Clairvoyant networks

Cheng Jin, Cristian Lumezanu, Zhi Li Zhang, Haifeng Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We use the term clairvoyant to refer to networks which provide on-demand visibility for any flow at any time. Traditionally, network visibility is achieved by instrumenting and passively monitoring all flows in a network. SDN networks, by design endowed with full visibility, offer another alternative to network-wide flow monitoring. Both approaches incur significant capital and operational costs to make networks clairvoyant.In this paper, we argue that we can make any existing network clairvoyant by installing one or more SDN-enabled switches and a specialized controller to support on-demand visibility. We analyze the benefits and costs of such clairvoyant networks and provide a basic design by integrating two existing mechanisms for updating paths through legacy switches with SDN, telekinesis and magnet MACs. Our evaluation on a lab testbed and through extensive simulations show that, even with a single SDN-enabled switch, operators can make any flow visible for monitoring within milliseconds, albeit at 38% average increase in path length. With as many as 2% strategically chosen legacy switches replaced with SDN switches, clairvoyant networks achieve on-demand flow visibility with negligible overhead.

Original languageEnglish (US)
Title of host publicationTMA 2019 - Proceedings of the 3rd Network Traffic Measurement and Analysis Conference
EditorsStefano Secci, Isabelle Chrisment, Marco Fiore, Lionel Tabourier, Keun-Woo Lim
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-96
Number of pages8
ISBN (Electronic)9783903176171
DOIs
StatePublished - Jun 2019
Event3rd IFIP/IEEE Network Traffic Measurement and Analysis Conference, TMA 2019 - Paris, France
Duration: Jun 19 2019Jun 21 2019

Publication series

NameTMA 2019 - Proceedings of the 3rd Network Traffic Measurement and Analysis Conference

Conference

Conference3rd IFIP/IEEE Network Traffic Measurement and Analysis Conference, TMA 2019
CountryFrance
CityParis
Period6/19/196/21/19

Bibliographical note

Funding Information:
We are grateful to TMA anonymous reviewers for their insightful comments. The research was supported in part by US DoD DTRA grant HDTRA1-14-1-0040, and NSF grants CNS 1618339, CNS 1617729, CNS 1814322 and CNS183677.

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