有限缓冲区网络的最大吞吐量及其在缓冲横杆中的应用

P. Giaccone, Emilio Leonardi, D. Shah
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引用次数: 31

摘要

在过去的一二十年里,分组网络的出现激发了许多研究者对队列网络性能的研究。然而,前面的大部分工作都假定队列大小是无限的。相反,在本文中,我们研究了有限队列大小的流控无损网络的最大可实现吞吐量。在这种网络中,吞吐量取决于所使用的数据包调度策略。作为本文的主要内容,我们得到了一种动态调度策略,该策略在网络内部节点上以最小的有限队列大小实现最大吞吐量(等于无限队列大小时的最大吞吐量)。虽然该政策的表现是理想的,但它非常复杂,因此难以实施。这将引导我们设计更简单且可能实现的策略。对于此策略,我们在吞吐量和队列大小之间获得了一种自然的权衡。将研究结果应用于具有缓冲交叉条结构的分组交换机。我们提出了一个简单的,可实现的,分布式调度策略,在最小的内部缓冲区存在的情况下提供高吞吐量。我们还获得了吞吐量,内部加速和缓冲区大小之间的自然权衡,为交换机设计人员提供了一系列设计。据作者所知,这是研究具有有限队列大小的一般网络的吞吐量的第一次尝试之一。我们相信我们的方法是通用的,可以在其他环境中使用。
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On the maximal throughput of networks with finite buffers and its application to buffered crossbars
The advent of packet networks has motivated many researchers to study the performance of networks of queues in the last decade or two. However, most of the previous work assumes the availability of infinite queue-size. Instead, in this paper, we study the maximal achievable throughput in a flow-controlled lossless network with finite-queue size. In such networks, throughput depends on the packet scheduling policy utilized. As the main of this paper, we obtain a dynamic scheduling policy that achieves the maximal throughput (equal to the maximal throughput in the presence of infinite queue-size) with a minimal finite queue-size at the internal nodes of the network. Though the performance of the policy is ideal, it is quite complex and hence difficult to implement. This leads us to a design of simpler and possibly implementable policy. We obtain a natural trade-off between throughput and queue-size for this policy. We apply our results to the packet switches with buffered crossbar architecture. We propose a simple, implementable, distributed scheduling policy which provides high throughput in the presence of minimal internal buffer. We also obtain a natural trade-off between throughput, internal speedup and buffer-size providing a switch designer with a gamut of designs. To the best of authors' knowledge, this is one of the first attempts to study the throughput for general networks with finite queue-size. We believe that our methods are general and can be useful in other contexts.
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