Real-Time Classification, Visualization, and QoS Control of Elephant Flows in SDN 


Vol. 42,  No. 3, pp. 612-622, Mar.  2017


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  Abstract

Long-lived flowed termed as elephant flows in data center networks have a tendency to consume a lot of bandwidth, leaving delay-sensitive short-lived flows referred to as mice flows choked behind them. This results in non-trivial delays for mice flows, eventually degrading application performance running on the network. Therefore, a datacenter network should be able to classify, detect, and visualize elephant flows as well as provide QoS guarantees in real-time. In this paper we aim to focus on: 1) a proposed framework for real-time detection and visualization of elephant flows in SDN using sFlow. This allows to examine elephant flows traversing a switch by double-clicking the switch node in the topology visualization UI; 2) an approach to guarantee QoS that is defined and administered by a SDN controller and specifications offered by OpenFlow. In the scope of this paper, we will focus on the use of rate-limiting (traffic-shaping) classification technique within an SDN network.

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  Cite this article

[IEEE Style]

A. Muhammad and W. Song, "Real-Time Classification, Visualization, and QoS Control of Elephant Flows in SDN," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 3, pp. 612-622, 2017. DOI: .

[ACM Style]

Afaq Muhammad and Wang-Cheol Song. 2017. Real-Time Classification, Visualization, and QoS Control of Elephant Flows in SDN. The Journal of Korean Institute of Communications and Information Sciences, 42, 3, (2017), 612-622. DOI: .

[KICS Style]

Afaq Muhammad and Wang-Cheol Song, "Real-Time Classification, Visualization, and QoS Control of Elephant Flows in SDN," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 3, pp. 612-622, 3. 2017.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880