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Partitioned Fair Round Robin: A Fast and Accurate QoS Aware Scheduler for Embedded Systems

机译:分区公平轮询:用于嵌入式系统的快速,准确的QoS感知调度程序

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A large class of embedded systems today which concurrently execute numerous independent QoS sensitive applications like streaming audio and video, web browsing, email, interactive gaming etc. Have proportional share schedulers at their heart as the principal resource multiplexing strategy. However, producing schedulers that have both low scheduling overheads as well as good proportional share allocation accuracy have proved to be a daunting task. On one hand, we have schemes that provide optimal task allocation fairness accuracy, but generally suffer scheduling overheads that are at least logarithmic to the number of tasks. On the other hand there are O (1) complexity round-robin based algorithms, but they generally fail to provide good fairness properties. This paper presents Partitioned Proportional Round-Robin (PPRR), a two level hierarchical O (1) proportional share scheduler that achieves near optimal fairness accuracy while executing a mix of jobs with varying priorities in most practical scenarios. Simulation based experimental results reveal that even on systems containing up to 50 tasks with skewed execution rate requirements, a PPRR scheduler with just eight groups is able to provide less than about one percent deviation per task with respect to their ideal execution rates.
机译:当今,大量嵌入式系统可同时执行众多独立的QoS敏感应用程序,例如流音频和视频,Web浏览,电子邮件,交互式游戏等。其核心是按比例分配调度程序作为主要的资源复用策略。然而,事实证明,既具有较低的调度开销又具有良好的比例份额分配准确性的调度器是一项艰巨的任务。一方面,我们提供的方案可提供最佳的任务分配公平性准确性,但通常会遭受至少与任务数量成对数的调度开销。另一方面,有基于O(1)复杂度的轮询算法,但是它们通常无法提供良好的公平性。本文介绍了分区比例轮循机制(PPRR),这是一种两级分层O(1)比例份额调度程序,在大多数实际情况下,它在执行具有不同优先级的作业混合时,可以获得接近最佳的公平性准确性。基于仿真的实验结果表明,即使在包含多达50个具有偏斜执行速率要求的任务的系统上,具有八个组的PPRR调度程序也能相对于其理想执行速率为每个任务提供小于大约1%的偏差。

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