QoE Assessment of HTTP Adaptive Video Streaming

Salvador, André; Nogueira, João; Sargento, Susana

doi:10.1007/978-3-319-18802-7_32

Cited by 9 publications

(3 citation statements)

References 4 publications

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“…With these models, QoE estimations can be made on-the-fly for a given service or video stream. As mentioned previously, the objective metrics show correlation with QoE scores and how each QoS parameter impacted the final QoE [26] [36].…”

Section: Qoementioning

confidence: 67%

“…This analysis will be on the client side, clearly the best place to perform the QoE assessment. A QoE probe implementation was done in [36], writen in C#, with Microsoft Smooth Streaming in mind. For MPEG-DASH , the probe was then adapted in [25] to support the Dash.JS player, a multi-platform and license free option for DASH written in AngularJS.…”

Section: Probing Qoe In Adaptive Video Transmissionsmentioning

confidence: 99%

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QoE of Video Streaming in Multihomed Vehicular Networks

Vieira

Luís

Zúquete

et al. 2019

Proceedings of the 4th Internet-QoE Workshop on QoE-based Analysis and Management of Data Communication Networks

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agradecimentos / acknowledgementsChega ao fim este grande capítulo da minha vida. Quero agradecer primeiramente e especialmente aos meus pais, por me darem esta oportunidade, por sempre me terem incentivado e apoiado. À restante família que me motivou neste percurso. Agradecer também à Samantha Oliveira por todo o apoio ao longo deste anos, por ter estado sempre ao meu lado e me ter aturado. Juntamente, ao Filipe Rocha e às demais viagens para a Universidade; aos pequenos-almoços em conjunto que davam a energia necessária logo pela manhã. Quero agradecer também ao Diogo Cunha pelos bons momentos e estadias passadas em Aveiro. Agradeço ao professor orientador André Zuquete, coorientador Miguel Luís e professora Susana Sargento pela orientação, ajuda prestada e oportunidade de fazer parte do NAP. Um agradecimento também aos colegas do NAP, obrigado por toda a ajuda. Um obrigado aos restantes amigos pelo apoio no meu percurso académico, e a tantos outros que também fizeram parte dele.

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Section: Qoementioning

confidence: 67%

Section: Probing Qoe In Adaptive Video Transmissionsmentioning

confidence: 99%

QoE of Video Streaming in Multihomed Vehicular Networks

Vieira

Luís

Zúquete

et al. 2019

Proceedings of the 4th Internet-QoE Workshop on QoE-based Analysis and Management of Data Communication Networks

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“…Figure 19 presents the MOS evaluation of the 3 approaches, using the MOS calculation in [19], where the mean opinion score is obtained relatively to variations of the video bitrate, screen size and video size ratios, frames per second, and the amount of buffer stalls. This MOS formula has been validated against the evaluation of the quality perception with real users.…”

Section: Assessment Of the Video Qualitymentioning

confidence: 99%

Real-time video frame differentiation in multihomed VANETs

2021

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Providing high quality video transmission in VANETs is very challenging due to the highly dynamic, unpredictable topology, and low bandwidth characteristics. In this article, we design a system able to optimally transmit RTP video streams in an IP-based multihomed VANET. By splitting the video through its different frame types in the array of multihomed paths from the center node of the network to the clients, the system can then send critical frames, depending on the used coding standard, through a more reliable path, in order to improve the video performance even if the quality is degraded due to bad signal reception. Two different content-based multihomed video distribution schemes have been proposed: linear selection, where the system is able to select more reliable paths for higher prioritized segments; and adaptive selection, where the paths are sensed to assess their congestion level in a real-time approach. Through real deployment of these approaches in a real vehicular scenario, with mobility, handovers and multihoming, the proposed approaches achieved a strong decrease in the loss percentage, with a maximum of approximately 60.4%, greatly improving the video quality while on the move.

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Quality of experience evaluation of HTTP video streaming based on user interactive behaviors

Wang

et al. 2017

The Journal of China Universities of Posts and Telecommunicatio

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QoE Assessment of HTTP Adaptive Video Streaming

Cited by 9 publications

References 4 publications

QoE of Video Streaming in Multihomed Vehicular Networks

QoE of Video Streaming in Multihomed Vehicular Networks

Real-time video frame differentiation in multihomed VANETs

Quality of experience evaluation of HTTP video streaming based on user interactive behaviors

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