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Ending the Anomaly: Achieving Low Latency and Airtime Fairness in WiFi
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-5241-6815
Tieto Poland, Szczecin, Poland.
TekLibre, San Francisco, CA USA.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-8731-2482
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2017 (English)In: 2017 USENIX ANNUAL TECHNICAL CONFERENCE (USENIX ATC '17), USENIX Assoc , 2017, p. 139-151Chapter in book (Other academic)
Abstract [en]

With more devices connected, delays and jitter at the WiFi hop become more prevalent, and correct functioning during network congestion becomes more important. However, two important performance issues prevent modern WiFi from reaching its potential: increased latency under load caused by excessive queueing (i.e. bufferbloat) and the 802.11 performance anomaly. To remedy these issues, we present a novel two-part solution. We design a new queueing scheme that eliminates bufferbloat in the wireless setting. Leveraging this queueing scheme, we then design an airtime fairness scheduler that operates at the access point and doesn't require any changes to clients. We evaluate our solution using both a theoretical model and experiments in a testbed environment, formulating a suitable analytical model in the process. We show that our solution achieves an order of magnitude reduction in latency under load, large improvements in multi -station throughput, and nearly perfect airtime fairness for both TCP and downstream UDP traffic. Further experiments with application traffic confirm that the solution provides significant performance gains for real -world traffic. We develop a production quality implementation of our solution in the Linux kernel, the platform powering most access points outside of the managed enterprise setting. The implementation has been accepted into the mainline kernel distribution, making it available for deployment on billions of devices running Linux today.

Place, publisher, year, edition, pages
USENIX Assoc , 2017. p. 139-151
Series
2017 USENIX ANNUAL TECHNICAL CONFERENCE (USENIX ATC '17)
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-67077ISI: 000428763500011ISBN: 978-1-931971-38-6 (print)OAI: oai:DiVA.org:kau-67077DiVA, id: diva2:1198870
Available from: 2018-04-19 Created: 2018-04-19 Last updated: 2018-06-26Bibliographically approved

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Høiland-Jørgensen, TokeHurtig, PerBrunström, Anna

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Citation style
  • apa
  • harvard1
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