Chen, Jian-Jia, Nelissen, Geoffrey, Huang, Wen-Hung Kevin et al. (10 more authors) (2018) Many Suspensions, Many Problems: A Review of Self-Suspending Tasks in Real-Time Systems. Real-Time Systems. ISSN 1573-1383
Abstract
In general computing systems, a job (process/task) may sus- pend itself whilst it is waiting for some activity to complete, e.g., an accelerator to return data. In real-time systems, such self-suspension can cause substantial performance/schedulability degradation. This observa- tion, first made in 1988, has led to the investigation of the impact of self-suspension on timing predictability, and many relevant results have been published since. Unfortunately, as it has recently come to light, a number of the existing results are flawed. To provide a correct platform on which future research can be built, this paper reviews the state of the art in the design and analysis of scheduling algorithms and schedulability tests for self-suspending tasks in real-time systems. We provide (1) a systematic description of how self-suspending tasks can be handled in both soft and hard real-time systems; (2) an explanation of the existing misconceptions and their potential remedies; (3) an assessment of the influence of such flawed analyses on partitioned multiprocessor fixed-priority scheduling when tasks synchronize access to shared resources; and (4) a discussion of the computational complexity of analyses for different self-suspension task models.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2018 |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 06 Sep 2018 11:00 |
Last Modified: | 16 Oct 2024 15:03 |
Published Version: | https://doi.org/10.1007/s11241-018-9316-9 |
Status: | Published online |
Refereed: | Yes |
Identification Number: | 10.1007/s11241-018-9316-9 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135393 |
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