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Multiple-resource periodic scheduling problem: how much fairness is necessary?

机译:多资源周期性调度问题:需要多少公平?

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The Pfair algorithms are optimal for independent periodic real-time tasks executing on a multiple-resource system. However, they incur a high scheduling overhead by making scheduling decisions in every time unit to enforce proportional progress for each task. In this paper, we will propose a novel scheduling algorithm, boundary fair (BF), which makes scheduling decisions and enforces fairness to tasks only at period boundaries. The BF algorithm is also optimal in the sense that it achieves 100% system utilization. Moreover, by making scheduling decisions at period boundaries, BF effectively reduces the number of scheduling points. Theoretically, the BF algorithm has the same complexity as that of the Pfair algorithms. But, in practice, it could reduce the number of scheduling points dramatically (e.g., up to 75% in our experiments) and thus reduce the overall scheduling overhead, which is especially important for online scheduling.
机译:对于在多资源系统上执行的独立的周期性实时任务,Pfair算法是最佳的。但是,它们通过在每个时间单位中制定计划决策来强制执行每个任务的按比例进度而导致较高的计划开销。在本文中,我们将提出一种新颖的调度算法-边界公平(BF),该算法可以制定调度决策并仅在周期边界对任务强制执行公平性。在达到100%系统利用率的意义上,BF算法也是最佳的。此外,通过在周期边界进行调度决策,BF有效地减少了调度点的数量。从理论上讲,BF算法的复杂度与Pfair算法相同。但是,实际上,它可以大大减少调度点的数量(例如,在我们的实验中最多可减少75%),从而减少总体调度开销,这对于在线调度而言尤其重要。

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