Performance of Video-Chat Applications under Congestion

Boyacı, Ömer; Forte, Andrea; Schulzrinne, Henning

doi:10.1109/ism.2009.45

Cited by 18 publications

(5 citation statements)

References 8 publications

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“…Packet loss in video-conferencing was approached by measurement of system behavior (e.g. [33]) , or simulations (e.g. [34]) but there is only one study which investigated the effect in video-conferencing with an interactive subjective test [20] with a relatively dated setup (CIF, 15fps, theora codec).…”

Section: A Impact Of System Factors On Videoconferencing Qoe and Intmentioning

confidence: 99%

Towards Individual QoE for Multiparty Videoconferencing

Schmitt

Redi

Bulterman

et al. 2018

IEEE Trans. Multimedia

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Abstract-Video-conferencing is becoming an essential part in everyday life. The visual channel allows for interactions which were not possible over audio-only communication systems such as the telephone. However, being a de-facto over-the-top service, the quality of the delivered video-conferencing experience is subject to variations, dependent on network conditions. Video-conferencing systems adapt to network conditions by changing for example encoding bitrate of the video. For this adaptation not to hamper the benefits related to the presence of a video channel in the communication, it needs to be optimized according to a measure of the Quality of Experience (QoE) as perceived by the user. The latter is highly dependent on the ongoing interaction and individual preferences, which have hardly been investigated so far. In this paper, we focus on the impact video quality has on conversations that revolve around objects that are presented over the video channel. To this end we conducted an empirical study where groups of 4 people collaboratively build a Lego® model over a video-conferencing system. We examine the requirements for such a task by showing when the interaction, measured by visual and auditory cues, changes depending on the encoding bitrate and loss. We then explore the impact that prior experience with the technology and affective state have on QoE of participants. We use these factors to construct predictive models which double the accuracy compared to a model based on the system factors alone. We conclude with a discussion of how these factors could be applied in real world scenarios.Index Terms-Multi-Party video conferencing, Quality of Experience, Over-the-top, subjective quality, quality metrics, user study

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Section: A Impact Of System Factors On Videoconferencing Qoe and Intmentioning

confidence: 99%

Towards Individual QoE for Multiparty Videoconferencing

Schmitt

Redi

Bulterman

et al. 2018

IEEE Trans. Multimedia

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“…Another work [16] investigates Skype video in order to study the rate control of Skype to match the unpredictable Internet bandwidth. The performance of four popular Instant Messenger (IM) clients -Skype, Windows Live Messenger, Eyebeam and X-Lite, focusing mainly on video-telephony part is analyzed in [19]. The authors in [23], compare perceptual voice quality of Skype and Google Talk.…”

Section: Related Workmentioning

confidence: 99%

“…Although many works have characterized the performance of video telephony apps [16,19,25,26,31], to the best of our knowledge, very limited work has been done in terms of video telephony apps' perceptual quality. Also, to the best of our knowledge, no work has been done in this aspect with end-devices being mobile (for example, smartphones).…”

mentioning

confidence: 99%

QoE prediction model for mobile video telephony

Jana

Chan

Pande

et al. 2015

Multimed Tools Appl

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Interactive online video applications, such as video telephony, are known for their vulnerability to network condition. With the increasing usage of hand-held wireless mobile devices, which are capable of capturing and processing good quality videos, combined with the flexibility in an end-user movements have added new challenging factors for application providers and network operators. These factors affect the perceived video quality of mobile video telephony applications, unlike conventional video telephony over desktop computers. We investigate this impact on video quality of mobile video telephony in varying network conditions and end-users movement scenarios. Based on 312 live traces, we quantitatively derive the correlation between the perceived video quality and the network Quality of Service (QoS) and user mobility. With the results, we develop a Quality of Experience (QoE) prediction model for mobile video telephony using Support Vector Regression techniques. The prediction models display ≈ 0.8 pearson correlation with experimental Multimed Tools Appl data. Our methodology and findings can be used to guide the video telephony application providers and network operators to work towards satisfying end-user experience.

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“…Measurements on audio quality [2,15,31], video quality [8,26,38], and interaction factors [9] under different conversational conditions are thus of great interest. Due to the complex tradeoffs among the various factors affecting QoE, there is no single metric that can capture the combined effect of one-way perceptual quality and interactivity.…”

Section: Related Workmentioning

confidence: 99%

Exploiting just-noticeable difference of delays for improving quality of experience in video conferencing

Wah

2013

Proceedings of the 4th ACM Multimedia Systems Conference

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This paper proposes a novel approach for improving the quality of experience (QoE) of real-time video conferencing systems. In these systems, QoE is affected by signal quality as well as interactivity, both depending on the packet loss rate, delay jitters, and mouth-toear delay (MED) that measures the sender-receiver delay on audio signals (and will be the same as that of video signals when video and audio is synchronized). We notice in the current Internet that increasing MED as well as reducing packet rate can help reduce the delay-aware loss rate in congested connections. Between the two methods, the former plays a more important role and applies well to a variety of network conditions for improving audiovisual signal quality, although overly increasing the MED will degrade interactivity. Based on a psychophysical concept called just-noticeable difference (JND), we find the extent to which MED can be increased, without humans perceiving the difference from the original conversation. The approach can be applied to improve existing video conferencing systems. Starting from the operating point of an existing system, we increase its MED to within JND in order to have more room for smoothing network delay spikes as well as recovering lost packets, without incurring noticeable degradation in interactivity. We demonstrate the idea on Skype and Windows Live Messenger by designing a traffic interceptor to extend their buffering time and to perform packet scheduling/recovery. Our experimental results show significant improvements in QoE, with much better signal quality while maintaining similar interactivity.

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Performance of Video-Chat Applications under Congestion

Abstract: We study the performance of four popular IM clients focusing our attention on video-chat. In particular, we analyze how Skype, Windows Live Messenger, Eyebeam and X-Lite react to changes in available bandwidth, presence of HTTP and bit-torrent traffic and random packet losses.

Cited by 18 publications

References 8 publications

Towards Individual QoE for Multiparty Videoconferencing

Towards Individual QoE for Multiparty Videoconferencing

QoE prediction model for mobile video telephony

Exploiting just-noticeable difference of delays for improving quality of experience in video conferencing

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