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International Conference on Architecture of Computing Systems

ARCS 2017: Architecture of Computing Systems - ARCS 2017 pp 205–218Cite as

Semi-partitioned Mixed-Criticality Scheduling

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10172))

Abstract

Scheduling isolation in mixed-criticality systems is challenging without sacrificing performance. In response, we propose a scheduling approach that combines server-based semi-partitioning and deadline-scaling. Semi-partitioning (whereby only some tasks migrate, in a carefully managed manner), hitherto used in single criticality systems, offers good performance with low overheads. Deadline-scaling selectively prioritise high-criticality tasks in parts of the schedule to ensure their deadlines are met even in rares case of execution time overrun. Our new algorithm NPS-F-MC brings semi-partitioning to mixed-criticality scheduling and uses Ekberg and Yi’s state-of-the-art deadline scaling approach. It ensures scheduling isolation among different-criticality tasks and only allows low-criticality task migration. We also explore variants that disallow migration entirely or relax the isolation between different criticalities (SP-EKB) in order to evaluate the performance tradeoffs associated with more flexible or rigid safety and isolation requirements.

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Notes

  1. 1.

    Setting S to an integral fraction of \(DT_{min}\) was handy for proving a utilisation bound for NPS-F in [3], but in fact the \(\mathrm {DBF}\)-based server-sizing by Sousa et al. [13] allows for dropping this constraint. In this paper, we just stick to tradition.

  2. 2.

    The plots of (non-weighted) schedulability can still be found in the Appendix of our TR [15].

  3. 3.

    Recall that, for the same configuration, SP-EKB strictly dominates P-EKB. However, some task sets schedulable by SP-EKB-\(\kappa \)U are unschedulable by P-EKB-U (and vice versa) and some tasks schedulable by SP-EKB-U are unschedulable by P-EKB-\(\kappa \)U (and vice versa).

References

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Acknowledgments

We would like to thank Pontus Ekberg for clarifying to us some aspects of his algorithm.

This work was partially supported by National Funds through FCT/MEC (Portuguese Foundation for Science and Technology) and co-financed by ERDF (European Regional Development Fund) under the PT2020 Partnership, within the CISTER Research Unit (CEC/04234); also by FCT/MEC and the EU ARTEMIS JU within project ARTEMIS/0001/2013- JU grant nr. 621429 (EMC2).

Author information

Authors and Affiliations

  1. CISTER/INESC-TEC Research Centre, Porto, Portugal

    Muhammad Ali Awan, Konstantinos Bletsas, Pedro F. Souto & Eduardo Tovar

  2. ISEP/IPP, Porto, Portugal

    Muhammad Ali Awan, Konstantinos Bletsas & Eduardo Tovar

  3. Faculty of Engineering, University of Porto, Porto, Portugal

    Pedro F. Souto

Authors
  1. Muhammad Ali Awan
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  2. Konstantinos Bletsas
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  3. Pedro F. Souto
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  4. Eduardo Tovar
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Corresponding author

Correspondence to Konstantinos Bletsas .

Editor information

Editors and Affiliations

  1. Vienna University of Technology, Vienna, Austria

    Jens Knoop

  2. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Wolfgang Karl

  3. Lawrence Livermore National Laboratory, Livermore, USA

    Martin Schulz

  4. Kyushu University, Fukuoka, Japan

    Koji Inoue

  5. Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany

    Thilo Pionteck

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Awan, M.A., Bletsas, K., Souto, P.F., Tovar, E. (2017). Semi-partitioned Mixed-Criticality Scheduling. In: Knoop, J., Karl, W., Schulz, M., Inoue, K., Pionteck, T. (eds) Architecture of Computing Systems - ARCS 2017. ARCS 2017. Lecture Notes in Computer Science(), vol 10172. Springer, Cham. https://doi.org/10.1007/978-3-319-54999-6_16

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  • DOI: https://doi.org/10.1007/978-3-319-54999-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54998-9

  • Online ISBN: 978-3-319-54999-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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