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Schedulability Analysis of WSAN Applications: Outperformance of a Model Checking Approach
Univ Tehran, Tehran, Iran..
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.ORCID iD: 0000-0001-8837-2068
Mälardalen Univ, Västerås, Sweden..
Mälardalen Univ, Västerås, Sweden..
2022 (English)In: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), Institute of Electrical and Electronics Engineers (IEEE), 2022Conference paper, Published paper (Refereed)
Abstract [en]

Wireless sensor and actuator networks (WSAN) are real-time systems which demand timing requirements. To ensure this level of requirements, different timing analysis approaches have been proposed for WSAN systems. Among different alternatives, analytical analysis and model checking approaches are two common ones which are widely used for the timing analysis of WSAN systems. Analytical approaches apply worst-case response time analysis techniques, whereas model checking generates explicit states of models to analyze them. In this paper, we develop schedulability analysis techniques based on two approaches, i.e., analytical and model checking approaches. We apply and compare the proposed analysis approaches on WSAN systems with an application in monitoring and control of civil infrastructures implemented on the Imote2 wireless sensor platform. We show that the highest possible data acquisition frequency for this application is computed while meeting the deadlines, and compare the results of the two approaches in terms of scalability, extensibility, and flexibility.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022.
Series
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), ISSN 1946-0740, E-ISSN 1946-0759
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:uu:diva-499403DOI: 10.1109/ETFA52439.2022.9921644ISI: 000934103900193ISBN: 978-1-6654-9996-5 (electronic)ISBN: 978-1-6654-9997-2 (print)OAI: oai:DiVA.org:uu-499403DiVA, id: diva2:1747610
Conference
IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), SEP 6-9, 2022, Stuttgart, Germany
Available from: 2023-03-30 Created: 2023-03-30 Last updated: 2023-03-30Bibliographically approved

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Mohaqeqi, Morteza

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CiteExportLink to record
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  • apa
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