Abstract
Mixed-criticality models are an emerging paradigm for the design of real-Time systems because of their significantly improved resource efficiency. However, formal mixed-criticality models have traditionally been characterized by two impractical assumptions: once any high-criticality task overruns, all low-criticality tasks are suspended and all other high-criticality tasks are assumed to exhibit high-criticality behaviors at the same time. In this paper, we propose a more realistic mixed-criticality model, called the flexible mixed-criticality (FMC) model, in which these two issues are addressed in a combined manner. In this new model, only the overrun task itself is assumed to exhibit high-criticality behavior, while other high-criticality tasks remain in the same mode as before. The guaranteed service levels of low-criticality tasks are gracefully degraded with the overruns of high-criticality tasks. We derive a utilization-based technique to analyze the schedulability of this new mixed-criticality model under EDF-VD scheduling. During run time, the proposed test condition serves an important criterion for dynamic service level tuning, by means of which the maximum available execution budget for low-criticality tasks can be directly determined with minimal overhead while guaranteeing mixed-criticality schedulability. Experiments demonstrate the effectiveness of the FMC scheme compared with state-of-The-Art techniques.
| Original language | English |
|---|---|
| Pages (from-to) | 543-558 |
| Number of pages | 16 |
| Journal | IEEE Transactions on Computers |
| Volume | 67 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Apr 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 12 Responsible Consumption and Production
Keywords
- EDF-VD scheduling
- flexible mixed-criticality system
- utilization-based analysis
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Hardware and Architecture
- Computational Theory and Mathematics
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