TY - GEN
T1 - Video QoE killer and performance statistics in WebRTC-based video communication
AU - Ammar, Doreid
AU - De Moor, Katrien
AU - Xie, Min
AU - Fiedler, Markus
AU - Heegaard, Poul
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/7
Y1 - 2016/9/7
N2 - In this paper, we investigate session-related performance statistics of a Web-based Real-Time Communication (WebRTC) application called appear.in. We explore the characteristics of these statistics and explore how they may relate to users' Quality of Experience (QoE). More concretely, we have run a series of tests involving two parties and according to different test scenarios, and collected real-Time session statistics by means of Google Chrome's WebRTC-internals tool. Despite the fact that the Chrome statistics have a number of limitations, our observations indicate that they are useful for QoE research when these limitations are known and carefully handled when performing post-processing analysis. The results from our initial tests show that a combination of performance indicators measured at the sender's and receiver's end may help to identify severe video freezes (being an important QoE killer) in the context of WebRTC-based video communication. In this paper the performance indicators used are significant drops in data rate, non-zero packet loss ratios, non-zero PLI values, and non-zero bucket delay.
AB - In this paper, we investigate session-related performance statistics of a Web-based Real-Time Communication (WebRTC) application called appear.in. We explore the characteristics of these statistics and explore how they may relate to users' Quality of Experience (QoE). More concretely, we have run a series of tests involving two parties and according to different test scenarios, and collected real-Time session statistics by means of Google Chrome's WebRTC-internals tool. Despite the fact that the Chrome statistics have a number of limitations, our observations indicate that they are useful for QoE research when these limitations are known and carefully handled when performing post-processing analysis. The results from our initial tests show that a combination of performance indicators measured at the sender's and receiver's end may help to identify severe video freezes (being an important QoE killer) in the context of WebRTC-based video communication. In this paper the performance indicators used are significant drops in data rate, non-zero packet loss ratios, non-zero PLI values, and non-zero bucket delay.
UR - http://www.scopus.com/inward/record.url?scp=84988843889&partnerID=8YFLogxK
U2 - 10.1109/CCE.2016.7562675
DO - 10.1109/CCE.2016.7562675
M3 - Conference contribution
AN - SCOPUS:84988843889
T3 - 2016 IEEE 6th International Conference on Communications and Electronics, IEEE ICCE 2016
SP - 429
EP - 436
BT - 2016 IEEE 6th International Conference on Communications and Electronics, IEEE ICCE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Communications and Electronics, IEEE ICCE 2016
Y2 - 27 July 2016 through 29 July 2016
ER -