自动调优活动队列管理

Joe H. Novak, S. Kasera
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引用次数: 3

摘要

主动队列管理(AQM)算法先发制人地丢弃数据包,以防止通过网络的不必要延迟,同时保持高利用率。已经提出了许多AQM思想,但没有一个被广泛采用,因为这些思想依赖于参数和阈值的预规范或预调优,而这些参数和阈值不一定适应动态网络条件。我们开发了一种AQM算法,该算法仅依赖于网络运行时测量和自然阈值,即延迟利用曲线的拐点。基于该算法能使系统在延迟利用曲线的拐点处运行的关键特性,我们将其称为延迟利用拐点算法(DUK)。我们在构建的Linux内核测试平台和ns-3网络模拟器中实现和评估DUK。我们发现,在不同的网络条件下,与其他算法相比,DUK可以获得更少的排队延迟和更少的流完成时间,而几乎没有减少链路利用率。
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Auto-tuning active queue management
Active queue management (AQM) algorithms preemptively drop packets to prevent unnecessary delays through a network while keeping utilization high. Many AQM ideas have been proposed, but none have been widely adopted because these rely on pre-specification or pre-tuning of parameters and thresholds that do not necessarily adapt to dynamic network conditions. We develop an AQM algorithm that relies only on network runtime measurements and a natural threshold, the knee on the delay-utilization curve. We call our AQM algorithm Delay Utilization Knee (DUK) based on its key characteristic of keeping the system operating at the knee of the delay-utilization curve. We implement and evaluate DUK in the Linux kernel in a testbed, that we build, and in the ns-3 network simulator. We find that DUK can attain reduced queuing delay and reduced flow completion times compared to other algorithms with virtually no reduction in link utilization under varying network conditions.
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