Phase Plane Analysis of Quantized Congestion Notification for Data Center Ethernet

• Published in: IEEE/ACM transactions on networking Vol. 23; no. 1; pp. 1 - 14
• Main Authors: Jiang, Wanchun, Ren, Fengyuan, Lin, Chuang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Computer centers; Differential equations; Economic models; Ethernet; Mathematical model; Network switching; Phase plane analysis; Product introduction; quantized congestion notification; sliding mode motion; stability; Stability analysis; Switches; Trajectory
• DOI: 10.1109/TNET.2013.2292851
• ISSN: 1063-6692

Currently, Ethernet is being enhanced to become the unified switch fabric in data centers. With the unified switch fabric, the cost on redundant devices is reduced, while the design and management of data center networks are simplified. Congestion management is one of the indispensable enhancements on Ethernet, and Quantized Congestion Notification (QCN) has just been ratified as the formal standard. Though QCN has been investigated for several years, there exist few in-depth theoretical analyses on QCN. The most possible reason is that QCN is heuristically designed and involves the property of variable structure. The classic linear analysis method is incapable of handling the segmented nonlinearity of the variable structure system. In this paper, we use the phase plane method, which is suitable for systems of segmented nonlinearity, to analyze the QCN system. The overall dynamic behaviors of the QCN system are presented, and the sufficient conditions for the stable QCN system are deduced. These sufficient conditions serve as guidelines toward proper parameters setting. Moreover, we find that the stability of QCN is mainly promised by the sliding mode motion, which is the underlying reason for QCN's stable queue shown in numerous simulations and experiments. Experiments on the NetFPGA platform verify that the analytical results can explain the complex behaviors of QCN.