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Mixed-criticality (MC) system has attracted a lot of research attention in the past few years for its resource efficiency. Recent work attempted to provide a new MC model, the so-called Flexible Mixed-Criticality (FMC) task model, to relax the pessimistic assumptions in classic MC scheduling. However, in FMC, the behavior of MC tasks is still analyzed in offline stage. The run-time behavior such as dynamic slack has not yet been studied in FMC scheduling framework. In this paper, we present a utilization-based slack scheduling framework for FMC tasks. In particular, we monitor task execution on run time and collect dynamic slacks generated by task early completion. And these slacks can then be used either by high-criticality tasks to reduce mode-switches, or by low-criticality tasks so that less suspensions are triggered with more execution time, and thus quality of service is improved. We evaluate our approach with extensive simulations, and experiment results demonstrate the effectiveness of the proposed approaches.

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