IEEE Access (Jan 2020)

A-ECN Minimizing Queue Length for Datacenter Networks

  • Shuo Wang,
  • Jiao Zhang,
  • Tao Huang,
  • Tian Pan,
  • Jiang Liu,
  • Yunjie Liu

DOI
https://doi.org/10.1109/access.2020.2979216
Journal volume & issue
Vol. 8
pp. 49100 – 49111

Abstract

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Recently, Explicit Congestion Notification (ECN) has been leveraged by DCTCP and its successive protocols to reduce the latency in datacenters. However, we find that DCTCP may induce the queue underflow and high latency in multi-queue scenarios and even single-queue environments. Our analysis concludes that the problem is caused by improper ECN marking thresholds of DCTCP. In this paper, an Adaptive ECN (A-ECN) marking scheme is proposed to enhance the performance of the ECN marking scheme of DCTCP.A-ECN is designed to minimize queue length as well as keeping high link utilization. More importantly, A-ECN can adaptively adjust ECN marking thresholds in different scenarios to achieve good generality. Therefore, network operators can directly deploy A-ECN in various environments regardless of underlying bandwidth, packet schedulers and the number of concurrent flows. At last, the testbed evaluation results show that A-ECN can minimize queue length and maintain high throughput. The flow completion times (FCT) for short flows could be reduced by up to 40% compared to the ECN marking scheme of DCTCP.

Keywords