On the suitability of current x264 rate controller algorithms for high definition video conferencing

2011 ◽  
Author(s):  
Abbas Javadtalab ◽  
Mona Omidyeganeh ◽  
Shervin Shirmohammandi ◽  
Mojtaba Hosseini
Keyword(s):  
Video Conferencing ◽  
High Definition ◽  
High Definition Video

A rate control algorithm for ×264 high definition video conferencing

2011 ◽  
Author(s):  
Abbas Javdtalab ◽  
Mona Omidyeganeh ◽  
Shervin Shirmohammandi ◽  
Mojtaba Hosseini
Keyword(s):  
Rate Control ◽  
Control Algorithm ◽  
Video Conferencing ◽  
High Definition ◽  
High Definition Video ◽  
Rate Control Algorithm

scholarly journals The Benefits and Risks of the Provision of a Hospital-Wide High-Definition Video Conferencing Virtual Visiting Service for Patients and Their Relatives

Cureus ◽  
2021 ◽  
Author(s):  
Adeel Abbas Dhahri ◽  
Agampodi Umanda De Thabrew ◽  
Nirali Ladva ◽  
Helen Pardoe
Keyword(s):  
Video Conferencing ◽  
High Definition ◽  
High Definition Video

scholarly journals A parallel H.264/SVC encoder for high definition video conferencing

2015 ◽  
Vol 30 ◽  
pp. 89-106 ◽  
Author(s):  
Sergio Sanz-Rodríguez ◽  
Mauricio Álvarez-Mesa ◽  
Tobias Mayer ◽  
Thomas Schierl
Keyword(s):  
Video Conferencing ◽  
High Definition ◽  
High Definition Video

scholarly journals Estimating PQoS of Video Conferencing on Wi-Fi Networks Using Machine Learning

2021 ◽  
Vol 13 (3) ◽  
pp. 63
Author(s):  
Maghsoud Morshedi ◽  
Josef Noll
Keyword(s):  
Machine Learning ◽  
Network Performance ◽  
Service Providers ◽  
Video Conferencing ◽  
Machine Learning Algorithms ◽  
Performance Parameters ◽  
High Definition ◽  
Internet Service ◽  
Novel Approach ◽  
5 Ghz

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 92–98% 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’ privacy while reducing the operational costs of monitoring and data analytics.

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