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.

中文翻译：

---

具有动态 Slack 管理的灵活混合关键性调度

混合临界（MC）系统在过去几年因其资源效率而引起了很多研究关注。最近的工作试图提供一种新的 MC 模型，即所谓的灵活混合临界 (FMC) 任务模型，以放松经典 MC 调度中的悲观假设。然而，在 FMC 中，MC 任务的行为仍然在离线阶段进行分析。FMC调度框架中还没有研究动态松弛等运行时行为。在本文中，我们提出了一个基于利用率的 FMC 任务松弛调度框架。特别是，我们在运行时监控任务执行并收集由任务提前完成产生的动态松弛。然后，这些松弛可以被高关键任务使用以减少模式切换，或者被低关键任务使用，以便在执行时间更长的情况下触发更少的暂停，从而提高服务质量。我们通过广泛的模拟评估我们的方法，实验结果证明了所提出方法的有效性。