Impact of Different Quality of Service Mechanisms on Students' Quality of Experience in Videoconferencing Learning Environment

Year 2018, Volume: 19 Issue: 3, 24 - 37, 17.07.2018

Toni Malınovskı Vladimir Trajkovık Tatjana Vasıleva-stojanovska

https://doi.org/10.17718/tojde.444614

Abstract

Videoconferencing technology is a successful tool for expanding possibilities for collaborative and distance learning, while bridging the distance between the teacher and students, providing time and cost savings. Recently, the focus in literature and practice for quality requirements are shifting from deterministic behavior of the infrastructure in videoconferencing learning environments to students’ Quality of Experience, as subjective measure that involves human dimensions. Hence, this study evaluates the impact of different Quality of Service mechanisms utilized in the infrastructure on students’ Quality of Experience in videoconferencing learning environments. It involved 263 faculty students that participated in 42 learning sessions via videoconferencing during their academic activities, while the infrastructure was subjected to Quality of Service mechanism in the network, as well as application enhancement in the videoconferencing platform, or both. The performance counters from the technical equipment and results from the survey regarding students’ perceived experience, showed definite Quality of Service to Quality of Experience correlation. When network and application Quality of Service were considered complementary, students’ Quality of Experience was in average 18.5% higher compared to network and 15% to application Quality of Service implementations. Similarly, best technical performance was achieved when both mechanisms were consider as a whole, such as 34% decrease in average transmit delay compared to application and 62.5% to network Quality of Service mechanisms, etc. Finally, application controls had greater impact on perceived students’ Quality of Experience than the network ones, which correlated to performance behavior of the infrastructure.Videoconferencing technology is a successful tool for expanding possibilities for collaborative and distance learning, while bridging the distance between the teacher and students, providing time and cost savings. Recently, the focus in literature and practice for quality requirements are shifting from deterministic behavior of the infrastructure in videoconferencing learning environments, or quality of service (QoS), to students’ quality of experience (QoE), as subjective measure that involves human dimensions. Hence, this study evaluates the impact of different QoS mechanisms utilized in the infrastructure on students’ QoE in videoconferencing learning environments. It involved 263 faculty students that participated in 42 learning sessions via videoconferencing during their academic activities, while the infrastructure was subjected to QoS mechanism in the network (NQoS), as well as application enhancement in the videoconferencing platform (AQoS), or both. The performance counters from the technical equipment and results from the survey regarding students’ perceived QoE after each learning session, showed definite QoS/QoE correlation. Even though students’ were not aware of the technical setup during the learning sessions, the highest level of students’ QoE was achieved when NQoS and AQoS were considered complementary, rather than as a single mechanism. In addition, AQoS controls had greater impact on perceived students’ QoE than NQoS.

Keywords

Videoconferencing, learning environments, Quality of Service, Quality of Experience, Quality of Service/Quality of Experience correlation

References

• Agboma, F., & Liotta, A. (2007). Addressing user expectations in mobile content delivery. Mobile Information Systems, 3(3-4), 153-164 Aldrich, S. E., Marks, R. T., Frey, M. M., Goulde, M. A., Lewis, J. M., & Seybold, P. B. (2000). What kind of the total customer experience does your e-business deliver. Patricia Seybold Group. Borodakiy, V. Y., Samouylov, K. E., Gudkova, I. A., Markova, E. V., & Last_Name, F. (2015). Algorithm for Calculating QoS Parameters of Video Conferencing and Video on Demand Services in Wireless Next Generation Networks. Journal of ICT Standardization, 3(1), 3-28 Bouhnik, D., & Marcus, T. (2006). Interaction in distance‐ learning courses. Journal of the Association for Information Science and Technology, 57(3), 299-305 Bozkurt, A., Akgun-Ozbek, E., Yilmazel, S., Erdogdu, E., Ucar, H., Guler, E., Sezgin, S., Karadeniz, A., Sen-Ersoy, N., Goksel-Canbek, N., & Dincer, G. D. (2015). Trends in distance education research: A content analysis of journals 2009-2013. The International Review of Research in Open and Distributed Learning, 16(1) Chen, Y., Farley, T., & Ye, N. (2004). QoS requirements of network applications on the Internet. Information Knowledge Systems Management, 4(1), 55-76 Chen, Y., Wu, K., & Zhang, Q. (2015). From QoS to QoE: A tutorial on video quality assessment. IEEE Communications Surveys & Tutorials, 17(2), 1126-1165 Chodorek, R. R., Chodorek, A., Rzym, G., & Wajda, K. (2017, June). A Comparison of QoS Parameters of WebRTC Videoconference with Conference Bridge Placed in Private and Public Cloud. In Enabling Technologies: Infra 36 Egilmez, H. E., Civanlar, S., & Tekalp, A. M. (2013). An optimization framework for QoSenabled adaptive video streaming over OpenFlow networks. IEEE Transactions on Multimedia, 15(3), 710-715 Harris, D. A., & Krousgrill, C. (2008). Distance education: New technologies and new directions. Proceedings of the IEEE, 96(6), 917-930 Hossain, M. S. (2014, February). QoS in web service-based collaborative multimedia environment. In Advanced Communication Technology (ICACT), 2014 16th International Conference on (pp. 881-884). IEEE Huang, X., Chandra, A., DePaolo, C. A., & Simmons, L. L. (2016). Understanding transactional distance in web‐ based learning environments: An empirical study. British Journal of Educational Technology, 47(4), 734-747 ITU-T (2007, January). Definition of Quality of Experience (QoE). International Telecommunication Union, Liaison Statement, Ref.: TD 109rev2 (PLEN/12) Jarschel, M., Schlosser, D., Scheuring, S., & Hoßfeld, T. (2011, June). An evaluation of QoE in cloud gaming based on subjective tests. In Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2011 Fifth International Conference on (pp. 330-335). IEEE Kalliris, G., Matsiola, M., Dimoulas, C. A., & Veglis, A. (2014, July). Emotional aspects in Quality of Experience and Learning (QoE & QoL) of audiovisual content in mediated learning. In Information, Intelligence, Systems and Applications, IISA 2014, The 5th International Conference on (pp. 198-203). IEEE Karadimce, A., & Davcev, D. (2014, October). Model for collaborative and adaptive multimedia content delivery in a collaborative m-learning environment. In Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2014 International Conference on (pp. 431-434). IEEE Kilinc, C., & Andersson, K. (2014). A congestion avoidance mechanism for WebRTC interactive video sessions in LTE networks. Wireless Personal Communications, 77(4), 2417- 2443 Kim, H. J., & Choi, S. G. (2010, February). A study on a QoS/QoE correlation model for QoE evaluation on IPTV service. In Advanced Communication Technology (ICACT), 2010 The 12th International Conference on (Vol. 2, pp. 1377-1382). IEEE Kuipers, F., Kooij, R., De Vleeschauwer, D., & Brunnström, K. (2010, June). Techniques for measuring quality of experience. In International Conference on Wired/Wireless Internet Communications (pp. 216-227). Springer, Berlin, Heidelberg Laghari, A. A., He, H., Zardari, S., & Shafiq, M. (2017). Systematic Analysis of Quality of Experience (QoE) Frameworks for Multimedia Services. IJCSNS, 17(5), 121 Laghari, K. U. R., & Connelly, K. (2012). Toward total quality of experience: A QoE model in a communication ecosystem. Communications Magazine, IEEE, 50(4), 58-65 Lawson, T., Comber, C., Gage, J., & Cullum‐ Hanshaw, A. (2010). Images of the future for education? Videoconferencing: A literature review. Technology, Pedagogy and Education, 19(3), 295-314 Lee, M., & Copeland, J. A. (2009, August). An adaptive end-to-end delay assurance algorithm with diffserv architecture in IEEE 802.11 e/IEEE 802.16 hybrid mesh/relay networks. In Computer Communications and Networks, 2009. ICCCN 2009. Proceedings of 18th Internatonal Conference on (pp. 1-6). IEEE Lee, Y., Lou, J., Luo, J., & Shen, X. (2007). An efficient packet scheduling algorithm with deadline guarantees for input-queued switches. IEEE/ACM Transactions on Networking (TON), 15(1), 212-225 Li, J., Yang, L., Fu, X., Chao, F., & Qu, Y. (2017). Dynamic QoS Solution for Enterprise Networks Using TSK Fuzzy Interpolation. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017) 37 Likert, R. (1931). A technique for the measurement of attitudes. Archives of Psychology. New York: Columbia University Press Malinovski, T., Vasileva, M., Vasileva-Stojanovska, T., & Trajkovik, V. (2014). Considering high school students’ experience in asynchronous and synchronous distance learning environments: QoE prediction model. The International Review of Research in Open and Distributed Learning, 15(4) Nahrstedt, K., Xu, D., Wichadakul, D., & Li, B. (2001). QoS-aware middleware for ubiquitous and heterogeneous environments. IEEE Communications magazine, 39(11), 140-148 Neeman, H., Severini, H., Wu, D., & Kantardjieff, K. (2010). Teaching high performance computing via videoconferencing. ACM Inroads, 1(1), 67-71 Nikravesh, A., Hong, D. K., Chen, Q. A., Madhyastha, H. V., & Mao, Z. M. (2016, August). QoE Inference Without Application Control. In Internet-QoE@ SIGCOMM (pp. 19-24) Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. 3rd ed. New York: McGraw-Hill Parakh, S., & Jagannatham, A. K. (2012, July). Game theory based dynamic bit-rate adaptation for H. 264 scalable video transmission in 4G wireless systems. In Signal Processing and Communications (SPCOM), 2012 International Conference on (pp. 1-5). IEEE Pathak, K. C., Singh, S., & Patel, J. N. (2016, December). Error detection and concealment algorithm for compressed video transmission. In Humanitarian Technology Conference (R10-HTC), 2016 IEEE Region 10 (pp. 1-5). IEEE Rajani, P. K., Khaparde, A., & Ghuge, A. D. (2017, March). Implementation of Video Error Concealment Using Block Matching Algorithm. In International Conference on Information and Communication Technology for Intelligent Systems (pp. 357-364). Springer, Cham Rajkumar, R., Lee, C., Lehoczky, J., & Siewiorek, D. (1997, December). A resource allocation model for QoS management. In Real-Time Systems Symposium, 1997. Proceedings. The 18th IEEE (pp. 298-307). IEEE Richards, A., Antoniades, M., Witana, V., & Rogers, G. (1998). Mapping user level QoS from a single parameter. In Proceedings of the International Conference on Multimedia Networks and Services (MMNS '98) Romero, D. (2008). Context-aware middleware: An overview. Paradigma, 2(3), 1-11 Saxena, P. C., Jasola, S., & Sharma, R. C. (2006). Impact of VoIP and QoS on Open and Distance Learning. Turkish Online Journal of Distance Education, 7(3) Siller, M., & Woods, J. (2003, April). Improving quality of experience for multimedia services by QoS arbitration on a QoE framework. In Proc. of the 13th Packed Video Workshop 2003 Simonson, M., Smaldino, S., & Zvacek, S. M. (Eds.). (2014). Teaching and learning at a distance: Foundations of distance education. IAP Stankiewicz, R., & Jajszczyk, A. (2011). A survey of QoE assurance in converged networks. Computer Networks, 55(7), 1459-1473 Sudarsono, A., Siswanto, A., Iswanto, H., & Setiawan, Q. (2016). Traffic Analysis of Quality of Service (QoS) for Video Conferencing between Main Campus and Sub Campus in Laboratory Scale. EMITTER International Journal of Engineering Technology, 3(2) Szigeti, T., Hattingh, C., Barton, R., & Briley Jr, K. (2013). End-to-End QoS Network Design: Quality of Service for Rich-Media & Cloud Networks. Cisco Press. Usman, M., He, X., Xu, M., & Lam, K. M. (2015, May). Survey of error concealment techniques: Research directions and open issues. In Picture Coding Symposium (PCS), 2015 (pp. 233-238). IEEE