A model predictive control approach to flow pacing for TCP
A model predictive control approach to flow pacing for TCP
复制标题
TCP 流量调步的模型预测控制方法
DOI：
10.1109/allerton.2017.8262845
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
D. Ghosal
中科院分区：
文献类型：
--
作者：
David Fridovich;Nathan Hanford;Margaret P. Chapman;C. Tomlin;M. Farrens;D. Ghosal
互联网流量管理的一个关键挑战是设计算法，以补充完善的协议，如传输控制协议（TCP），同时解决其局限性。在通常从较高带宽连接过渡到较低带宽连接的长路径上的大型所谓“大象”流的背景下，挑战变得更大。在这些转换点，当缓冲区过度供应时形成持久队列，或者当缓冲区供应不足时发生数据包丢失;这两种情况都会导致端到端性能下降和/或高度可变。理想情况下，对于此类场景，源应该“学习”并设置与较低带宽连接相匹配的起搏速率。本文采用基于模型的滚动时域控制策略设计了一种定步控制方法。每个新的往返时间（RTT）测量值首先被纳入线性时变（LTV）预测模型。随后，我们解决了一步前瞻优化问题，该问题根据最新模型找到最佳权衡RTT、RTT方差和吞吐量的起搏速率。我们在Linux操作系统上实现了我们的概念验证控制策略以及现有的CoDel排队规则（qdisc）和HTCP排队控制算法。我们的初步结果表明显着减少的RTT和吞吐量的方差，从而在更可预测的整体性能。
A key challenge in the management of Internet traffic is the design of algorithms that complement well-established protocols, such as the Transmission Control Protocol (TCP), and simultaneously address their limitations. The challenge becomes greater in the context of large so-called “elephant” flows over long paths that often transition from higher to lower bandwidth connections. At these transition points either persistent queues are formed when buffers are over-provisioned or packet loss occurs when buffers are under-provisioned; both cases lead to degraded and/or highly variable end-to-end performance. Ideally, for such scenarios, the source should “learn” and set a pacing rate that matches the lower bandwidth connection. In this paper, we adopt a model-based receding horizon control strategy to design a pacing control method. Each new round-trip time (RTT) measurement is first incorporated into a linear time-varying (LTV) predictive model. Subsequently, we solve a one-step look-ahead optimization problem which finds the pacing rate which optimally trades off RTT, variance in RTT, and throughput according to the most up-to-date model. We implemented our proof-of-concept control strategy on the Linux operating system alongside the existing CoDel queuing discipline (qdisc) and HTCP congestion-control algorithm. Our preliminary results indicate significant reduction in the variances of the RTT and the throughput, resulting in more predictable performance overall.
使用状态预测控制的 TCP/AQM 网络拥塞控制
DOI：
--
发表时间：
2006
期刊：
Electrical Engineering in Japan 156・3
影响因子：
--
作者：
T.Azuma;T.Fujita;M.Fujita
通讯作者：
M.Fujita
使用自旋量子位进行运动平均
DOI：
--
发表时间：
2017
期刊：
影响因子：
--
作者：
大野圭司;森貴洋;森山悟士
通讯作者：
森山悟士