FSQCN: Fast and simple quantized congestion notification in data center ethernet

Ruan, Chang; Wang, Jianxin; Jiang, Wanchun; Huang, Jiawei; Min, Geyong; Pan, Yi

doi:10.1016/j.jnca.2017.01.025

Cited by 14 publications

(9 citation statements)

References 18 publications

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“…In addition, Y. Zhang et al [17] investigate the unfairness problem between the flows controlled by QCN and analyze the stability of QCN using the Lyapunov method. C. Ruan et al [18] improve the stability of QCN and design FSQCN. They prove that FSQCN can enter the slide mode motion using the phase plane method.…”

Section: Related Workmentioning

confidence: 99%

Nonlinear Control Analysis of Quantized Congestion Notification in Data Center Networks

Ruan

Zhang

et al. 2020

IEEE Access

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In data center networks, quantized congestion notification (QCN) has been ratified as the standard layer 2 congestion control mechanism. Since the congestion control algorithm of QCN conducts nonlinear switching between the rate increasing and decreasing stages, it is very difficult to analyze QCN theoretically. Previous works derive the stability condition of QCN using tools from linear control theory. However, the tools cannot reveal the reason why the queue at a congested link oscillates persistently when QCN is enabled. In this paper, we use the describing function method from nonlinear control theory to analyze queue oscillation. We show that unsuitable network configurations like more flows, a higher link capacity and a larger link delay will cause more severe oscillation of the queue. In particular, the impacts of the QCN parameters, such as the sampling probability and the constant in the active increase phase in QCN, on the oscillation magnitude of the queue are also analyzed. The simulation results validate the conclusion from our theoretical analysis well. INDEX TERMS quantized congestion notification, data center networks, nonlinear analysis, describing function, limit circle.

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Section: Related Workmentioning

confidence: 99%

Nonlinear Control Analysis of Quantized Congestion Notification in Data Center Networks

Ruan

Zhang

et al. 2020

IEEE Access

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“…The TCP Incast problem is also solved at other layers [26,27]. PLATO [28] adopts a packet labeling scheme to prevent labeled packets from being dropped.…”

Section: Related Workmentioning

confidence: 99%

Gentle Slow Start to Alleviate TCP Incast in Data Center Networks

2019

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Modern data center networks typically adopt symmetric topologies, such as leaf-spine and fat-tree. When a large number of transmission control protocol (TCP) flows in data center networks send data to the same receiver, the congestion collapse, called TCP Incast, frequently happens because of the huge packet losses and Time-Out. To address the TCP Incast issue, we firstly demonstrate that adjusting the increasing speed of the congestion window during the slow start phase is crucially important. Then we propose the Gentle Slow Start (GSS) algorithm, which adjusts the congestion window according to real-time congestion state in a gentle manner and smoothly switches from slow start to congestion avoidance phase. Furthermore, we present the implementation and design of Gentle Slow Start and also integrate it into the state-of-the-art data center transport protocols. The test results show that GSS effectively decreases the Incast probability and increases the network goodput by average 8x.

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“…Condition (2) guarantees that a VM can only be migrated to one PM. Conditions (3) and (4) guarantees that all the CPU utilizations of all PMs cannot exceed their overloaded thresholds after the VM migrations.…”

Section: Content-based Vm Selecting and Placement Problem With Fixed mentioning

confidence: 99%

“…VM migration is indispensable for this process. Current CDCs are usually with sophisticated network [4], which makes the smooth transmission of VMs a hard task in VM migration.…”

Section: Introductionmentioning

confidence: 99%

An optimization of virtual machine selection and placement by using memory content similarity for server consolidation in cloud

Wang

et al. 2018

Future Generation Computer Systems

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FSQCN: Fast and simple quantized congestion notification in data center ethernet

Cited by 14 publications

References 18 publications

Nonlinear Control Analysis of Quantized Congestion Notification in Data Center Networks

Nonlinear Control Analysis of Quantized Congestion Notification in Data Center Networks

Gentle Slow Start to Alleviate TCP Incast in Data Center Networks

An optimization of virtual machine selection and placement by using memory content similarity for server consolidation in cloud

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