Modeling the qoe of rate changes in SKYPE/SILK VoIP calls

Chen, Chien-nan; Chu, Cing-Yu; Yeh, Su‐Ling; Chu, Hao-Hua; Huang, Polly

doi:10.1145/2393347.2393370

Cited by 7 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This corresponds to the research findings in [7] and [21]. As such, gradual bitrate switches are indeed preferred over large multi-range switches since they have a smaller impact on quality perception [23], [24]. Remark, however, that this finding is in our case only valid when switching between the highest and lowest quality levels of the video.…”

Section: Scenario 3: Influence Of Multi-range Bitrate Switchessupporting

confidence: 89%

“…For example, results in [23] and [24] show that the impact of quality fluctuations during quality assessment is relative to the current perceived quality level. The fact that frequent bitrate switches should be avoided was also concluded based on the experiments conducted in [25].…”

Section: Overview Of Subjective Video Quality Experiments On Mobmentioning

confidence: 99%

“…Accordingly, three different scenarios with a fixed duration of 108 seconds were selected in order to evaluate 1) the impact of bitrate fluctuations on current quality perception [23], [24] and the influence of buffer starvations [26], [27], 2) the influence of frequent bitrate switches [25], 3) the difference between multi-ranges bitrate switches and gradual bitrate switches [7], [21], on quality perception. These scenarios are also graphically represented in Fig.…”

Section: Simulating Video Delivery Over Http Adaptive Streamingmentioning

confidence: 99%

“…No real difference can be observed between switching to a mid-quality levels gradually or instantaneously. As such, there are limited noticeable differences between the high and mid-quality levels of the video stream [22] which impact quality ratings [23], [24]. In the third scenario (Section V-C), we will investigate whether this is also the case when switching gradually or instantaneously between the highest and the lowest quality levels of the video stream.…”

Section: A Scenario 1: Influence Of Bitrate Fluctuations and Video Smentioning

confidence: 99%

See 3 more Smart Citations

Subjective Quality Assessment of Longer Duration Video Sequences Delivered Over HTTP Adaptive Streaming to Tablet Devices

Staelens

Meulenaere

Claeys

et al. 2014

IEEE Trans. on Broadcast.

View full text Add to dashboard Cite

Abstract-HTTP Adaptive Streaming facilitates video streaming to mobile devices connected through heterogeneous networks without the need for a dedicated streaming infrastructure. By splitting different encoded versions of the same video into small segments, clients can continuously decide which segments to download based on available network resources and device characteristics. These encoded versions can, for example, differ in terms of bitrate and spatial or temporal resolution. However, as a result of dynamically selecting video segments, perceived video quality can fluctuate during playback which will impact end-users' Quality of Experience. Subjective studies have already been conducted to assess the influence of video delivery using HTTP Adaptive Streaming to mobile devices. Nevertheless, existing studies are limited to the evaluation of short video sequences in controlled environments. Research has already shown that video duration and assessment environment influence quality perception. Therefore, in this article, we go beyond the traditional ways for subjective quality evaluation by conducting novel experiments on tablet devices in more ecologically valid testing environments using longer duration video sequences. As such, we want to mimic realistic viewing behaviour as much as possible. Our results show that both video content and the range of quality switches significantly influence end-users' rating behaviour. In general, quality level switches are only perceived in high motion sequences or in case switching occurs between high and low quality video segments. Moreover, we also found that video stallings should be avoided during playback at all times.Index Terms-Quality of Experience (QoE), Subjective video quality assessment, HTTP adaptive streaming, Mobile video, Tablet devices.

show abstract

Section: Scenario 3: Influence Of Multi-range Bitrate Switchessupporting

confidence: 89%

Section: Overview Of Subjective Video Quality Experiments On Mobmentioning

confidence: 99%

Section: Simulating Video Delivery Over Http Adaptive Streamingmentioning

confidence: 99%

Section: A Scenario 1: Influence Of Bitrate Fluctuations and Video Smentioning

confidence: 99%

See 2 more Smart Citations

Subjective Quality Assessment of Longer Duration Video Sequences Delivered Over HTTP Adaptive Streaming to Tablet Devices

Staelens

Meulenaere

Claeys

et al. 2014

IEEE Trans. on Broadcast.

View full text Add to dashboard Cite

show abstract

“…There have also been large scale studies looking at MPEG-2 video streaming [24] and Skype [31] [19] traffic. These studies examine the link between network QoS, specifically latency, jitter and packet loss, and QoE as measured by mean opinion scores from user surveys.…”

Section: Related Workmentioning

confidence: 99%

Scalable classification of QoS for real-time interactive applications from IP traffic measurements

Middleton

Modafferi

2016

Computer Networks

View full text Add to dashboard Cite

Measurement of network Quality of Service (QoS) has attracted considerable research effort over the last two decades. The recent trend towards Internet Service Providers (ISP's) offering application-specific QoS is creating possibilities for more sophisticated QoS metrics to be offered by ISP's in service level agreements. This in turn could be used for the purposes of improved network optimization and billing according to application specific QoS guarantees. We report a scalable near real-time approach using passively logging IP traffic data for classification of application latency and packet loss across a range of real-time interactive applications. We run six experiments involving Minecraft, Quake 3 Urban Terror, VLC video streaming and the commercial Wirofon VOIP application. We use a mixture of laboratory and realworld deployments, with run times ranging from hours to days, and observe a combination of real and simulated ISP latency and packet loss events. Our binary classification (i.e. classes 'OK' or 'lag') 10-fold cross validation F1 scores are between 0.80 and 0.93 depending on application type. Our multi-class classification (i.e. classes representing discrete packet loss or latency ranges) 10-fold cross validation F1 scores for Minecraft are 0.89 for latency and 0.90 for packet loss. With new business models between ISP's and application developers being actively considered this work represents a significant contribution to the debate by providing scientific evidence relating to a novel approach to scalable QoS measurement

show abstract

A QoE centric distributed caching approach for vehicular video streaming in cellular networks

Sun

Liu

Hou

et al. 2015

Wireless Communications

View full text Add to dashboard Cite

Distributed caching‐empowered wireless networks can greatly improve the efficiency of data storage and transmission and thereby the users' quality of experience (QoE). However, how this technology can alleviate the network access pressure while ensuring the consistency of content delivery is still an open question, especially in the case where the users are in fast motion. Therefore, in this paper, we investigate the caching issue emerging from a forthcoming scenario where vehicular video streaming is performed under cellular networks. Specifically, a QoE centric distributed caching approach is proposed to fulfill as many users' requests as possible, considering the limited caching space of base stations and basic user experience guarantee. Firstly, a QoE evaluation model is established using verified empirical data. Also, the mathematic relationship between the streaming bit rate and actual storage space is developed. Then, the distributed caching management for vehicular video streaming is formulated as a constrained optimization problem and solved with the generalized–reduced gradient method. Simulation results indicate that our approach can improve the users' satisfaction ratio by up to 40%. Copyright © 2015 John Wiley & Sons, Ltd.

show abstract

Modeling the qoe of rate changes in SKYPE/SILK VoIP calls

Cited by 7 publications

References 15 publications

Subjective Quality Assessment of Longer Duration Video Sequences Delivered Over HTTP Adaptive Streaming to Tablet Devices

Subjective Quality Assessment of Longer Duration Video Sequences Delivered Over HTTP Adaptive Streaming to Tablet Devices

Scalable classification of QoS for real-time interactive applications from IP traffic measurements

A QoE centric distributed caching approach for vehicular video streaming in cellular networks

Contact Info

Product

Resources

About