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Adaptive runtime shaping for mixed-criticality systems

机译:混合关键性系统的自适应运行时整形

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This paper investigates runtime shaping for mixed-criticality systems to increase the system QoS. Unlike the previous work in the literature that enforces an offline workload bound, an adaptively shaping approach is proposed where the incoming workload of the low-critical tasks is regulated by the actual demand of the high-critical tasks. This actual demand is adaptively updated using the historical arrival information of the high-critical tasks and thus can maximize the runtime QoS of low-critical tasks. To reduce the online overheads of computing the workload demand, a lightweight scheme with the complexity of O(n log(m)) is developed. Experiments are also provided to demonstrate the effectiveness and efficiency of our approach.
机译:本文调查了混合关键性系统的运行时整形,以增加系统QoS。与在脱机工作量绑定的文献中的先前工作不同,提出了一种自适应地塑造方法,其中低关键任务的输入工作量由高关键任务的实际需求调节。使用高关键任务的历史到达信息,自适应更新此实际需求,从而可以最大化低关键任务的运行时QoS。为了减少计算工作负载需求的在线开销,开发了一种具有复杂性的轻量级方案(n log(m))。还提供了实验以证明我们方法的有效性和效率。

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