Avoiding redundancies in the Proxel method Online publication date: Tue, 31-Mar-2015
by Robert Buchholz; Claudia Krull; Graham Horton
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 7, No. 2, 2015
Abstract: The simulation of discrete stochastic systems is used to make predictions on system behaviour. Its most widely used technique, discrete event simulation, computes possible simulation results by using random numbers. Consequently, these results are also only random numbers. Alternative state space-based simulation techniques can directly compute the actual system behaviour, but are computationally infeasible for bigger models. In this work, we improve the state space-based Proxel simulation method by avoiding some of its redundancies through clustering of discrete states. Our experiments demonstrate a speedup by a factor of two to five for realistic models, without any loss in accuracy. If no redundancies in the model can be exploited, the method only incurs a small computational overhead. Our approach thus has the potential of making deterministic state space-based analysis of existing models more efficient, and of enabling the analysis of bigger models that more accurately reflect real systems.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Aided Engineering and Technology (IJCAET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com