FDALB:数据中心网络的流量分布感知负载均衡

Shuo Wang, Jiao Zhang, Tao Huang, Tian Pan, Jiang Liu, Yun-jie Liu
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引用次数: 9

摘要

本文提出了一种基于流分布感知的负载平衡机制FDALB,旨在减少流冲突并实现高可扩展性。与大多数集中式方法一样,FDALB使用集中式控制器来获取网络视图和拥塞信息。然而,FDALB将流分为短流和长流。短流路径和长流路径分别由分布式开关和集中控制器控制。因此,控制器只处理流的一小部分,以实现高可伸缩性。为了进一步减少控制器的开销,FDALB利用终端主机标记长流,因此交换机可以通过检查标记轻松确定长流。此外,FDALB可以自适应调整各端主机的阈值,以跟上流量分布动态。
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FDALB: Flow distribution aware load balancing for datacenter networks
We present FDALB, a flow distribution aware load balancing mechanism aimed at reducing flow collisions and achieving high scalability. FDALB, like the most of centralized methods, uses a centralized controller to get the view of networks and congestion information. However, FDALB classifies flows into short flows and long flows. The paths of short flows and long flows are controlled by distributed switches and the centralized controller respectively. Thus, the controller handles only a small part of flows to achieve high scalability. To further reduce the controller's overhead, FDALB leverages end-hosts to tag long flows, thus switches can easily determine long flows by inspecting the tag. Besides, FDALB can adaptively adjust the threshold at each end-host to keep up with the flow distribution dynamics.
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