Modeling and Design of Adaptive Video Streaming Control Systems

Cofano, Giuseppe; Cicco, Luca De; Mascolo, Saverio

doi:10.1109/tcns.2016.2631452

Cited by 11 publications

(6 citation statements)

References 20 publications

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“…The authors, propose a D-DASH framework that combines the use of Deep Learning and Reinforcement Learning techniques to enable the QoE optimization at the end-user. One Thus, in order to enable high Quality of Experience at the mobile user side the following aspects need to be addressed: avoiding re-buffering events and playback interruptions, minimizing the start-up delay and maximizing the video quality level, finding a trade-off between the stream switching frequency and the storage costs at the servers [121].…”

Section: E Discussionmentioning

confidence: 99%

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

Trestian

Comşa

Tüysüz

2018

IEEE Commun. Surv. Tutorials

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Copyright and moral rights to this work are retained by the author and/or other copyright owners unless otherwise stated. The work is supplied on the understanding that any use for commercial gain is strictly forbidden. A copy may be downloaded for personal, non-commercial, research or study without prior permission and without charge.Works, including theses and research projects, may not be reproduced in any format or medium, or extensive quotations taken from them, or their content changed in any way, without first obtaining permission in writing from the copyright holder(s). They may not be sold or exploited commercially in any format or medium without the prior written permission of the copyright holder(s).Full bibliographic details must be given when referring to, or quoting from full items including the author's name, the title of the work, publication details where relevant (place, publisher, date), pagination, and for theses or dissertations the awarding institution, the degree type awarded, and the date of the award.If you believe that any material held in the repository infringes copyright law, please contact the Repository Team at Middlesex University via the following email address:eprints@mdx.ac.ukThe item will be removed from the repository while any claim is being investigated. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract-The increasing popularity of live video streaming from mobile devices such as Facebook Live, Instagram Stories, Snapchat, etc. pressurises the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of Quality of Experience (QoE) as the basis for network control, customer loyalty and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users' quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-theart approaches following three key directions: adaptation, energy efficiency and multipath content delivery. Discussions, challenges and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided.

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Section: E Discussionmentioning

confidence: 99%

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

Trestian

Comşa

Tüysüz

2018

IEEE Commun. Surv. Tutorials

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“…Cofano and De Cicco [13] proposed rules to guide the controller design, by designing a model to control the level based on a hybrid dynamic system. Based on this model, they derived a relationship between minimum switching frequency and control system parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

“…6. The general goal of the proposed control algorithm ( [13]) is maximizing QoE for users in available bandwidth. To achieve this goal, they designed an official model of the closed-loop system by using a level-based hysteresis controller.…”

Section: Literature Reviewmentioning

confidence: 99%

An Adaptive Quality Switch-aware Framework for Optimal Bitrate Video Streaming Delivery

Alqhtani¹,

Ashraf²,

Maazen³

2020

IJACSA

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Given a large number of online video viewers, video streaming, over various networks, is important communication technology. The multitude of viewers makes it challenging for service providers to provide a good viewing experience for subscribers. Video streaming capabilities are designed based on concepts including quality, viewing flexibility, changing network conditions, and specifications for different customer devices. Adjusting the quality levels, and controlling various relevant parameters to stream the video content with good quality and without interruption is vital. This paper proposes an adaptive framework to balance the average video bitrates with respect to appropriate quality switches, making the transition to higher switches more seamless. The quality adaptation scheme increases the bitrates to the maximum value at their current quality switch before shifting to a higher level. This reduced switching times between levels and guarantees the stability of viewing and avoids interruptions. The use of a dynamic system ensures optimal performance, by controlling system parameters and making the algorithm more tunable. We built the system using an open-source DASH library (Libdash) with QuickTime player, studied the video load changes on two performance parameters, Central Processing Unit and Memory usages that have a high impact on multimedia quality. Consequently, the values of parameters that affected the performance of video streaming could be decreased, permitting users to regulate the parameters according to their preferences. Further, reducing the switching levels will reduce the overloads that occur while transferring from one level to another.

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“…The algorithm presented in [116] considered the measured throughput, bu er occupancy, and the variation in segment sizes to better manage the users' QoE. Finally, [117] modeled adaptation control systems to gain design insights.…”

Section: Background and Related Workmentioning

confidence: 99%

Quality of experience and access network traffic management of HTTP adaptive video streaming

Seufert

Tran-Gia

2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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Modeling and Design of Adaptive Video Streaming Control Systems

Cited by 11 publications

References 20 publications

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

An Adaptive Quality Switch-aware Framework for Optimal Bitrate Video Streaming Delivery

Quality of experience and access network traffic management of HTTP adaptive video streaming

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