Empirical Evaluation of HTTP Adaptive Streaming under Vehicular Mobility

Yao, Jun; Kanhere, Salil S.; Hossain, Imran; Hassan, Mahbub

doi:10.1007/978-3-642-20757-0_8

Cited by 50 publications

(44 citation statements)

References 8 publications

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“…The ClosetoEdge video (43,24) is from a documentary and is mostly shot with a handheld camera and features varying characteristics. The Rollingstone video (45,42) is from a concert recording, where the lead singer moves around a lot and the video has some sudden scene changes. The News (49,23) video is from a TV news broadcast and has static scenes with one/two standing/sitting people, some scenes with moving background and some scenes without reporters with more motion and panning.…”

Section: Subjective Experiments Of Video Qualitymentioning

confidence: 99%

“…The adaptation is made possible through the provision of multiple bitrate copies in segments of the video being transmitted from the server. The usage of adaptive streaming has been notably observed to be useful in the reduction of video stalling that might occur due to bandwidth constraints [45]. A client might prefer to switch to lower quality video instead of experiencing a halt (buffering) in the video playback.…”

Section: Introductionmentioning

confidence: 99%

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On subjective quality assessment of adaptive video streaming via crowdsourcing and laboratory based experiments

Sogaard

Shahid

Pokhrel

et al. 2016

Multimed Tools Appl

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Video streaming services are offered over the Internet and since the service providers do not have full control over the network conditions all the way to the end user, streaming technologies have been developed to maintain the quality of service in these varying network conditions i.e. so called adaptive video streaming. In order to cater for users' Quality of Experience (QoE) requirements, HTTP based adaptive streaming solutions of video services have become popular. However, the keys to ensure the users a good QoE with this technology is still not completely understood. User QoE feedback is therefore instrumental in improving this understanding. Controlled laboratory based perceptual quality experiments that involve a panel of human viewers are considered to be the most valid method of the assessment of QoE. Besides laboratory based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative

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Section: Subjective Experiments Of Video Qualitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On subjective quality assessment of adaptive video streaming via crowdsourcing and laboratory based experiments

Sogaard

Shahid

Pokhrel

et al. 2016

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…The work in [9] has analysed the trade-off between those two impairments directly. In the context of HAS, studies on optimal segment length and buffer size [24], also identified initial delays as an impairment type to be considered. Concerning stalling events during the video playout, it is generally assumed that they decrease QoE severely and that quality adaptation performs better.…”

Section: Related Workmentioning

confidence: 99%

The Impact of Adaptation Strategies on Perceived Quality of HTTP Adaptive Streaming

Egger

Gardlo

Seufert

et al. 2014

Proceedings of the 2014 Workshop on Design, Quality and Deployment of Adaptive Video Streaming

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Changing network conditions like bandwidth fluctuations and resulting bad user experience issues (e.g. video freezes) pose severe challenges to Internet video streaming. To address this problem, an increasing number of video services utilizes HTTP adaptive streaming (HAS). HAS enables service providers to improve Quality of Experience (QoE) and resource utilization by incorporating information from different layers. However, these adaptation possibilities of HAS also introduce new perceivable impairments such as the fluctuation of audiovisual quality levels over time, which in turn lead to novel QoE-related research questions. The main contribution of this paper is the formulation of open research questions as well as a thorough systematic user-centric analysis of different quality adaptation dimensions and strategies. The underlying data has been acquired through two crowdsourcing and one lab study. The results provide guidance w.r.t. which encoding dimensions are combined best for the creation of the adaptation set and what type of adaptation strategy should be used. Furthermore it provides insights on the impact of adaptation frequency and the true QoE gain of adaptation over stallings.

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“…The type of encoder immensely influences QoE and is applicable for scalable video codecs (SVC) that inspect streaming using H.264/SVC with wavelet-based coding. Authors of [70,71,72,73,74] introduced a new approach to encode and segment video information for adaptively streaming H.264 video. They also achieved up to 30% reduction in encoding bitrate while maintaining the same or higher quality of video.…”

Section: Network Protocols and Algorithmsmentioning

confidence: 99%

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

Taha

Lloret

Cánovas

et al. 2017

NPA

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Streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users experience. Due to changing network conditions, bit rate and initial delay, the multimedia file freezes or provides poor video quality to the end users. Researchers across industry and academia have explored HTTP Adaptive Streaming (HAS), which splits the video content into multiple segments and offers the clients varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively vary bit rate and video quality to match the transmission media conditions. Furthermore, the main aim of this paper is to give an overview on the state of the art of HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering, etc. It also focuses on various challenges on QoE influence ISSN 1943-3581 2017 www.macrothink.org/npa 86 factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Moreover, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments. Network Protocols and Algorithms

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Empirical Evaluation of HTTP Adaptive Streaming under Vehicular Mobility

Cited by 50 publications

References 8 publications

On subjective quality assessment of adaptive video streaming via crowdsourcing and laboratory based experiments

On subjective quality assessment of adaptive video streaming via crowdsourcing and laboratory based experiments

The Impact of Adaptation Strategies on Perceived Quality of HTTP Adaptive Streaming

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

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