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Energy-aware adaptive mixed-criticality scheduling with semi-clairvoyance and graceful degradation
College of Computer Science and Technology, Huaqiao University, No. 668, Jimei Avenue, Fujian, Xiamen, China.
College of Computer Science and Technology, Huaqiao University, No. 668, Jimei Avenue, Fujian, Xiamen, China.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.ORCID iD: 0000-0003-4228-2774
2024 (English)In: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 23, no 1, article id 11Article in journal (Refereed) Published
Abstract [en]

The classic Mixed-Criticality System (MCS) task model is a non-clairvoyance model in which the change of the system behavior is based on the completion of high-criticality tasks while dropping low-criticality tasks in high-criticality mode. In this paper, we simultaneously consider graceful degradation and semi-clairvoyance in MCS. We first propose the analysis for adaptive mixed-criticality with semi-clairvoyance denoted as C-AMC-sem. The so-called semi-clairvoyance refers to the system’s behavior change being revealed at the time that jobs are released. Moreover, we propose a new algorithm based on C-AMC-sem to reduce energy consumption. Finally, we verify the performance of the proposed algorithms via experiments upon synthetically generated tasksets. The experimental results indicate that the proposed algorithms significantly outperform the existing algorithms.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2024. Vol. 23, no 1, article id 11
Keywords [en]
energy-aware scheduling, graceful degradation, mixed-criticality systems, Real-time scheduling, semi-clairvoyance
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-224838DOI: 10.1145/3632749Scopus ID: 2-s2.0-85184778531OAI: oai:DiVA.org:umu-224838DiVA, id: diva2:1868366
Funder
Swedish Research Council, 2023-04485The Kempe FoundationsAvailable from: 2024-06-11 Created: 2024-06-11 Last updated: 2024-06-11Bibliographically approved

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Gu, Zonghua

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CiteExportLink to record
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  • apa
  • ieee
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