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Criticality-aware EDF scheduling for constrained-deadline imprecise mixed-criticality systems
College of Computer Science and Technology, Huaqiao University, China.
College of Computer Science and Technology, Huaqiao University, China.
College of Computer Science and Technology, Huaqiao University, China.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0003-4228-2774
2024 (English)In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ISSN 0278-0070, E-ISSN 1937-4151, Vol. 43, no 2, p. 480-491Article in journal (Refereed) Published
Abstract [en]

EDF-VD first focuses on the classic mixed-criticality task model in which all low criticality (LO) tasks are abandoned in the high criticality mode, which is an effective dynamic priority scheduling algorithm for mixed-criticality systems. However, it has low schedulability for the imprecise mixed-criticality (IMC) task model with constrained-deadlines, in which LO tasks are provided graceful degradation services instead of being abandoned. In this paper, we study how to improve schedulability for the IMC tasks model. First, we propose a novel criticality-aware EDF scheduling algorithm (CA-EDF) that tries to delay the LO task execution to improve schedulability. Second, we derive sufficient conditions of schedulability for CA-EDF based on the Demand Bound Function. Finally, we evaluate CA-EDF through extensive simulation. The experimental results indicate that CA-EDF can improve the schedulability ratio by about 13.10% compared to the existing algorithms.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024. Vol. 43, no 2, p. 480-491
Keywords [en]
Computational modeling, demand bound function, graceful degradation, imprecise mixed-criticality, Industries, Job shop scheduling, Program processors, real-time scheduling, Scheduling algorithms, Switches, Task analysis
National Category
Computer Engineering Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-219518DOI: 10.1109/TCAD.2023.3318512Scopus ID: 2-s2.0-85181578343OAI: oai:DiVA.org:umu-219518DiVA, id: diva2:1830004
Funder
The Kempe FoundationsAvailable from: 2024-01-22 Created: 2024-01-22 Last updated: 2024-01-22Bibliographically approved

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Gu, Zonghua

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CiteExportLink to record
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  • apa
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