A Framework for Classification and Visualization of Elephant Flows in SDN-Based Networks

Muhammad Afaq, Shafqat Ur Rehman, Wang Cheol Song*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

14 Scopus citations

Abstract

Long-lived flows termed as elephant flows normally transport large volumes of data in enterprise networks, particularly data center networks. These flows tend to consume a lot of bandwidth and fill up network buffers end-to-end. This causes non-trivial delays for short-lived flows referred to as mice flows which are usually delay-sensitive. Therefore, identifying and handling elephant flows is important for QoS provisioning. In this paper, we present a framework for real-time detection and visualization of elephant flows in SDN-based networks using sFlow. Using our proposed framework, network operators can examine elephant flows through each switch by double-clicking the switch node in the topology visualization UI. Although not in the scope of this paper, but in order to meet traffic engineering requirements, the elephant flows detected and visualized by our proposed framework can be reprioritized, re-scheduled, or routed via dedicated high speed links. We evaluate the proposed framework by using a physical SDN testbed as well as a Mininet-based testbed.

Original languageEnglish
Pages (from-to)672-681
Number of pages10
JournalProcedia Computer Science
Volume65
DOIs
StatePublished - 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 The Authors.

Keywords

  • Avior
  • Floodlight controller
  • Mininet
  • OpenFlow
  • SDN
  • elephant flows detection
  • sFlow
  • visualization

ASJC Scopus subject areas

  • General Computer Science

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