Publication Details

Enabling Event-Triggered Data Plane Monitoring

KUČERA, J.; POPESCU, D.; WANG, H.; MOORE, A.; KOŘENEK, J.; ANTICHI, G. Enabling Event-Triggered Data Plane Monitoring. In SOSR 2020 - Proceedings of the 2020 Symposium on SDN Research. New York, NY: Association for Computing Machinery, 2020. p. 14-26. ISBN: 978-1-4503-7101-8.
Czech title
Událostmi řízené monitorování s využitím programovatelné datové cesty
Type
conference paper
Language
English
Authors
Kučera Jan, Ing., Ph.D. (DCSY)
POPESCU, D.
WANG, H.
Moore Andrew
Kořenek Jan, doc. Ing., Ph.D. (DCSY)
Antichi Gianni, Dr.
Keywords

Network measurements, traffic aggregates, Elastic Trie, P4

Abstract

We propose a push-based approach to network monitoring that allows the detection, within the dataplane, of traffic aggregates. Notifications from the switch to the controller are sent only if required, avoiding the transmission or processing of unnecessary data. Furthermore, the dataplane iteratively refines the responsible IP prefixes, allowing the controller to receive information with a flexible granularity. We implemented our solution, Elastic Trie, in P4 and for two different FPGA devices. We evaluated it with packet traces from an ISP backbone. Our approach can spot changes in the traffic patterns and detect (with 95% of accuracy) either hierarchical heavy hitters with less than 8KB or superspreaders with less than 300KB of memory, respectively. Additionally, it reduces controller-dataplane communication overheads by up to two orders of magnitude with respect to state-of-the-art solutions.

Published
2020
Pages
14–26
Proceedings
SOSR 2020 - Proceedings of the 2020 Symposium on SDN Research
ISBN
978-1-4503-7101-8
Publisher
Association for Computing Machinery
Place
New York, NY
DOI
EID Scopus
BibTeX
@inproceedings{BUT162080,
  author="KUČERA, J. and POPESCU, D. and WANG, H. and MOORE, A. and KOŘENEK, J. and ANTICHI, G.",
  title="Enabling Event-Triggered Data Plane Monitoring",
  booktitle="SOSR 2020 - Proceedings of the 2020 Symposium on SDN Research",
  year="2020",
  pages="14--26",
  publisher="Association for Computing Machinery",
  address="New York, NY",
  doi="10.1145/3373360.3380830",
  isbn="978-1-4503-7101-8",
  url="https://www.fit.vut.cz/research/publication/11810/"
}
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