Fair Quantized Congestion Notification in Data Center Networks
Fair Quantized Congestion Notification in Data Center Networks
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DOI：
10.1109/tcomm.2013.102313.120809
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发表时间：
2013-10
影响因子：
8.3
通讯作者：
Yan Zhang;N. Ansari
中科院分区：
文献类型：
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作者：
Yan Zhang;N. Ansari
量化拥塞通知（QCN）已经由IEEE数据中心桥接任务组针对IEEE 802.1Qau开发，以在数据中心网络（DCN）中的以太网层或第2层处提供拥塞控制。QCN的一个缺点是当共享一个瓶颈链路时，不同流的速率不公平。在本文中，我们提出了一种增强的QCN拥塞通知算法，称为公平QCN（QCN），以提高速率分配的公平性，多个流共享一个瓶颈链路的DCN。拥塞控制网络通过联合队列和单流监测来识别拥塞源，通过组播将拥塞信息反馈给各个拥塞源，并保证收敛到统计公平性。我们分析了稳定性和公平性的BSCCN通过李雅普诺夫函数和评估BSCCN的性能，通过模拟的队列长度稳定性，链路吞吐量和速率分配的业务流与不同的流量动态下的三个网络拓扑结构。仿真结果证实了QCN的速率分配不公平性，验证了QCN在TCP Incast环境下保持了队列长度的稳定性，成功地为共享链路容量的各个业务源分配了公平的共享速率，提高了TCP吞吐量性能。
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.