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Background and Literature Survey

  • Ying Wang
  • Wen’an Zhou
  • Ping Zhang
Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

In this chapter, an overview of QoE is given and the current state-of-the-art background for QoE is described. Specifically, the definitions of QoE from different aspects and QoE influencing factors are first presented. Then, QoE assessment methods and QoE models are introduced in the following section. In addition, QoE management and control issues are also investigated. Last but not least the challenges of QoE in 5G wireless networks are discussed.

Keywords

Packet Loss Mean Opinion Score Mobile Cloud Computing Multiple Description Code European Telecommunication Standard Institute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Quality of experience. http://www.wikepedia.org.
  2. 2.
    ITU Telecommunication Standardization Sector and OF ITU. “Definition of quality of experience (QoE), liaison statement”. ITU-T Recommendation P.10/G.100, Amd 1, 2007.Google Scholar
  3. 3.
    European Telecommunication Standards Institute TC HF (Human Factors). “Quality of Experience (QoE) requirements for real-time communication services”. Technical report, European Telecommunication Standards Institute, 2010.Google Scholar
  4. 4.
    P. Le Callet, S. Moller, and A. Perkis. “Qualinet white paper on definitions of quality of experience (QoE)”, 2013.Google Scholar
  5. 5.
    K. Kilkki. “Quality of Experience in Communications Ecosystem”. J. UCS, 14(5):615–624, 2008.Google Scholar
  6. 6.
    K. U. R. Laghari and K. Connelly. “Toward total quality of experience: A QoE model in a communication ecosystem”. Communications Magazine, IEEE, 50(4):58–65, 2012.Google Scholar
  7. 7.
    S. Jumisko-Pyykkö, V.K. Malamal Vadakital, and M.M. Hannuksela. “Acceptance threshold: A bidimensional research method for user-oriented quality evaluation studies”. International Journal of Digital Multimedia Broadcasting, 2008.Google Scholar
  8. 8.
    H. Rifai, S. Mohammed, and A. Mellouk. “A brief synthesis of QoS-QoE methodologies”. In Programming and Systems (ISPS), 2011 10th International Symposium on, pages 32–38. IEEE, 2011.Google Scholar
  9. 9.
    S. Möller, A. Raake, M. Wältermann, and N. Côte. “Towards a universal scale for perceptual value”. In Quality of Multimedia Experience (QoMEX), 2010 Second International Workshop on, pages 142–146. IEEE, 2010.Google Scholar
  10. 10.
    T. Hoßfeld, S. Biedermann, R. Schatz, A. Platzer, S. Egger, and M. Fiedler. “The memory effect and its implications on Web QoE modeling”. In Proceedings of the 23rd International Teletraffic Congress, pages 103–110. International Teletraffic Congress, 2011.Google Scholar
  11. 11.
    S. Ickin, K. Wac, M. Fiedler, L. Janowski, et al. “Factors influencing quality of experience of commonly used mobile applications”. Communications Magazine, IEEE, 50(4):48–56, 2012.Google Scholar
  12. 12.
    S. Baraković, J. Baraković, and H. Bajrić. “Qoe dimensions and QoE measurement of NGN services”. In in Proc. Telecommunications Forum, 2010.Google Scholar
  13. 13.
    L. Skorin-Kapov and M. Varela. “A multi-dimensional view of QoE: the ARCU model”. In in Proc. International Convention MIPRO, pages 662–666. IEEE, 2012.Google Scholar
  14. 14.
    W. Song, D. Tjondronegoro, and M. Docherty. “Understanding user experience of mobile video: framework, measurement, and optimization”. INTECH Open Access Publisher, 2012.Google Scholar
  15. 15.
    ITUT Rec. “P. 800.1, mean opinion score (mos) terminology”. International Telecommunication Union, Geneva, 2006.Google Scholar
  16. 16.
    I. Rec. “Bt. 500-11, methodology for the subjective assessment of the quality of television pictures”. International Telecommunication Union, 2002.Google Scholar
  17. 17.
    W. Cherif, A. Ksentini, D. Négru, and M. Sidibé. “A_PSQA: Efficient real-time video streaming QoE tool in a future media internet context”. In Proceedings of 2011 IEEE International Conference on Multimedia and Expo (ICME), pages 1–6. IEEE, 2011.Google Scholar
  18. 18.
    Fernando Kuipers, Robert Kooij, Danny De Vleeschauwer, and Kjell Brunnström. “A Techniques for measuring quality of experience”. Springer, 2010.Google Scholar
  19. 19.
    G. Rubino. “The PSQA project”. INRIA Rennes, http://www.irisa.fr/armor/lesmembres/Rubino/myPages/psqa.html, 2010.
  20. 20.
    M. Ghareeb and C. Viho. “A multiple description coding approach for overlay multipath video streaming based on QoE evaluations”. In Proceedings of International Conference on Multimedia Information Networking and Security (MINES), pages 39–43. IEEE, 2010.Google Scholar
  21. 21.
    M. Ghareeb and C. Viho. “Hybrid qoe assessment is well-suited for multiple description coding video streaming in overlay networks”. In Proceedings of 2010 Eighth AnnualCommunicati on Networks and Services Research Conference (CNSR), pages 327–333. IEEE, 2010.Google Scholar
  22. 22.
    K. Piamrat, A. Ksentini, J. Bonnin, and C. Viho. “Q-DRAM: QoE-based dynamic rate adaptation mechanism for multicast in wireless networks”. In Proceedings of IEEE Global Telecommunications Conference, pages 1–6. IEEE, 2009.Google Scholar
  23. 23.
    X. Sun, K. Piamrat, and C. Viho. “QoE-based dynamic resource allocation for multimedia traffic in IEEE 802.11 wireless networks”. In Proceedings of 2011 IEEE International Conference on Multimedia and Expo (ICME), pages 1–6. IEEE, 2011.Google Scholar
  24. 24.
    K. Piamrat, C. Viho, J. Bonnin, and A. Ksentini. “Quality of experience measurements for video streaming over wireless networks”. In Proceedings of 2009 Sixth International Conference on Information Technology: New Generations, pages 1184–1189. IEEE, 2009.Google Scholar
  25. 25.
    K. Piamrat, K. D. Singh, A. Ksentini, C. Viho, et al. “QoE-aware scheduling for video-streaming in high speed downlink packet access”. In Proceedings of 2010 IEEE Wireless Communications and Networking Conference (WCNC), pages 1–6. IEEE, 2010.Google Scholar
  26. 26.
    P. Reichl, B. Tuffin, and R. Schatz. “Economics of logarithmic quality-of-experience in communication networks”. In Proceedings of 2010 9th Conference on Telecommunications Internet and Media Techno Economics (CTTE), pages 1–8. IEEE, 2010.Google Scholar
  27. 27.
    P. Reichl, S. Egger, R. Schatz, and A. D’Alconzo. “The logarithmic nature of QoE and the role of the Weber–Fechner law in QoE assessment”. In Proceedings of IEEE International Conference on Communications (ICC), pages 1–5. IEEE, 2010.Google Scholar
  28. 28.
    S. Khan, S. Duhovnikov, E. Steinbach, and W. Kellerer. “MOS-based multiuser multiapplication cross-layer optimization for mobile multimedia communication”. Advances in Multimedia, 2007(1):1–11, 2007.Google Scholar
  29. 29.
    T. Hosfeld, S. Biedermann, R. Schatz, A. Platzer, S. Egger, and M. Fiedler. “The memory effect and its implications on Web QoE modeling”. In Proceedings of 2011 23rd International Teletraffic Congress (ITC), pages 103–110, 2011.Google Scholar
  30. 30.
    V. Menkovski, A. Oredope, A. Liotta, and A. C. Sánchez. “Predicting quality of experience in multimedia streaming”. In in Proc. the 7th International Conference on Advances in Mobile Computing and Multimedia, pages 52–59. ACM, 2009.Google Scholar
  31. 31.
    P. Reichl, S. Egger, R. Schatz, and A. D’Alconzo. “The logarithmic nature of QoE and the role of the Weber–Fechner Law in QoE assessment”. In Proceedings of 2010 IEEE International Conference on Communications (ICC), pages 1–5. IEEE, 2010.Google Scholar
  32. 32.
    M. Fiedler, T. Hossfeld, and P. Tran-Gia. “A generic quantitative relationship between quality of experience and quality of service”. IEEE Network, 24(2):36–41, 2010.Google Scholar
  33. 33.
    Kandaraj Piamrat, Adlen Ksentini, César Viho, and Jean-Marie Bonnin. “AqoE-aware admission control for multimedia applications in ieee 802.11 wireless networks”. In Vehicular Technology Conference, 2008. VTC 2008-Fall. IEEE 68th, pages 1–5. IEEE, 2008.Google Scholar
  34. 34.
    S. Latré, P. Simoens, B. De Vleeschauwer, et al. “An autonomic architecture for optimizing QoE in multimedia access networks”. Computer Networks, 53(10):1587–1602, 2009.Google Scholar
  35. 35.
    N. Amram, B. Fu, G. Kunzmann, T. Melia, D. Munaretto, S. Randriamasy, B. Sayadi, J. Widmer, and M. Zorzi. “QoE-based transport optimization for video delivery over next generation cellular networks”. In in Proc. IEEE Symposium on Computers and Communications (ISCC), pages 19–24. IEEE, 2011.Google Scholar
  36. 36.
    S. Thakolsri, W. Kellerer, and E. Steinbach. “QoE-based cross-layer optimization of wireless video with unperceivable temporal video quality fluctuation”. In in Proc. IEEE International Conference on Communications (ICC), pages 1–6. IEEE, 2011.Google Scholar
  37. 37.
    W. Ying, M. Sachula, C. Yongce, S. Ruijin, Xinshui W., and Kai S. “Multi-leader multi-follower stackelberg game based dynamic resource allocation for mobile cloud computing environment”. Wireless Personal Communication, to appear.Google Scholar
  38. 38.
    Hao Zhu, Yang Cao, Wei Wang, Boxi Liu, and Tao Jiang. “Qoe-aware resource allocation for adaptive device-to-device video streaming”. Network, IEEE, 29(6):6–12, 2015.Google Scholar
  39. 39.
    G. Fettweis and S. Alamouti. “5G: Personal mobile internet beyond what cellular did to telephony”. IEEE Communications Magazine, 52(2):140–145, 2014.Google Scholar
  40. 40.
    B. Bangerter, S. Talwar, R. Arefi, and K. Stewart. “Networks and devices for the 5G era”. IEEE Communications Magazine, 52(2):90–96, 2014.Google Scholar
  41. 41.
    W. Hummer, S. Schulte, P. Hoenisch, and S. Dustdar. “Context-Aware Data Prefetching in Mobile Service Environments”. In Proc. IEEE Fourth International Conference on Big Data and Cloud Computing (BdCloud), pages 214–221, 2014.Google Scholar

Copyright information

© The Author(s) 2017

Authors and Affiliations

  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Institute of Network TechnologyBeijing University of Posts and TelecommunicationsBeijingChina

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