QoE inference and improvement without end-host control

Ashkan Nikravesh, Qi Alfred Chen, Scott Haseley, Xiao Zhu, Geoffrey Challen, Z. Morley Mao

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

Abstract

Network quality-of-service (QoS) does not always translate to user quality-of-experience (QoE). Consequently, knowledge of user QoE is desirable in several scenarios that have traditionally operated on QoS information. Examples include traffic management by ISPs and resource allocation by the operating system. But today these systems lack ways to measure user QoE. To help address this problem, we propose offline generation of per-app models mapping app-independent QoS metrics to app-specific QoE metrics. This enables any entity that can observe an app’s network traffic—including ISPs and access points—to infer the app’s QoE. We describe how to generate such models for many diverse apps with significantly different QoE metrics. We generate models for common user interactions of 60 popular apps. We then demonstrate the utility of these models by implementing a QoE-aware traffic management framework and evaluate it on a WiFi access point. Our approach successfully improves QoE metrics that reflect user-perceived performance. First, we demonstrate that prioritizing traffic for latency-sensitive apps can improve responsiveness and video frame rate, by 46% and 115%, respectively. Second, we show that a novel QoE-aware bandwidth allocation scheme for bandwidth-intensive apps can improve average video bitrate for multiple users by up to 23%.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 3rd ACM/IEEE Symposium on Edge Computing, SEC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages43-57
Number of pages15
ISBN (Electronic)9781538694459
DOIs
StatePublished - Dec 6 2018
Event3rd ACM/IEEE Symposium on Edge Computing, SEC 2018 - Bellevue, United States
Duration: Oct 25 2018Oct 27 2018

Publication series

NameProceedings - 2018 3rd ACM/IEEE Symposium on Edge Computing, SEC 2018

Other

Other3rd ACM/IEEE Symposium on Edge Computing, SEC 2018
CountryUnited States
CityBellevue
Period10/25/1810/27/18

Keywords

  • Application Performance
  • Measurement
  • Quality of Experience (QoE)
  • Quality of Service (QoS)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence

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