首页> 外文会议>IEEE Annual Computer Software and Applications Conference Workshops >Flow-Aware Congestion Control to Improve Throughput under TCP Incast in Datacenter Networks
【24h】

Flow-Aware Congestion Control to Improve Throughput under TCP Incast in Datacenter Networks

机译:流动感知拥塞控制提高DATCATER网络中TCP本发明下的吞吐量

获取原文

摘要

Data enter networks (DCNs) host cloud computing and various applications. In this environment, there are mice and elephant flows and the partition/aggregate communication pattern is common, so TCP in cast may often occur. Massive mice flows directly affect the elephant flows under in cast, and the standard TCP mechanism or SDN approach with centralized controller is insufficient to solve this problem. In this paper, we focused on how a flow-aware congestion control method that takes into account flow characteristics can improve throughput under in cast. It is required to establish our long-term goal that provides different network level services based on flow characteristics. We propose a switch-based method that identifies target flows and provides different congestion control using explicit congestion notification (ECN). Although our method uses ECN, it does not require any change to TCP stacks on end nodes or a dedicated queue for the targets. In our experiments, we focused on the throughput of flows, and selected elephant flows as targets because their throughput is more sensitive than mice flows. We compared the experimental results from our method to those of standard TCP, ECN, and a dedicated queue for elephants. Our method improved the aggregate throughput of elephant flows by 1.7x to 5.1x and the good put of elephant flows by 1.9x to 5.4x compared to those of the above methods under our in cast scenario.
机译:数据输入网络(DCN)主机云计算和各种应用程序。在这种环境中,有小鼠和大象流动,并且分区/聚合通信模式是常见的,因此施放中的TCP可能经常发生。大规模的小鼠流动直接影响铸造的大象流量,标准的TCP机制或带集中控制器的SDN方法不足以解决这个问题。在本文中,我们专注于如何进入考虑流动特性的流动感知控制方法可以提高铸造的吞吐量。需要建立我们的长期目标,基于流量特征提供不同的网络级别服务。我们提出了一种基于交换机的方法,用于使用显式拥塞通知(ECN)来识别目标流并提供不同的拥塞控制。虽然我们的方法使用ECN,但它不需要在结束节点上的TCP堆栈或目标专用队列的任何更改。在我们的实验中,我们专注于流动的吞吐量,并且选择的大象作为目标流动,因为它们的吞吐量比小鼠流动更敏感。我们将我们的方法与标准TCP,ECN和Elephants专用队列的实验结果进行了比较。我们的方法改善了大象流量的总吞吐量1.7倍至5.1倍,与我们在我们的演员方案下的上述方法相比,大象的良好放置流量为1.9倍至5.4倍。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号