BCN: A Fast Notified Backpressure Congestion Management
Abstract: Applications such as cloud computing, big data processing, and artificial intelligence, demand high bandwidth and low latency in datacenter networks. Existing congestion control and flow control schemes at switches have limitations in granularity, fairness, and signal transmission delay. This paper proposes a fast notified per-hop per-flow backpressure congestion management, called BCN. BCN dynamically allocates queues for each flow at each switch hop, precisely pauses upstream queues based on queuing conditions, and enables non-paused queues to continue transmission. The switch sends network status notifications, collaborating with sender-side speed up and deceleration strategies to achieve rapid traffic rate adjustment. To the best of our knowledge, this is the first work focusing on fast rate adjustment of per-hop per-flow traffic. We evaluate BCN in real traffic scenarios and observe significant reductions in flow completion time of 53% and 60% compared to BFC and DCQCN, respectively. Under high workload conditions, BCN also improves network throughput. In high incast scenarios, BCN outperforms BFC and DCQCN, reducing flow completion time by 67.7% and 74.2%, respectively, while maintaining throughput comparable to BFC. Additionally, BCN minimizes transmission delay, ensuring nearly lossless transmission and optimizing overall throughput.
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