Fair quantized congestion notification in data center networks

Yan Zhang, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Quantized Congestion Notification (QCN) has been developed for IEEE 802.1Qau to provide congestion control at the Ethernet Layer or Layer 2 in data center networks (DCNs) by the IEEE Data Center Bridging Task Group. One drawback of QCN is the rate unfairness of different flows when sharing one bottleneck link. In this paper, we propose an enhanced QCN congestion notification algorithm, called fair QCN (FQCN), to improve rate allocation fairness of multiple flows sharing one bottleneck link in DCNs. FQCN identifies congestion culprits through joint queue and per flow monitoring, feedbacks individual congestion information to each culprit through multi-casting, and ensures convergence to statistical fairness. We analyze the stability and fairness of FQCN via Lyapunov functions and evaluate the performance of FQCN through simulations in terms of the queue length stability, link throughput and rate allocations to traffic flows with different traffic dynamics under three network topologies. Simulation results confirm the rate allocation unfairness of QCN, and validate that FQCN maintains the queue length stability, successfully allocates the fair share rate to each traffic source sharing the link capacity, and enhances TCP throughput performance in the TCP Incast setting.

Original languageEnglish (US)
Article number6648356
Pages (from-to)4690-4699
Number of pages10
JournalIEEE Transactions on Communications
Volume61
Issue number11
DOIs
StatePublished - Nov 2013

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • Congestion notification
  • Data center network (DCN)
  • Quantized congestion notification (QCN)

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