Active Queue Management (AQM) aims to prevent bufferbloat and serial drops in router and switch FIFO packet buffers that usually employ drop-tail queueing. AQM describes methods to send proactive feedback to TCP flow sources to regulate their rate using selective packet drops or markings. Traditionally, AQM policies relied on heuristics to approximately provide Quality of Service (QoS) such as a target delay for a given flow. These heuristics are usually based on simple network and TCP control models together with the monitored buffer filling. A primary drawback of these heuristics is that their way of accounting flow characteristics into the feedback mechanism and the corresponding effect on the state of congestion are not well understood. In this work, we show that taking a probabilistic model for the flow rates and the dequeueing pattern, a Semi-Markov Decision Process (SMDP) can be formulated to obtain an optimal packet dropping policy. This policy-based AQM, denoted PAQMAN, takes into account a steady-state model of TCP and a target delay for the flows. Additionally, we present an inference algorithm that builds on TCP congestion control in order to calibrate the model parameters governing underlying network conditions. Finally, we evaluate the performance of our approach using simulation compared to state-of-the-art AQM algorithms.

翻译：活跃的 Quue 管理 (AQM) 旨在 防止路由器中缓冲膨胀和序列下降, 并切换通常使用滴尾队列的 FIFO 包缓冲。 AQM 描述向 TCP 流源发送主动反馈的方法, 以便使用选择性的袋滴滴或标记来调节其速度。 传统上, AQM 政策依赖超常性来大致提供服务质量( QOS ), 如特定流的目标延迟 。 这些超常性通常基于简单的网络和 TCP 控制模型以及受监测的缓冲。 这些超常性的一个主要缺点是, 其向反馈机制的会计流特性和对拥堵状态的相应影响没有得到很好理解。 在这项工作中, 我们显示, 可以用流动率和递解模式模式的半马尔科夫 决策程序( SMDP ) 来获得最佳的放弃政策 。 这种基于政策的 AQM QM ( 意称 PAQM MAN ) 的 模式, 其首要缺点是考虑到 TCP 的稳态模式模式 模式 和 目标延迟化网络控制流程的升级 。