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Randomized scheduling algorithms for high-aggregate bandwidth switches

机译:高聚合带宽交换机的随机调度算法

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The aggregate bandwidth of a switch is its port count multiplied by its operating line rate. We consider switches with high-aggregate bandwidths; for example, a 30-port switch operating at 40 Gb/s or a 1000-port switch operating at 1 Gb/s. Designing high-performance schedulers for such switches with input queues is a challenging problem for the following reasons: (1) high performance requires finding good matchings; (2) good matchings take time to find; and (3) in high-aggregate bandwidth switches there is either too little time (due to high line rates) or there is too much work to do (due to a high port count). We exploit the following features of the switching problem to devise simple-to-implement, high-performance schedulers for high-aggregate bandwidth switches: (1) the state of the switch (carried in the lengths of its queues) changes slowly with time, implying that heavy matchings will likely stay heavy over a period of time and (2) observing arriving packets will convey useful information about the state of the switch. The above features are exploited using hardware parallelism and randomization to yield three scheduling algorithms - APSARA, LAURA, and SERENA. These algorithms are shown to achieve 100% throughput and simulations show that their delay performance is quite close to that of the maximum weight matching, even when the traffic is correlated. We also consider the stability property of these algorithms under generic admissible traffic using the fluid-model technique. The main contribution of this paper is a suite of simple to implement, high-performance scheduling algorithms for input-queued switches. We exploit a novel operation, called MERGE, which combines the edges of two matchings to produce a heavier match, and study of the properties of this operation via simulations and theory. The stability proof of the randomized algorithms we present involves a derandomization procedure and uses methods which may have wider applicability.
机译:交换机的总带宽是其端口数乘以其工作线速。我们考虑具有高聚合带宽的交换机。例如,以40 Gb / s运行的30端口交换机或以1 Gb / s运行的1000端口交换机。为具有输入队列的此类交换机设计高性能调度程序是一个具有挑战性的问题,原因如下:(1)高性能需要找到良好的匹配; (2)好的匹配需要花费时间才能找到; (3)在高聚合带宽的交换机中,时间太短(由于高线速)或太多的工作要做(由于端口数高)。我们利用交换问题的以下特征,为高聚合带宽的交换器设计易于实现的高性能调度程序:(1)交换器的状态(在其队列长度中承载)随时间缓慢变化,这意味着繁重的匹配可能会在一段时间内保持繁重的状态;(2)观察到达的数据包将传达有关交换机状态的有用信息。使用硬件并行性和随机化来利用上述功能,以产生三种调度算法-APSARA,LAURA和SERENA。这些算法显示出达到100%的吞吐量,并且仿真显示它们的延迟性能与最大权重匹配的延迟性能非常接近,即使在流量相关时也是如此。我们还使用流体模型技术考虑了这些算法在通用允许流量下的稳定性。本文的主要贡献是针对输入排队交换机的一套易于实现的高性能调度算法。我们利用一种称为MERGE的新颖操作,该操作将两个匹配的边缘结合在一起以产生更重的匹配,并通过模拟和理论研究此操作的属性。我们目前提出的随机算法的稳定性证明涉及一个去随机化程序,并使用可能具有更广泛适用性的方法。

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