Change search
ReferencesLink to record
Permanent link

Direct link
Network-Based Monitoring of Quality of Experience
Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The recent years have observed a tremendous shift from the technology-centric assessment to the user-centric assessment of network services. Consequently, measurement and modelling of Quality of Experience (QoE) attracted many contributions from researchers and practitioners. Generally, QoE is assessed via active and passive measurements. While the former usually allows QoE assessment on the test traffic, the latter opens avenues for continuous QoE assessment on the real traffic generated by the users. This thesis contributes towards passive assessment of QoE.

This thesis document begins with a background on the fundamentals of network management and objective QoE assessment. It extends the discussion further to the QoE-centric monitoring and management of network, complimented by the details about QoE estimator agent developed within the Celtic project QuEEN (Quality of Experience Estimators in Network).

The discussion on findings starts with results from subjective tests to understand the relationship between waiting times and user subjective feedback over time. These results strengthen the understanding of timescales on which users react, as well as, the effect of user memory on QoE. The findings show that QoE drops significantly when the user faces recurring waiting times of 0.5 s to 4 s durations in case of video streaming and web browsing services. With recurring network disturbances within every 8 s – 16 s time intervals, the user tolerance to waiting times decreases constantly, showing the sign of user memory of recent disturbances.

Subsequently, this document introduces and evaluates a passive wavelet-based QoE monitoring method. The method detects timescales on which transient outages occur frequently. A study presents results from qualitative measurements, showing the ability of wavelet to differentiate on-fly between “Good” and “Bad” traffic streams. In sequel, a quantitative study systematically evaluates wavelet-based metrics. Subsequently, the subjective evaluation and wavelet analysis of 5 – 6 minutes long video streaming sessions on mobile networks show that wavelet-based metrics is indeed useful for passive monitoring of QoE issues.

Finally, this thesis investigates a method for passive monitoring of user reactions to degrading network performance. The method is based on the TCP termination flags. With a systematic evaluation in a test environment, the results characterise termination of data transfers in case of different user actions in the web browser.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2015. , 193 p.
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 11
Keyword [en]
Quality of Experience, Network Performance, Network measurements
National Category
URN: urn:nbn:se:bth-10495ISBN: 978-91-7295-309-3OAI: diva2:848095
Public defence
2015-09-21, J1650, Karlskrona, 15:15 (English)
Available from: 2015-08-24 Created: 2015-08-18 Last updated: 2015-09-21Bibliographically approved

Open Access in DiVA

fulltext(4396 kB)55 downloads
File information
File name FULLTEXT02.pdfFile size 4396 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Junaid, Junaid
By organisation
Department of Communication Systems

Search outside of DiVA

GoogleGoogle Scholar
Total: 114 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 298 hits
ReferencesLink to record
Permanent link

Direct link