In this paper we consider the problem of mixed-criticality (MC) scheduling of implicit-deadline sporadic task systems on a homogenous multiprocessor platform. Focusing on dual-criticality systems, algorithms based on the fluid scheduling model have been proposed in the past. These algorithms use a dual-rate execution model for each high-criticality task depending on the system mode. Once the system switches to the high-criticality mode, the execution rates of such tasks are increased to meet their increased demand. Although these algorithms are speed-up optimal, they are unable to schedule several feasible dual-criticality task systems. This is because a single fixed execution rate for each high-criticality task after the mode switch is not efficient to handle the high variability in demand during the transition period immediately following the mode switch. This demand variability exists as long as the carry-over jobs of high-criticality tasks, that is jobs released before the mode switch, have not completed. Addressing this shortcoming, we propose a multi-rate fluid execution model for dual-criticality task systems in this paper. Under this model, high-criticality tasks are allocated varying execution rates in the transition period after the mode switch to efficiently handle the demand variability. We derive a sufficient schedulability test for the proposed model and show its dominance over the dual-rate fluid execution model. Further, we also present a speed-up optimal rate assignment strategy for the multi-rate model, and experimentally show that the proposed model outperforms all the existing MC scheduling algorithms with known speed-up bounds.

中文翻译：

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多处理器上混合临界系统的多速率流体调度

在本文中，我们考虑了同构多处理器平台上隐式截止时间零星任务系统的混合临界 (MC) 调度问题。针对双临界系统，过去已经提出了基于流体调度模型的算法。这些算法根据系统模式对每个高危任务使用双速率执行模型。一旦系统切换到高临界模式，此类任务的执行率就会增加，以满足其增加的需求。虽然这些算法是加速优化的，但它们无法调度几个可行的双临界任务系统。这是因为模式切换后每个高关键性任务的单个固定执行速率对于处理紧接模式切换后的过渡期间需求的高可变性是无效的。只要高危任务的结转作业，即在模式切换之前发布的作业，还没有完成，这种需求可变性就存在。针对这一缺点，我们在本文中提出了一种双关键性任务系统的多速率流体执行模型。在此模型下，高危任务在模式切换后的过渡期内被分配不同的执行率，以有效处理需求变化。我们为所提出的模型推导出了充分的可调度性测试，并显示了它在双速率流体执行模型上的优势。更多，