Fine-grained queue measurement in the data plane

Xiaoqi Chen, Shir Landau Feibish, Yaron Koral, Jennifer Rexford, Ori Rottenstreich, Steven A. Monetti, Tzuu Yi Wang

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

1 Scopus citations

Abstract

Short-lived surges in traffic can cause periods of high queue utilization, leading to packet loss and delay. To diagnose and alleviate performance problems, networks need support for real-time, fine-grained queue measurement. By identifying the flows that contribute significantly to queue build-up directly in the data plane, switches can make targeted decisions to mark, drop, or reroute these flows in real time. However, collecting fine-grained queue statistics is challenging even with modern programmable switch hardware, due to limited memory and processing resources in the data plane. We present ConQuest, a compact data structure that identifies the flows making a significant contribution to the queue. ConQuest operates entirely in the data plane, while working within the hardware constraints of programmable switches. Additionally, we show how to measure queues in legacy devices through link tapping and an off-path switch running ConQuest. Simulations show that ConQuest can identify contributing flows with 90% precision on a 1 ms timescale, using less than 65 KB of memory. Experiments with our Barefoot Tofino prototype show that ConQuest-enabled active queue management reduces flow-completion time.

Original languageEnglish (US)
Title of host publicationCoNEXT 2019 - Proceedings of the 15th International Conference on Emerging Networking Experiments and Technologies
PublisherAssociation for Computing Machinery, Inc
Pages15-29
Number of pages15
ISBN (Electronic)9781450369985
DOIs
StatePublished - Dec 3 2019
Event15th ACM International Conference on Emerging Networking Experiments and Technologies, CoNEXT 2019 - Orlando, United States
Duration: Dec 9 2019Dec 12 2019

Publication series

NameCoNEXT 2019 - Proceedings of the 15th International Conference on Emerging Networking Experiments and Technologies

Conference

Conference15th ACM International Conference on Emerging Networking Experiments and Technologies, CoNEXT 2019
CountryUnited States
CityOrlando
Period12/9/1912/12/19

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications

Keywords

  • Network monitoring
  • P4
  • Queue measurement
  • SDN

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  • Cite this

    Chen, X., Feibish, S. L., Koral, Y., Rexford, J., Rottenstreich, O., Monetti, S. A., & Wang, T. Y. (2019). Fine-grained queue measurement in the data plane. In CoNEXT 2019 - Proceedings of the 15th International Conference on Emerging Networking Experiments and Technologies (pp. 15-29). (CoNEXT 2019 - Proceedings of the 15th International Conference on Emerging Networking Experiments and Technologies). Association for Computing Machinery, Inc. https://doi.org/10.1145/3359989.3365408