Real-Time Monitoring and Classification of Quality of Experience (QoE) in Video Streaming over Wireless Local Area Network (WLAN)

Samuel Bassey; Imeh Umoren

Samuel Bassey
Imeh Umoren

Keywords: User Quality of Experience (uQoE), Quality of Service (QoS), AKSU, Graphical User Interface, WLAN, ML, SVM, MN

Abstract

The need for internet access is currently rising, and information regarding user Quality of Experience (uQoE) in video streaming is necessary for sound decision making by network service providers. Indeed, it is vital to compute the recording or correlation between objective Quality of Service (QoS) and subjective Quality of Experience (QoE) metrics. Basically, streaming services is a major feature that has gained more popularity on the internet and expanding online audience. Hence, it is essential for network content providers to fulfill user requirements in the provision of sufficient QoS to relevant subscribers and applications. Nevertheless, recent advances show that QoS cannot accurately characterize the users’ perception. Consequently, the perception of real-time monitoring system for Quality of Experience (QoE) monitoring of video streaming services over wireless local area network is considered. This research proposed a Machine Learning (ML) based approach using Support Vector Machine (SVM) and Neural Network (NN) to monitor QoE metrics for video traffic in a typical Wireless Local Area Network (WLAN). The machine learning algorithms were trained with the subjective dataset obtained from Akwa Ibom State University (AKSU) ICT unit for more than 60 days in real-time. The work adopts subjective experimental methodology based on dataset which represents the correlation between objective QoS parameters and subjective QoE. The experimental evaluations conducted with confusion matrix show that the system model achieves up to 90% classification accuracy for support vector machine (SVM), 89% accuracy for neural networks (NN). The transformed model was deployed in an operational system API environment with flexible Graphical User Interface (GUI) for real-time video streaming monitoring and mapping to guide the behavior of the overall networks on user experience (uQoE) and efficient management of the network resources.

References

Akbar, J., Utami, E., & Yaqin, A. (2022, December). Multi-Label Classification of Film Genres Based on Synopsis Using Support Vector Machine, Logistic Regression and Naïve Bayes Algorithms. In 2022 6th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE) (pp. 250-255). IEEE.
Amour, L., Souihi, S., Hoceini, S., & Mellouk, A. (2015). A hierarchical classification model of QoE influence factors. In Wired/Wireless Internet Communications: 13th International Conference, WWIC 2015, Malaga, Spain, May 25-27, 2015, Revised Selected Papers 13 (pp. 225-238). Springer International Publishing. https://doi.org/9071.225-238.10.1007/978-3-319-22572-2_16.
Apostolopoulos, J. G., Tan, W. T., & Wee, S. J. (2002). Video streaming: Concepts, algorithms, and systems. HP Laboratories, report HPL-2002-260, 2641-8770.
Balachandran, A., Sekar, V., Akella, A., Seshan, S., Stoica, I., & Zhang, H. (2013). Developing a predictive model of quality of experience for internet video. ACM SIGCOMM Computer Communication Review, 43(4), 339-350.
Chen, Y., Wu, K., & Zhang, Q. (2015). From QoS to QoE: A tutorial on video quality assessment. IEEE Commun. Surv. Tutorials, 17(2), 1126–1165.
Dobre, C., & Xhafa, F. (Eds.). (2016). Pervasive Computing: Next Generation Platforms for Intelligent Data Collection. In Intelligent Data-Centric Systems (pp. xvii-xix). Academic Press. https://doi.org/10.1016/b978-0-12-803663-1.09984-8.
Elkotob, M., Grandlund, D., Andersson, K., & Ahlund, C. (2010). Multimedia QoE Optimized Management Using Prediction and Statistical Learning. In 35th Annual IEEE Conference on Local Computer Networks.
Fairoz, B. (2015). Adaptive Cross-Layer Video Streaming Over Wireless LAN. International Journal of Innovative Research in Computer and Communication Engineering, 3, 1000-1007. https://doi.org/10.15680/ijircce.2015.0302042.
Isong, E., & Umoren, I. J. (2019). Path Loss Modelling of WLAN Infrastructure Using Fuzzy Logic. Conference of the International Journal of Arts & Sciences, 12(1), 195-214.
Joseph, V., & de Veciana, G. (2014, April). NOVA: QoE-driven optimization of DASH-based video delivery in networks. In IEEE INFOCOM 2014-IEEE conference on computer communications (pp. 82-90). IEEE.
Kuipers, F., Kooij, R., De Vleeschauwer, D., & Brunnström, K. (2010). Techniques for measuring quality of experience. In Wired/Wireless Internet Communications: 8th International Conference, WWIC 2010, Luleå, Sweden, June 1-3, 2010. Proceedings 8 (pp. 216-227). Springer Berlin Heidelberg.
Le Callet, P., Möller, S., & Perkis, A. (2012). Qualinet white paper on definitions of quality of experience. European network on quality of experience in multimedia systems and services (COST Action IC 1003), 3(2012).
Letaifa, A. B. (2017, June). Adaptive QoE monitoring architecture in SDN networks: Video streaming services case. In 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 1383-1388). IEEE. https://doi.org/10.1109/IWCMC.2017.7986486
Nam, H., Kim, K. H., & Schulzrinne, H. (2016, April). QoE matters more than QoS: Why people stop watching cat videos. In IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications (pp. 1-9). IEEE.
Serral-Gracià, R., Cerqueira, E., Curado, M., Yannuzzi, M., Monteiro, E., & Masip-Bruin, X. (2010, June). An overview of quality of experience measurement challenges for video applications in IP networks. In International Conference on Wired/Wireless Internet Communications (pp. 252-263). Berlin, Heidelberg: Springer Berlin Heidelberg.
Shaout, A., & Crispin, B. (2020). Streaming video classification using machine learning. Int. Arab J. Inf. Technol., 17(4A), 677-682.
Umoren, I. J., & Inyang, S. J. (2021). Methodical Performance Modelling of Mobile Broadband Networks with Soft Computing Model. International Journal of Computer Applications, 174(25), 7-21.
Umoren, I. J., & Okon, S. B. (2021). A Multidimensional Fuzzy Knowledge-based System for Optimizing Wireless Local Area Networks Performance. International Journal of Computer Applications, 975, 8887.
Umoren, I. J., Asuquo, D. E., Gilean, O., & Esang, M. (2019). Performability of Retransmission of Loss Packets in Wireless Sensor Networks. Comput. Inf. Sci., 12(2), 71-86.
Umoren, I., Asagba, P. & Owolabi, O. (2014). Handover Manageability and Performance Modeling in Mobile Communication Networks. Computing, Information Systems, Development Informatics and Allied Research Journal, 5(1), 27-42.
Umoren, I., Effiang, D., & Etuk, U. (2016). Improving Capacity of Reception Quality in Mobile Communication Networks Using BER Performance Metric. Journal of Advances in Mathematical & Computational Sciences, 3(1), 1-26.
Vapnik, V., & Izmailov, R. (2017). Knowledge transfer in SVM and neural networks. Annals of Mathematics and Artificial Intelligence, 81(1-2), 3-19.
Venkataraman, M., & Chatterjee, M. (2011). Inferring video QoE in real time. IEEE Netw. 25(1), 4–13.
Wang, Q., Dai, H. N., Wu, D., & Xiao, H. (2018). Data analysis on video streaming QoE over mobile networks. EURASIP Journal on Wireless Communications and Networking, 2018, 1-10.
Wu, D., Hou, Y. T., & Zhang, Y. Q. (2000). Transporting real-time video over the Internet: Challenges and approaches. Proceedings of the IEEE, 88(12), 1855-1877.
Wu, D., Hou, Y. T., Zhu, W., Zhang, Y. Q., & Peha, J. M. (2001). Streaming video over the Internet: approaches and directions. IEEE Transactions on circuits and systems for video technology, 11(3), 282-300. https://doi.org/10.1184/R1/6073481.v1
Zhu, X., & Girod, B. (2007, September). Video streaming over wireless networks. In 2007 15th European Signal Processing Conference (pp. 1462-1466). IEEE.