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A statistical approach to simulation model validation in response-time analysis of complex real-time embedded systems
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-7366-7186
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0001-6132-7945
University of York.ORCID iD: 0000-0003-2415-8219
2011 (English)In: Proceedings of the ACM Symposium on Applied Computing 2011, 2011, 711-716 p.Conference paper, Published paper (Refereed)
Abstract [en]

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. © 2011 ACM.

Place, publisher, year, edition, pages
2011. 711-716 p.
Series
Proceedings of the ACM Symposium on Applied Computing
Keyword [en]
complex realtime embedded systems, non-parametric statistical hypothesis testing, response time, simulation model validation, two-sample kolmogorov-smirnov test, Actual system, Industrial robotics, Kolmogorov-Smirnov test, Non-parametric, Real-time embedded systems, Response-time analysis, Simulation model, Simulation result, Simulation-based analysis, Statistical approach, Statistical hypothesis test, Temporal differences, Temporal simulation, Timing Analysis, Embedded systems, Real time systems, Robotics, Statistical tests, Systems analysis, Computer simulation
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:mdh:diva-16058DOI: 10.1145/1982185.1982341Scopus ID: 2-s2.0-79959289106ISBN: 9781450301138 (print)OAI: oai:DiVA.org:mdh-16058DiVA: diva2:563367
Conference
26th Annual ACM Symposium on Applied Computing, SAC 2011, 21 March 2011 through 24 March 2011, TaiChung
Note

Sponsors: ACM Special Interest Group on Applied Computing (SIGAPP); Tunghai University; Taiwan Ministry of Education; Taiwan Bureau of Foreign Trade; Taiwan National Science Council (NSC)

Available from: 2012-10-29 Created: 2012-10-29 Last updated: 2013-12-19Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
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Output format
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  • asciidoc
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