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Modeling of quality of experience for web-based unified communications with perceptual dimensions

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Abstract

The integration of heterogeneous communication services and devices has led to paradigm shift towards unified communications, which promise to improve productivity and lifestyle by creating the digitally connected life and work environment. The increasing use of various devices for accessing web-based rather than native unified communication is expected to initiate the rise of interest among various parties included in the service delivery chain in comprehension of the influence of different perceptual dimensions on user’s quality of experience. This paper presents a multidimensional analysis of quality of experience for web-based unified communication. The contribution of the paper is twofold. First, the multidimensional model, which quantifies the mutual relations between quality of experience and numerous perceivable dimensions of the experience that determine its quality is proposed. Second, the importance of distinct dimensions in terms of overall user perceived quality of experience for web-based unified communication is identified.

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References

  1. Reimer, K., Taing, S.: Unified communications. Bus. Inf. Syst. Eng. 1, 326–330 (2009)

    Article  Google Scholar 

  2. Bolton, A., Murray, M., Flucker, J.: Transforming the Workplace: unified communications & collaboration usage patterns in a large automotive manufacturer. In: Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS 2017), pp. 5470–5479 (2017)

  3. Frost & Sullivan: High-tech Companies: How to Win the Innovation race with Advanced Communication and Collaboration Tools. https://ww2.frost.com/frost-perspectives/high-tech-companies-how-to-win-the-innovation-race-with-advanced-communication-and-collaboration-tools/ (2019). Accessed on 26 April 2020

  4. Research & Market: Global unified communication and collaboration market 2016–2020. https://www.researchandmarkets.com/research/9fm6ll/global_ unified (2016). Accessed on 26 April 2020

  5. PRNewswire: WebRTC Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2018–2026. https://www.prnewswire.com/news-releases/webrtc-market—global-industry-analysis-size-share-growth-trends-and-forecast-2018—2026-300866723.html (2019) Accessed on 26 April 2020

  6. Fosser, E., Nedberg, L.O.D.: Quality of Experience of WebRTC Based Video Communication. Master’s thesis, Norwegian University of Science and Technology, Trondheim, Norway (2016)

  7. Laghari, K.U.R., Connelly, K.: Toward total quality of experience: a QoE Modeling in a communication ecosystem. IEEE Commun Mag 50, 56–58 (2012)

    Google Scholar 

  8. Baraković Husić, J., et al.: Quality of experience for unified communications: a survey. Int. J. Netw. Manag. (2019). https://doi.org/10.1002/nem.2083

    Article  Google Scholar 

  9. Paiano, R., Caione, A., Guido, A.L., Mattella, A., Pandurino, A.: Web application editor: a user-experience design framework for knowledge-intensive organizations. J. Web Eng. 15, 412–432 (2016)

    Google Scholar 

  10. Brunnstrom, K. et al.: Qualinet white paper on definitions of quality of experience. http://www.qualinet.eu/images/stories/QoE_whitepaper_v1.2.pdf (2013) Accessed 15 April 2020

  11. Baraković, S., Skorin-Kapov, L.: Survey and challenges of QoE management issues in wireless networks. J. Comput. Netw. Commun. 2013, 165146 (2013). https://doi.org/10.1155/2013/165146

    Article  Google Scholar 

  12. Wei, X., Zhou, L.: Multimedia QoE Evaluation. Springer, Cham (2019)

    Book  Google Scholar 

  13. Baraković, S., Skorin-Kapov, L.: Multidimensional Modeling of quality of experience for mobile web browsing. Comput. Hum. Behav. 50, 314–332 (2015)

    Article  Google Scholar 

  14. Tsolkas, D., Liotou, E., Passas, N., Merakos, L.: A survey on parametric QoE estimation for popular services. J. Netw. Comput. Appl. 77, 1–17 (2017)

    Article  Google Scholar 

  15. Bouraqia, K., et al.: Quality of experience for streaming services: measurements, challenges and insights. IEEE Access 8, 13341–13361 (2020)

    Article  Google Scholar 

  16. Thakolsri, S., Khan, S., Steinbach, E., Kellerer, W.: QoE-driven cross-layer optimization for high speed downlink packet access. J. Commun. 4, 669–680 (2009)

    Article  Google Scholar 

  17. ITU-T: Recommendation G.107. The E-model: a computational model for use in transmission planning (2014)

  18. ITU-T: Recommendation G.108. Application of the E-model: A planning guide (1999)

  19. Cole, R.G., Rosenbluth, J.R.: Voice over IP performance monitoring. ACM SIGCOMM Comput. Commun. Rev. 31, 9–24 (2001)

    Article  Google Scholar 

  20. Khan, A., Sun, L., Jammeh, E., Ifeachor, E.: Quality of experience driven adaptation scheme for video applications over wireless networks. IET Commun. 4, 1337–1347 (2010)

    Article  Google Scholar 

  21. Khan, A., Sun, L., Ifeachor, E.: Content clustering-based video quality prediction model for MPEG video streaming networks. J. Multimed. 4, 228–239 (2009)

    Article  Google Scholar 

  22. Hoβfeld, T., Schatz, R., Biersack, E., Plissonneau, L.: Internet video delivery in YouTube: from traffic measurements to quality of experience. In: Biersack, E., Callegari, C., Matijasevic, M. (eds.) Data Traffic Monitoring and Analysis, LNCS 7754, pp. 264–301. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  23. Hoβfeld, T., Seufert, M. Sieber, C., Zinner, T.: Assessing effect sizes of influence factors toward a QoE model for HTTP adaptive streaming. In: Proceedings of the 6th International Workshop on Quality of Multimedia Experience (QoMEX 2014). (2014)

  24. Seufert, M., Egger, S., Slanina, M., Zinner, T., Hoβfeld, T., Tran-Gia, P.: A survey on quality of experience of HTTP adaptive streaming. IEEE Commun. Surv. Tutor. 17, 469–492 (2017)

    Article  Google Scholar 

  25. Osmanović, I., Baraković Husić, J., Baraković, S.: Impact of media-related SIFs on QoE for H.265/HEVC video streaming. J. Commun. Softw. Syst. 14, 157–170 (2018)

    Google Scholar 

  26. Begluk, T., Baraković Husić, J., Baraković, S.: Machine learning-based QoE prediction for video streaming over LTE network. In: Proceedings of the 17th International Symposium INFOTEH-JAHORINA. (2018)

  27. ITU-T: Recommendation G.1070. Opinion model for video-telephony applications (2012)

  28. ITU-T: Recommendation G.1030. Estimating end-to-end performance in IP networks for data applications (2014)

  29. Chen, C., Chu, C., Yeh, S., Chu, H., Huang, P.: Measuring the perceptual quality of Skype sources. In: Proceedings of the Workshop on Measurements Up and Down the Stack (W-MUST’12). (2012)

  30. Chen, K.T., Huang, S. Y., Huang, P., Lei, C. L.: Quantifying Skype user satisfaction. In: Proceedings of ACM SIGCOMM 2006 Conference. (2006)

  31. Chen, S., Chu, C.Y., Yeh, S.L., Hua, H., Huang, P.: Modeling the QoE of rate changes in Skype/SILK VoIP calls. IEEE/ACM Trans. Netw. 22, 1781–1793 (2014)

    Article  Google Scholar 

  32. Karn, N.K., Zhang, H., Jiang, F., et al.: Measuring bandwidth and buffer occupancy to improve the QoE of HTTP adaptive streaming. Signal Image Video Process 13, 1367–1375 (2019)

    Article  Google Scholar 

  33. Baraković Husić, J., Alagić, E., Baraković, S., Mrkaja, M.: The influence of task complexity and duration when testing QoE in WebRTC. In: Proceedings of the 18th International Symposium INFOTEH-JAHORINA. (2019)

  34. Tsiaras, C., Rösch, M., Stiller, B.: VoIP-based calibration of the DQX model. In: Proceedings of IFIP Networking. (2015)

  35. Yan, S., Guo, Y., Chen, Y., Xie, F., Yu, C., Liu, Y.: Enabling QoE learning and prediction of WebRTC video communication in WiFi networks. In: Proceedings of the ICC 2017. (2017)

  36. Vučić, D., Skorin-Kapov, L., Sužnjević, M.: The impact of bandwidth limitations and video resolution size on QoE for WebRTC-based mobile multi-party video conferencing. In: Proceedings of PQS 2016. (2016)

  37. Baraković Husić, J., Baraković, S., Veispahić, A.: What factors influence the quality of experience for WebRTC video calls? In: Proceedings of the 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). (2017)

  38. Fiedler, M., Hoβfeld, T., Tran-Gia, P.: A generic quantitative relationship between quality of experience and quality of service. IEEE Netw. 24, 36–41 (2010)

    Article  Google Scholar 

  39. Nikravesh, A., Hong, D. K., Chen, Q. A., Madhyastha, H. V., Mao, M.: QoE inference without application control. In: Proceedings of Internet-QoE’16. (2016)

  40. Mustafa, S., Hameed, A.: Perceptual quality assessment of video using machine learning algorithm. Signal Image Video Process. 13, 1495–1502 (2019)

    Article  Google Scholar 

  41. Hoßfeld, T., Atzori, L., Heegaard, P.E., Skorin-Kapov, L., Varela, M.: The interplay between QoE, user bahavior and system blocking in QoE management. In: Proceedings of the 22nd Conference on Innovation in Clouds, Internet and Networking and Workshops (ICIN). (2019)

  42. Baraković, S., Skorin-Kapov, L.: Survey of research on quality of experience Modeling for web browsing. Qual. User Exp. 2, 6 (2017)

    Article  Google Scholar 

  43. Varela, M., Skorin-Kapov, L., Mäki, T., Hoβfeld, T. QoE in the web: a dance of design and performance. In: Proceedings of the 7th International Workshop on Quality of Multimedia Experience (QoMEX 2015). (2015)

  44. ITU-T: Recommendation P.800.1. Mean opinion score (MOS) terminology (2006)

  45. Lewis, J.R.: IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. http://drjim.0catch.com/usabqtr.pdf (1993). Accessed 26 April 2020

  46. Lee, S., Koubek, R.J.: Understanding user preferences based on usability and aesthetics before and after actual use. Interact. Comput. 22, 530–543 (2010)

    Article  Google Scholar 

  47. Likert, R.: A technique for the measurement of attitudes. Arch. Psychol. 22, 1–55 (1932)

    Google Scholar 

  48. Baraković, S.: The psychometric evaluation of the survey. https://drive.google.com/open?id=1FRMq2LSrVFDRUYCsdif2bQTrMc3RLvYx (2020). Accessed 6 Oct 2020

  49. UCLA Statistical Consulting Group: Choosing the correct statistical test in SAS, STATA, SPSS and R. https://stats.idre.ucla.edu/other/mult-pkg/whatstat/ Accessed 26 April 2020

  50. Brace, N., Kemp, R., Snelgar, R.: SPSS for psychologists. Palgrave MacMillan, Hampshire (2016)

    Book  Google Scholar 

  51. Sweet, S.A., Grace-Martin, K.A.: Data analysis with SPSS: A first course in applied statistics. Pearson, New York (2012)

    Google Scholar 

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Correspondence to Ondrej Krejcar.

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Baraković Husić, J., Baraković, S., Krejcar, O. et al. Modeling of quality of experience for web-based unified communications with perceptual dimensions. SIViP 15, 977–985 (2021). https://doi.org/10.1007/s11760-020-01822-0

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