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A Statistical Approach to Simulation Model Validation in Response-Time Analysis of Complex Real-Time Embedded Systems

Fulltext:


Authors:

Yue Lu, Johan Kraft, Thomas Nolte, Iain Bate

Research group:

Complex Real-Time Embedded Systems

Publication Type:

Conference/Workshop Paper

Venue:

26th ACM Symposium on Applied Computing (SAC11)

Publisher:

ACM

Abstract

As simulation-based analysis methods make few restrictions on the system design and scale to very large and complex systems, they are widely used in, e.g., timing analysis of complex real-time embedded systems (CRTES) in industrial circles. However, before such methods are used, the analysis simulation models have to be validated in order to assess if they represent the actual system or not, which also matters to the confidence in the simulation results. This paper presents a statistical approach to validation of temporal simulation models extracted from CRTES, by introducing existing mature statistical hypothesis tests to the context. Moreover, our evaluation using simulation models depicting a fictive but representative industrial robotic control system indicates that the proposed method can successfully identify temporal differences between different simulation models, hence it has the potential to be considered as an effective simulation model validation technique.

Bibtex

@inproceedings{Lu1940,
author = {Yue Lu and Johan Kraft and Thomas Nolte and Iain Bate},
title = {A Statistical Approach to Simulation Model Validation in Response-Time Analysis of Complex Real-Time Embedded Systems},
pages = {711--716},
month = {March},
year = {2011},
booktitle = {26th ACM Symposium on Applied Computing (SAC11)},
publisher = {ACM},
url = {http://www.es.mdu.se/publications/1940-}
}