{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:51:51Z","timestamp":1760233911568,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T00:00:00Z","timestamp":1614729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["272304"],"award-info":[{"award-number":["272304"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Video conferencing services based on web real-time communication (WebRTC) protocol are growing in popularity among Internet users as multi-platform solutions enabling interactive communication from anywhere, especially during this pandemic era. Meanwhile, Internet service providers (ISPs) have deployed fiber links and customer premises equipment that operate according to recent 802.11ac\/ax standards and promise users the ability to establish uninterrupted video conferencing calls with ultra-high-definition video and audio quality. However, the best-effort nature of 802.11 networks and the high variability of wireless medium conditions hinder users experiencing uninterrupted high-quality video conferencing. This paper presents a novel approach to estimate the perceived quality of service (PQoS) of video conferencing using only 802.11-specific network performance parameters collected from Wi-Fi access points (APs) on customer premises. This study produced datasets comprising 802.11-specific network performance parameters collected from off-the-shelf Wi-Fi APs operating at 802.11g\/n\/ac\/ax standards on both 2.4 and 5 GHz frequency bands to train machine learning algorithms. In this way, we achieved classification accuracies of 92\u201398% in estimating the level of PQoS of video conferencing services on various Wi-Fi networks. To efficiently troubleshoot wireless issues, we further analyzed the machine learning model to correlate features in the model with the root cause of quality degradation. Thus, ISPs can utilize the approach presented in this study to provide predictable and measurable wireless quality by implementing a non-intrusive quality monitoring approach in the form of edge computing that preserves customers\u2019 privacy while reducing the operational costs of monitoring and data analytics.<\/jats:p>","DOI":"10.3390\/fi13030063","type":"journal-article","created":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T20:33:57Z","timestamp":1614803637000},"page":"63","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Estimating PQoS of Video Conferencing on Wi-Fi Networks Using Machine Learning"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4644-7054","authenticated-orcid":false,"given":"Maghsoud","family":"Morshedi","sequence":"first","affiliation":[{"name":"EyeNetworks AS, 0680 Oslo, Norway"},{"name":"Department of Technology Systems, University of Oslo, 2007 Kjeller, Norway"}]},{"given":"Josef","family":"Noll","sequence":"additional","affiliation":[{"name":"Department of Technology Systems, University of Oslo, 2007 Kjeller, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,3]]},"reference":[{"key":"ref_1","unstructured":"BigMarketResearch (2021, January 19). Global Web Real-Time Communication (WebRTC) Market. Available online: https:\/\/www.bigmarketresearch.com\/report\/4026536\/global-web-real-time-communication-webrtc-market."},{"key":"ref_2","unstructured":"ASSIA (2021, January 19). Deliver Better Wi-Fi to Residential Subscriber, ASSIA. Available online: https:\/\/www.assia-inc.com\/products\/cloudcheck\/."},{"key":"ref_3","unstructured":"Hora, D.D., van Doorselaer, K., van Oost, K., and Teixeira, R. (2018, January 16\u201319). Predicting the effect of home Wi-Fi quality on QoE. Proceedings of the INFOCOM 2018 IEEE International Conference on Computer Communications, Honolulu, HI, USA."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Chakraborty, A., Sanadhya, S., Das, S.R., Kim, D., and Kim, K.H. (2016, January 12\u201315). ExBox: Experience Management Middlebox for Wireless Networks. Proceedings of the 12th International on Conference on Emerging Networking Experiments and Technologies, New York, NY, USA.","DOI":"10.1145\/2999572.2999597"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Morshedi, M. (2020, January 20\u201323). Preparing Wi-Fi Networks for Novel Services in Smart Infrastructure. Proceedings of the 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC), Paris, France.","DOI":"10.1109\/FMEC49853.2020.9144819"},{"key":"ref_6","unstructured":"ITU (2021, January 19). G.114: One-Way Transmission Time. Available online: https:\/\/www.itu.int\/rec\/T-REC-G.114-200305-I\/en."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1109\/TNSM.2013.110513.130490","article-title":"A Prioritized Adaptive Scheme for Multimedia Services over IEEE 802.11 WLANs","volume":"Volume 4","author":"Yuan","year":"2013","journal-title":"IEEE Transactions on Network and Service Management"},{"key":"ref_8","unstructured":"Vyopta (2021, January 19). Troubleshooting Packet Loss: How Much Is an Acceptable Amount?. Available online: https:\/\/www.vyopta.com\/blog\/video-conferencing\/understanding-packet-loss\/."},{"key":"ref_9","unstructured":"ITU (2021, January 19). P.800.2: Mean Opinion Score Interpretation and Reporting. Available online: https:\/\/www.itu.int\/rec\/T-REC-P.800.2-201607-I\/en."},{"key":"ref_10","unstructured":"ITU (2021, January 19). G.107: The E-Model: A Computational Model for Use in Transmission Planning. Available online: https:\/\/www.itu.int\/rec\/T-REC-G.107-201506-I\/en."},{"key":"ref_11","unstructured":"Vouzis, P. (2021, January 19). Impact of Packet Loss, Jitter, and Latency on VoIP. Available online: https:\/\/netbeez.net\/blog\/impact-of-packet-loss-jitter-and-latency-on-voip\/."},{"key":"ref_12","unstructured":"Pingman Tools (2021, January 19). How Is MOS Calculated in PingPlotter Pro?. Available online: https:\/\/www.pingman.com\/kb\/article\/how-is-mos-calculated-in-pingplotter-pro-50.html."},{"key":"ref_13","unstructured":"Ribadeneira, A.F. (2021, January 19). An Analysis of the MOS under Conditions of Delay, Jitter and Packet Loss and an Analysis of the Impact of Introducing Packet Loss and an Analysis of the Impact of Introducing Piggybacking and Reed Solomon FEC for VOIP. Available online: https:\/\/scholarworks.gsu.edu\/cgi\/viewcontent.cgi?referer=&httpsredir=1&article=1043&context=cs_theses."},{"key":"ref_14","unstructured":"Elastic (2021, January 19). Elastic Stack, Elastic. Available online: https:\/\/www.elastic.co\/elastic-stack."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.artint.2018.07.007","article-title":"Explanation in Artificial Intelligence: Insights from the Social Science","volume":"267","author":"Miller","year":"2019","journal-title":"Artif. Intell."},{"key":"ref_16","unstructured":"Waikato, U.O. (2021, January 19). Weka. Available online: https:\/\/www.cs.waikato.ac.nz\/ml\/weka\/."},{"key":"ref_17","unstructured":"Yan, S., Guo, Y., Chen, Y., Xie, F., Yu, C., and Liu, Y. (2021, January 19). Enabling QoE Learning and Prediction of WebRTCVideo Communication in Wi-Fi Networks. Available online: https:\/\/eeweb.engineering.nyu.edu\/faculty\/yongliu\/docs\/yishuai_icc17.pdf."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Yan, S., Guo, Y., Chen, Y., and Xie, F. (2018, January 19). Predicting Freezing of WebRTC Videos in Wi-Fi Networks. Proceedings of the International Conference on Ad Hoc Networks, Cairns, Australia.","DOI":"10.1007\/978-3-030-05888-3_27"},{"key":"ref_19","unstructured":"Sulema, Y., Amram, N., Aleshchenko, O., and Sivak, O. (2018, January 2\u20134). Quality of Experience Estimation for WebRTC-based Video Streaming. Proceedings of the 24th European Wireless Conference, Catania, Italy."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ammar, D., Moor, K.D., Skorin-Kapov, L., Fiedler, M., and Heegaard, P.E. (2019, January 14\u201317). Exploring the Usefulness of Machine Learning in the Context of WebRTC Performance Estimation. Proceedings of the 2019 IEEE 44th Conference on Local Computer Networks (LCN), Osnabrueck, Germany.","DOI":"10.1109\/LCN44214.2019.8990677"},{"key":"ref_21","unstructured":"Gast, M. (2012). 802.11n: A Survival Guide, O\u2019Reilly Media."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Morshedi, M., and Noll, J. (2020, January 8\u201310). A Survey on Prediction of PQoS Using Machine Learning on Wi-Fi Networks. Proceedings of the 2020 International Conference on Advanced Technologies for Communications (ATC), Nha Trang, Vietnam.","DOI":"10.1109\/ATC50776.2020.9255457"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Spetebroot, T., Afra, S., Aguilera, N., Saucez, D., and Barakat, C. (2015, January 12\u201313). From Network-level Measurements to Expected Quality of Experience: The Skype Use Case. Proceedings of the 2015 IEEE International Workshop on Measurements & Networking (M&N), Coimbra, Portugal.","DOI":"10.1109\/IWMN.2015.7322989"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/13\/3\/63\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:32:01Z","timestamp":1760160721000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/13\/3\/63"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,3]]},"references-count":23,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,3]]}},"alternative-id":["fi13030063"],"URL":"https:\/\/doi.org\/10.3390\/fi13030063","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2021,3,3]]}}}