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Scheduling optimization with partitioning for mixed-criticality systems
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering. General Motors, USA.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
2019 (English)In: Journal of systems architecture, ISSN 1383-7621, E-ISSN 1873-6165, Vol. 98, p. 191-200Article in journal (Refereed) Published
Abstract [en]

Modern real-time embedded and cyber-physical systems comprise a large number of applications, often of different criticalities, executing on the same computing platform. Partitioned scheduling is used to provide temporal isolation among tasks with different criticalities. Isolation is often a requirement, for example, in order to avoid the case when a low criticality task overruns or fails in such a way that causes a failure in a high criticality task. When the number of partitions increases in mixed criticality systems, the size of the schedule table can become extremely large, which becomes a critical bottleneck due to design time and memory constraints of embedded systems. In addition, switching between partitions causes CPU overhead due to preemption. In this paper, we propose a design framework comprising the trade-off between schedule table size and system utilization, as well as a re-scheduling algorithm to reduce the effect of preemptions on utilization. Extensive experiments demonstrate the effectiveness of the proposed algorithms and design framework.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 98, p. 191-200
Keywords [en]
Real-time systems, Mixed-criticality systems, Scheduling
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-160490DOI: 10.1016/j.sysarc.2019.07.007ISI: 000487166300015Scopus ID: 2-s2.0-85069685876OAI: oai:DiVA.org:liu-160490DiVA, id: diva2:1353810
Available from: 2019-09-24 Created: 2019-09-24 Last updated: 2019-10-24Bibliographically approved

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Samii, SoheilEles, Petru IonPeng, Zebo

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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