Delay-Based Trend-Aware Congestion Control in Lossless Datacenter Network
In current high-speed datacenter networks,congestion control is crucial for ensuring consistent high performance.Over the past decade,researchers and developers have explored several congestion signals such as ECN,RTT,and INT.However,most of the existing congestion control algorithms suffer from either imprecise congestion detection due to ambiguous signals or excessive bandwidth loss due to aggressive rate decrease.This paper proposes a novel congestion control mechanism called DELTA,which is a delay-based trend-aware approach designed for lossless datacenter networks.DELTA leverages the change in RTT to learn the congestion trend and adjusts the sending rate accordingly.By analyzing the congestion trend,the sender reacts by adjusting the sending rate to a reasonable level,while still maintaining high bandwidth utilization to dismiss congestion.We evaluate DELTA extensively in NS-3 simulations and the experimental results demonstrate that DELTA outperforms the compared congestion control algorithms in both FCT and convergence speed.
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