Haohan Li

The Preemptive Uniprocessor Scheduling of Mixed-Criticality Implicit-Deadline Sporadic Task Systems

Systems in many safety-critical application domains are subject to certification requirements. For any given system, however, it may be the case that only a subset of its functionality is safety-critical and hence subject to certification, the rest of the functionality is non safety critical and does not need to be certified, or is certified to a lower level of assurance. An algorithm called EDF-VD (for Earliest Deadline First with Virtual Deadlines) is described for the scheduling of such mixed-criticality task systems. Analyses of EDF-VD significantly superior to previously-known ones are presented, based on metrics such as processor speedup factor (EDF-VD is proved to be optimal with respect to this metric) and utilization bounds.

Outstanding Paper Award: Global Mixed-Criticality Scheduling on Multiprocessors

The scheduling of mixed-criticality implicit-deadline sporadic task systems on identical multiprocessor platforms is considered, when inter-processor migration is permitted. A scheduling algorithm is derived and proved correct, and its properties investigated. Theoretical analysis (in the form of both a speedup factor and sufficient schedulability conditions) as well as extensive simulation experiments serve to demonstrate its effectiveness.

Mixed-criticality scheduling on multiprocessors

The scheduling of mixed-criticality implicit-deadline sporadic task systems on identical multiprocessor platforms is considered. Two approaches, one for global and another for partitioned scheduling, are described. Theoretical analyses and simulation experiments are used to compare the global and partitioned scheduling approaches.

Load-based schedulability analysis of certifiable mixed-criticality systems

Many safety-critical embedded systems are subject to certification requirements. However, only a subset of the functionality of the system may be safety-critical and hence subject to certification; the rest of the functionality is non safety-critical and does not need to be certified. Certification requirements in such mixed-criticality systems give rise to some interesting scheduling problems, that cannot be satisfactorily addressed using techniques from conventional scheduling theory. In prior work, we have proposed a priority-based algorithm for scheduling such mixed-criticality systems on preemptive uniprocessor platforms. In this paper, we derive a sufficient schedulability condition for efficiently determining whether a given mixed-criticality system can be successfully scheduled by this algorithm. We show that this algorithm (and the associated schedulability test) is strictly superior to prior algorithms that have been used for scheduling mixed-criticality systems needing certification.

Preemptive Uniprocessor Scheduling of Mixed-Criticality Sporadic Task Systems

Systems in many safety-critical application domains are subject to certification requirements. For any given system, however, it may be the case that only a subset of its functionality is safety-critical and hence subject to certification; the rest of the functionality is non-safety-critical and does not need to be certified, or is certified to lower levels of assurance. The certification-cognizant runtime scheduling of such mixed-criticality systems is considered. An algorithm called EDF-VD (for Earliest Deadline First with Virtual Deadlines) is presented: this algorithm can schedule systems for which any number of criticality levels are defined. Efficient implementations of EDF-VD, as well as associated schedulability tests for determining whether a task system can be correctly scheduled using EDF-VD, are presented. For up to 13 criticality levels, analyses of EDF-VD, based on metrics such as processor speedup factor and utilization bounds, are derived, and conditions under which EDF-VD is optimal with respect to these metrics are identified. Finally, two extensions of EDF-VD are discussed that enhance its applicability. The extensions are aimed at scheduling a wider range of task sets, while preserving the favorable worst-case resource usage guarantees of the basic algorithm.