Skip to main content

QoE Assessment of HTTP Adaptive Video Streaming

  • Conference paper
  • First Online:

Abstract

Quality of Experience (QoE) is a crucial characteristic of any multimedia service and must be accounted for during the service development and planning stages. Nonetheless, given its subjective nature, it is extremely difficult to use analytical methods to estimate the average Mean Opinion Score (MOS).

Traditional progressive multimedia streaming is a well researched topic with respect to QoE, however, modern streaming services relying on advanced adaptive video streaming technologies, with specific characteristics, have yet to have an all-encompassing method for QoE estimation, as research work tend to focus on only one, or a small subset, of the technology’s aspects, such as the impact of buffering events, bit-rate change frequency, or initial playout delay.

This paper proposes a model for determining the QoE estimate of a playback session of HTTP adaptive video streaming, encompassing its complete range of characteristics. Several key-metrics are extracted throughout the playback session, and then analyzed by an analytical method able to predict the consumers’ QoE. A subjective QoE survey is conducted according to industry’s best practices and recommendations in order to validate the proposed models. The obtained results show that both subjective and objective estimations produce similar results, hence validating the proposed model.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Li, D., Cai, M.: A video quality-estimation model for streaming media services based on human visual system. In: International Conference on Computational Intelligence and Software Engineering 2009, CiSE 2009, pp. 1–4, Dec 2009

    Google Scholar 

  2. Lui, G., Gallagher, T., Li, B., Dempster, A.G., Rizos, C.: Differences in RSSI readings made by different Wi-Fi chipsets: a limitation of WLAN localization. In: 2011 International Conference on Localization and GNSS, ICL-GNSS 2011, pp. 53–57 (2011)

    Google Scholar 

  3. Moorthy, A.K., Choi, L.K., Bovik, A.C., de Veciana, G.: Video quality assessment on mobile devices: subjective, behavioral and objective studies. IEEE J. Sel. Top. Sig. Process. 6(6), 652–671 (2012)

    Article  Google Scholar 

  4. Germany OPTICOM GmbH. Pevq - advanced perceptual evalutoin of video quality (2005). http://www.pevq.com/. Accessed 4 June 2014

  5. Sakamoto, K., Aoyama, S., Asahara, S., Yamashita, K., Okada, A.: Evaluation of viewing distance vs. tv size on visual fatigue in a home viewing environment. In: Digest of Technical Papers International Conference on Consumer Electronics, ICCE 2009, pp. 1–2, Jan 2009

    Google Scholar 

  6. ur Rehman Laghari, K., Issa, O., Speranza, F., Falk, T.H.: Quality-of-experience perception for video streaming services: preliminary subjective and objective results. In: 2012 Asia-Pacific Signal Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 1–9, Dec 2012

    Google Scholar 

Download references

Acknowledgement

This work was supported by the QREN Initiative, through UE/ FEDER, COMPETE financing, in the Project PANORAMA II.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Susana Sargento .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Salvador, A., Nogueira, J., Sargento, S. (2015). QoE Assessment of HTTP Adaptive Video Streaming. In: Mumtaz, S., Rodriguez, J., Katz, M., Wang, C., Nascimento, A. (eds) Wireless Internet. WICON 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-319-18802-7_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-18802-7_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18801-0

  • Online ISBN: 978-3-319-18802-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics