You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

A Statistical Approach for Validation of Task Simulation Models with Intricate Temporal Execution Dependencies

Fulltext:


Publication Type:

Conference/Workshop Paper

Venue:

Proceedings of the Work-In-Progress (WIP) track of the 16th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS10)


Abstract

This paper presents a novel approach to validation of temporal simulation models extracted from real industrial control systems containing intricate task execution dependencies, by introducing existing mature statistical methods to the context. The proposed approach firstly collects sampling distributions of response time data of tasks in both the modeled system and the model, in terms of simple random samples (SRS). The second step of the approach is to compare the sampling distributions using a non-parametric Kolmogorov-Smirnov test. After evaluating a fictive system model inspired by a real robotic control system, the proposed algorithm shows the possibility of identifying the temporal differences between a target system and its extracted model, i.e., whether the model is a sufficiently accurate approximation of the target system. The approach makes few assumptions on the system design and scales to very large and complex systems.

Bibtex

@inproceedings{Lu1778,
author = {Yue Lu and Johan Kraft and Thomas Nolte and Christer Norstr{\"o}m},
title = {A Statistical Approach for Validation of Task Simulation Models with Intricate Temporal Execution Dependencies},
pages = {5--8},
month = {April},
year = {2010},
booktitle = {Proceedings of the Work-In-Progress (WIP) track of the 16th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS10)},
url = {http://www.es.mdh.se/publications/1778-}
}