomes greater than a threshold L min. By blocking one can reduce the number of time errors in order to allow the local estimations to handle more efficiently the remaining time errors. In a first time, we seek for an empirical optimal trade-off between the initial blocking length, the speedup relative to a conservative simulation and the accuracy of the results. Then an automatic tuning is performed to adjust the initial blocking length to a desired time error ratio. We apply this method to simulate an ATM network and the results show that the length blocking strategy succeed in reducing the number of causality violations with a very small blocking overhead. Also both accuracy and speedup can be achieved.