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Efficient Schedulability Analysis of Semi-Clairvoyant Sporadic Task Systems With Graceful Degradation

Published: 07 June 2022 Publication History

Abstract

Vestal proposed an abstract model for mixed-criticality workloads in which each job is characterized by multiple different estimates of its actual, but unknown, worst-case execution time (WCET). While this model helped establish the study of mixed-criticality systems, it has received criticism for incorporating some unrealistic assumptions. In response, recent works have introduced an alternative “semi-clairvoyant” model in which each job reveals upon arrival which of its WCET parameters it will respect. Such models are practically realizable and demonstrate a significant improvement over conventionally considered models in terms of speedup factor and schedulability. More recently, several different interpretations of graceful degradation have been considered in the context of semi-clairvoyant scheduling. Under one of these, Earliest Deadline First (EDF) scheduling has been shown to be optimal and associated exact schedulability tests have been derived. This work proposes Mixed-Criticality Quick Processor-demand Analysis (MC-QPA), an efficient and exact schedulability test for EDF-based semi-clairvoyant scheduling of sporadic task systems, and formally establishes its correctness. The effectiveness of MC-QPA over prior approaches in terms of the test running times is demonstrated via simulation experiments.

References

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Qingling Zhao, Mengfei Qu, Bo Huang, Zhe Jiang, and Haibo Zeng. 2022. Schedulability analysis and stack size minimization for adaptive mixed criticality scheduling with semi-Clairvoyance and preemption thresholds. Journal of Systems Architecture 124 (2022), 102383. https://doi.org/10.1016/j.sysarc.2021.102383

Cited By

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  • (2025)Semi-clairvoyant scheduling in non-preemptive fixed-priority mixed-criticality systemsJournal of Systems Architecture10.1016/j.sysarc.2025.103332(103332)Online publication date: Jan-2025
  • (2024)Energy-Aware Adaptive Mixed-Criticality Scheduling with Semi-Clairvoyance and Graceful DegradationACM Transactions on Embedded Computing Systems10.1145/363274923:1(1-20)Online publication date: 10-Jan-2024
  • (2024)Energy-aware reliability guarantee scheduling with semi-clairvoyant in mixed-criticality systemsJournal of Systems Architecture10.1016/j.sysarc.2024.103269156(103269)Online publication date: Nov-2024
  • Show More Cited By

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cover image ACM Other conferences
RTNS '22: Proceedings of the 30th International Conference on Real-Time Networks and Systems
June 2022
241 pages
ISBN:9781450396509
DOI:10.1145/3534879
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 June 2022

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Author Tags

  1. Demand Bound Functions
  2. Graceful Degradation
  3. Mixed-criticality
  4. Quick Processor-demand Analysis (QPA)
  5. Semi-clairvoyance

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Overall Acceptance Rate 119 of 255 submissions, 47%

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Cited By

View all
  • (2025)Semi-clairvoyant scheduling in non-preemptive fixed-priority mixed-criticality systemsJournal of Systems Architecture10.1016/j.sysarc.2025.103332(103332)Online publication date: Jan-2025
  • (2024)Energy-Aware Adaptive Mixed-Criticality Scheduling with Semi-Clairvoyance and Graceful DegradationACM Transactions on Embedded Computing Systems10.1145/363274923:1(1-20)Online publication date: 10-Jan-2024
  • (2024)Energy-aware reliability guarantee scheduling with semi-clairvoyant in mixed-criticality systemsJournal of Systems Architecture10.1016/j.sysarc.2024.103269156(103269)Online publication date: Nov-2024
  • (2024)Energy-aware fault-tolerant scheduling for imprecise mixed-criticality systems with semi-clairvoyanceJournal of Systems Architecture10.1016/j.sysarc.2024.103141151(103141)Online publication date: Jun-2024
  • (2023)EDF-Based Energy-Efficient Semi-Clairvoyant Scheduling With Graceful DegradationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.332197043:2(468-479)Online publication date: 3-Oct-2023

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