Web Quality of Experience Measurement: Metrics, Methods and Tools

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2021-07-02
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Authors

Date

2021

Department

Tietoliikenne- ja tietoverkkotekniikan laitos
Department of Communications and Networking

Major/Subject

Mcode

Degree programme

Language

en

Pages

135 + app. 65

Series

Aalto University publication series DOCTORAL DISSERTATIONS, 76/2021

Abstract

The web is one of the dominant applications on the Internet. Over the last three decades, the web has been evolving in terms of content types, supporting technologies, content provisioning, and access protocols. Similarly, the users' demands for fast and reliable web access have been also growing. Understanding the user browsing Quality of Experience (QoE) is of interest to content and service providers to deliver a quality service. However, the subjective nature of QoE makes it challenging to measure the web user experience on a large scale. Due to this, Quality of Service (QoS) metrics that can be measured on different layers of the web stack have been used to approximate the user experience. In this thesis, we propose a method to calculate an objective web QoE metric that better approximates the user experience. We design and implement a measurement system and tool that can be used on a large scale. We discuss the validation of the measurement system and benchmark the system performance. We present results from measurements that have been conducted to understand the web performance and QoE both from fixed-line and cellular networks. We also discuss modeling the web QoE from the QoS metrics using existing export models (e.g., ITU-T and IQX), and machine learning algorithms (e.g., SVR, CART, BOOST). This thesis contributes to the effort towards understanding, designing, and managing infrastructure to provide improved web QoE. Web users and content and service providers can use the methodology we have proposed and the tools we have designed to understand and troubleshoot possible bottlenecks for poor user experience. For instance, Internet Service Providers (ISPs) can deploy our tools on customer premises in their subscriber base and monitor their end-user web QoE. ISPs can use this for efficient capacity planning, network design, and web traffic management towards popular Content Delivery Networks (CDNs). The work on modeling web QoE shows that the expert models and machine learning-based models have comparable degree of performance accuracy. This thesis also shows that the expert models can accommodate new time-related metrics beyond the web latency metrics.

Description

Defence is held on 2.7.2021 14:00 – 18:00 Zoom https://aalto.zoom.us/j/5066362673?pwd=YTc0aDZwUlNhNW5ZMGYrRUExZ3Y4UT09

Supervising professor

Ott, Jörg, Prof., Aalto University, Department of Communications and Networking, Finland

Thesis advisor

Sarolahti, Pasi, Dr., Aalto University, Finland

Keywords

web measurement, web performance, web QoE, QoE modeling

Other note

Parts

  • [Publication 1]: Alemnew Sheferaw Asrese, Pasi Sarolahti, Magnus Boye, Jörg Ott. WePR: A Tool for Automated Web Performance Measurement. In Proceedings of Globecom workshops, Washington, DC, USA, 4–8 December 2016, pages 1–6.
    DOI: 10.1109/GLOCOMW.2016.7849082 View at publisher
  • [Publication 2]: Alemnew Sheferaw Asrese, Steffie Jacob Eravuchira, Vaibhav Bajpai, Pasi Sarolahti and Jörg Ott. Measuring Web Latency and Rendering Performance: Method, Tools & Longitudinal Dataset. IEEE Transactions on Network and Service Management, vol. 16, no. 2, 2019, pp. 535–549.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201906033369
    DOI: 10.1109/TNSM.2019.2896710 View at publisher
  • [Publication 3]: Diego Neves da Hora, Alemnew Sheferaw Asrese, Vassilis Christophides, Renata Teixeira and Dario Rossi. Narrowing the gap between QoS metrics and Web QoE using Above-the-fold metrics. In Proceedings of the 19th International Conference on Passive Active Measurement Conference, Berlin, Germany, 26–27 March 2018, pages 31–43.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201804042059
    DOI: 10.1007/978-3-319-76481-8 View at publisher
  • [Publication 4]: Alemnew Sheferaw Asrese, Ermias Andargie Walelgne, Vaibhav Bajpai, Andra Lutu, Özgü Alay and Jörg Ott. Measuring Web Quality of Experience in Cellular Networks. In Proceedings of the 20th International Conference on Passive Active Measurement Conference, Puerto Varas, Chile, 27–29 March 2019, pages 18–33.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201905062716
    DOI: 10.1007/978-3-030-15986-3_2 View at publisher

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https://urn.fi/URN:ISBN:978-952-64-0401-1

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[diss] Sähkötekniikan korkeakoulu / ELEC