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EDF-based energy-efficient semi-clairvoyant scheduling with graceful degradation
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. 468-479Article in journal (Refereed) Published
Abstract [en]

Recent works introduce a semi-clairvoyant model, in which the system mode transition is revealed on the arrival of high criticality jobs. To solve the problem of inconsistency between the correctness criterion for mixed-criticality systems (MCS) with a semi-clairvoyant and the actual situation, we study the problem of schedulability and energy in MCS with the semi-clairvoyant model in this paper. First, we propose a new correctness criterion for MCS with semi-clairvoyant and graceful degradation and develop the schedulability test based on Demand Bound Function methods denoted as SCS-GD. Second, we propose an energy-efficient semi-clairvoyant scheduling algorithm based on SCS-GD denoted as EE-SCS-GD. Finally, we conduct an experimental evaluation of SCS-GD and EE-SCS-GD by synthetically generated task sets. The experimental results show that SCS-GD can improve the schedulability ratio by 5.98% compared to existing algorithms while EE-SCS-GD can save 56.17% energy compared to SCS-GD.

Place, publisher, year, edition, pages
IEEE, 2024. Vol. 43, no 2, p. 468-479
Keywords [en]
Degradation, DVFS, Dynamic scheduling, Energy consumption, Energy efficiency, energy management, graceful degradation, mixed-criticality, Scheduling algorithms, semi-clairvoyant, Switches, Task analysis
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:umu:diva-216110DOI: 10.1109/TCAD.2023.3321970ISI: 001166816300016Scopus ID: 2-s2.0-85174801429OAI: oai:DiVA.org:umu-216110DiVA, id: diva2:1811936
Funder
The Kempe FoundationsAvailable from: 2023-11-14 Created: 2023-11-14 Last updated: 2024-04-26Bibliographically approved

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Gu, Zonghua

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CiteExportLink to record
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