The traditional mixed-criticality (MC) model does not allow less critical tasks to execute during an event of the error and exception. Recently, the imprecise MC (IMC) model has been proposed where, even for exceptional events, less critical tasks also receive some amount of (degraded) service, e.g., a task overruns its execution demand. In this work, we present our ongoing effort to extend the IMC model to the precise scheduling of tasks and integrate with the dynamic voltage and frequency scaling (DVFS) scheme to enable energy minimization. Precise scheduling of MC systems is highly challenging because of its requirement to simultaneously guarantee the timing correctness of all tasks under both pessimistic and less pessimistic assumptions. We propose an utilization-based schedulability test and sufficient schedulability conditions for such systems under earliest deadline first with virtual deadline (EDF-VD) scheduling policy. For this unified model, we present a quantitative study in the forms of speedup bound and approximation ratio. Finally, both theoretical and experimental analysis will be conducted to prove the correctness of our algorithm and to demonstrate its effectiveness.

Sustainability is a formalization of the requirement for scheduling algorithms and schedulability tests that a system deemed to be correctly schedulable should remain so if its run-time behavior is better than anticipated. The notion of sustainability is extended to mixed-criticality systems, and sustainability properties are determined for a variety of widely-studied uniprocessor and multi-processor mixed-criticality scheduling algorithms.