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Fixed-Priority Scheduling of Mixed Soft and Hard Real-Time Tasks on Multiprocessors

机译:多处理器混合软硬实时任务的固定优先级调度

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This paper answers several open questions of practical concerns to schedule soft real-time (SRT) tasks, to guarantee their bounded tardiness, under fixed-priority scheduling in homogeneous multiprocessor systems. We consider both cases with only SRT tasks and with mixed sets of SRT and hard real-time (HRT) tasks. For the case in which the system has only SRT tasks, we show that any fixed priority assignment policy yields a capacity augmentation factor of 2 - 1/M where M is the number of processors. We prove the optimality of the utilization-monotonic (UM) priority assignment (i.e., assigning higher priorities to high-utilization tasks) under our sufficient test for guaranteeing bounded tardiness. We show that UM priority assignment can yield a utilization bound of M+1/2M, which is shown asymptotically the best possible bound. For the case in which the system has mixed SRT and HRT tasks, we present two new fixed-priority assignment algorithms and their associated schedulability tests. One is a clustering-based greedy priority assignment policy and another is based on Audsley's optimal priority assignment (OPA) approach. We show that the utilization bounds, augmentation factors, and speedup factors are still maintained by the hard real-time cases. Therefore, introducing soft real-time tasks does not create additional problems (at least in those metrics) for scheduling if the priority assignments are properly done. As demonstrated by extensive experiments, these two policies yield reasonably good performance overall and much better performance than the deadline-monotonic priority assignment.
机译:本文回答了实际问题的几个开放性问题,以安排软实时(SRT)任务,以保证其在同一性多处理器系统中的固定优先级调度下的有界迟到的。我们考虑两个只有SRT任务的案例,以及混合SRT和硬实时(HRT)任务。对于系统仅具有SRT任务的情况,我们显示任何固定的优先级分配策略会产生2 - 1 / m的容量增强因子,其中M是处理器的数量。我们证明了利用 - 单调(UM)优先级分配(即,为高利用率为高利用率的优先级分配)的最优性,以保证有界迟到。我们表明UM优先级分配可以产生M + 1 / 2M的利用率,这被渐近地显示了最佳绑定。对于系统混合SRT和HRT任务的情况,我们呈现了两个新的固定优先级分配算法及其相关的调度性测试。一个是基于聚类的贪婪优先级分配政策,另一个是基于Audsley的最佳优先级分配(OPA)方法。我们展示了利用范围,增强因子和加​​速因子仍然由硬实时案例维持。因此,如果正确完成优先级分配,则引入软实时任务不会创建其他问题(至少在这些度量标准中),以便调度。正如广泛的实验所证明的那样,这两种政策总体上总体表现优于截止日期 - 单调优先权任务。

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