Data center network is composed of high-speed Ethernet extended in a limited area of a data center building, so its RTT is extremely small of µsec order. In order to regulate data center network delay large part of which is queuing delay, QCN is proposed for layer 2 congestion control in IEEE 802.1Qau. QCN controls transmission rate of the sender by congestion feedback from a congested switch. QCN adopts probabilistic feedback transmission to reduce the control overhead. When the number of flows through a bottleneck link increases, some flows might receive no feedback even in congestion phase due to probabilistic feedback transmission. In this situation, queue length might be significantly fluctuated. In this paper, we propose a new delay-based congestion detection and control method. Our proposed delay-based congestion control is cooperated with the conventional QCN so as to detect and react congestion not detected by QCN.

Quantized congestion notification (QCN), discussed in IEEE 802.1Qau, is one of the most promising Layer 2 congestion control methods for data center networks. Because data center networks have fundamentally symmetric structures and links are designed to have high link utilization, data center flows often pass through multiple bottleneck links. QCN reduces its transmission rate in a probabilistic manner with each congestion notification feedback reception, which might cause excessive regulation of the transmission rate in a multiple-bottleneck case because each bottleneck causes congestion feedbacks. We have already proposed QCN with bottleneck selection (QCN/BS) for multicast communications in data center networks. Although QCN/BS was originally proposed for multicast communications, it can also be applied to unicast communications with multiple bottleneck points. QCN/BS calculates the congestion level for each switch based on feedback from the switch and adjusts its transmission rate to the worst congestion level. In this paper, we preliminarily evaluate QCN/BS in unicast communications with multiple tandem bottleneck points. Our preliminary evaluation reveals that QCN/BS can resolve the excessive rate regulation problem of QCN but has new fairness problems for long-hop flows. To resolve this, we propose a new algorithm that integrates QCN/BS and our already proposed Adaptive BC_LIMIT. In Adaptive BC_LIMIT, the opportunities for rate increase are almost the same for all flows even if their transmission rates differ, enabling an accelerated convergence of fair rate allocation among flows sharing a bottleneck link. The integrated algorithm is the first congestion control mechanism that takes into account unicast flows passing through multiple tandem bottleneck points based on QCN. Furthermore, it does not require any modifications of switches used in QCN. Our simulation results show that our proposed integration of QCN/BS and Adaptive BC_LIMIT significantly mitigates the fairness problem for unicast communications with multiple bottleneck points in data center networks.