Partitioned and overhead-aware scheduling of mixed-criticality real-time systems
24th Asia and South Pacific Design Automation Conference (ASPDAC), Tokyo, Japan
ABSTRACT
Modern real-time embedded and cyber-physical systems comprise a large number of applications, often of different criticalities, executing on the same computing platform. Partitioned scheduling is used to provide temporal isolation among tasks with different criticalities. Isolation is often a requirement, for example, in order to avoid the case when a low criticality task overruns or fails in such a way that causes a failure in a high criticality task. When the number of partitions increases in mixed criticality systems, the size of the schedule table can become extremely large, which becomes a critical bottleneck due to design time and memory constraints of embedded systems. In addition, switching between partitions at runtime causes CPU overhead due to preemption. In this paper, we propose a design framework comprising a hyper-period optimization algorithm, which reduces the size of schedule table and preserves schedulability, and a re-scheduling algorithm to reduce the number of preemptions. Extensive experiments demonstrate the effectiveness of proposed algorithms and design framework.
[ZSEP19] Yuanbin Zhou, Soheil Samii, Petru Eles, Zebo Peng, "Partitioned and overhead-aware scheduling of mixed-criticality real-time systems", 24th Asia and South Pacific Design Automation Conference (ASPDAC), Tokyo, Japan |
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