Fast-Converging Congestion Control in Datacenter Networks

Abstract

The widespread deployment of Remote Direct Memory Access (RDMA) in datacenter networks increases the stringency for convergence speed when congestion occurs. Fast convergence significantly reduces buffer occupancy, which in turn lessens the probability of triggering Priority-based Flow Control (PFC). Besides, the propagation delay becomes shorter with rapidly growing link speed, which correspondingly makes the queueing delay a major part of end-to-end latency. Fast convergence and low buffer occupancy become more essential for lowering queue delay and flow complete time. We present DQCC (Double-Q Congestion Control), a fast-converging congestion control scheme, which consists of two fundamental components: (i) an ECN-marking-ratio-based queue buffer occupancy estimating (QBOE) solution and (ii) a queue-building-rate driven rate adjustment (QDRA) mechanism to achieve fast convergence. We conduct extensive experiments to evaluate the performance of DQCC, and the results show that DQCC greatly accelerates the convergence process. DQCC achieves low tail latency and low buffer occupancy simultaneously.