雾中的排队:有限知识下的缓冲和调度

Itamar Cohen, Gabriel Scalosub
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引用次数: 3

摘要

调度和管理有界缓冲区的队列是计算机网络中最基本的问题之一。传统上,通常假设每个包的所有属性在到达时立即已知。然而,随着流量变得越来越异构和复杂,这些假设在许多情况下是无效的。特别是,在各种场景中,只有在数据包经过一些初始处理之后,才能获得有关数据包特征的信息。在这项工作中,我们研究了有限知识下的队列管理问题。我们首先展示了在这种情况下任何算法的竞争比的下界。接下来,我们使用从这些边界中获得的见解来确定适合该问题的几个算法概念,并使用这些指导方针来设计具体的算法框架。我们分析了我们提出的算法的性能,并进一步展示了它如何在各种设置中实现,这些设置因未知信息的类型和性质而不同。我们通过模拟研究进一步验证了我们的结果和算法方法,该研究在面对有限知识的情况下为我们的算法设计原则提供了进一步的见解。
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Queueing in the mist: Buffering and scheduling with limited knowledge
Scheduling and managing queues with bounded buffers are among the most fundamental problems in computer networking. Traditionally, it is often assumed that all the properties of each packet are known immediately upon arrival. However, as traffic becomes increasingly heterogeneous and complex, such assumptions are in many cases invalid. In particular, in various scenarios information about packet characteristics becomes available only after the packet has undergone some initial processing. In this work, we study the problem of managing queues with limited knowledge. We start by showing lower bounds on the competitive ratio of any algorithm in such settings. Next, we use the insight obtained from these bounds to identify several algorithmic concepts appropriate for the problem, and use these guidelines to design a concrete algorithmic framework. We analyze the performance of our proposed algorithm, and further show how it can be implemented in various settings, which differ by the type and nature of the unknown information. We further validate our results and algorithmic approach by a simulation study that provides further insights as to our algorithmic design principles in face of limited knowledge.
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