Real-time video adaptation in virtualised 5G networks

Pablo Salva-Garcia; Jose M. Alcaraz-Calero; Qi Wang; Maria Barros; Anastasius Gavras

doi:10.1109/LCN44214.2019.8990815

Real-time video adaptation in virtualised 5G networks

Pablo Salva-Garcia, Jose M. Alcaraz-Calero, Qi Wang, Maria Barros, Anastasius Gavras

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Video applications are expected to increasingly dominate the traffic of mobile networks in the 5G era, and thus a real-time adaptation of these high resource demanding network applications is crucial in optimising the overall 5G networks. In this manuscript, we leverage Virtual Network Function (VNF) techniques to implement a video adaptation service that automatically adapts the quality of video transmissions depending on the status of the network. Furthermore, Network Function Virtualisation (NFV) techniques are employed here to simplify, optimise and speed up the deployment process of the aforementioned video adapter service (vAdapter), and therefore, allowing its on-demand deployment in a flexible way. We design, implement and test the scheme in a realistic virtualised 5G testbed. Empirical results focus on the scalability evaluation and performance as well as demonstrates a significant bandwidth reduction without compromising the final user’s video quality expectations.

Original language	English
Title of host publication	2019 IEEE 44th Conference on Local Computer Networks (LCN)
Editors	Karl Andersson, Hwee-Pink Tan, Sharief Oteafy
Publisher	IEEE
Number of pages	4
ISBN (Electronic)	9781728110288
DOIs	https://doi.org/10.1109/LCN44214.2019.8990815
Publication status	Published - 13 Feb 2020

Bibliographical note

IEEE Conference on Local Computer Networks, LCN 2019 ; Conference date: 14-10-2019 Through 17-10-2019

Keywords

Real-time
Multimedia
Adaptive
SDN
NFV
5G
Network management
QoS

Access to Document

10.1109/LCN44214.2019.8990815

Cite this

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title = "Real-time video adaptation in virtualised 5G networks",

abstract = "Video applications are expected to increasingly dominate the traffic of mobile networks in the 5G era, and thus a real-time adaptation of these high resource demanding network applications is crucial in optimising the overall 5G networks. In this manuscript, we leverage Virtual Network Function (VNF) techniques to implement a video adaptation service that automatically adapts the quality of video transmissions depending on the status of the network. Furthermore, Network Function Virtualisation (NFV) techniques are employed here to simplify, optimise and speed up the deployment process of the aforementioned video adapter service (vAdapter), and therefore, allowing its on-demand deployment in a flexible way. We design, implement and test the scheme in a realistic virtualised 5G testbed. Empirical results focus on the scalability evaluation and performance as well as demonstrates a significant bandwidth reduction without compromising the final user{\textquoteright}s video quality expectations.",

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author = "Pablo Salva-Garcia and Alcaraz-Calero, {Jose M.} and Qi Wang and Maria Barros and Anastasius Gavras",

note = "IEEE Conference on Local Computer Networks, LCN 2019 ; Conference date: 14-10-2019 Through 17-10-2019",

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AU - Alcaraz-Calero, Jose M.

AU - Wang, Qi

AU - Barros, Maria

AU - Gavras, Anastasius

N1 - IEEE Conference on Local Computer Networks, LCN 2019 ; Conference date: 14-10-2019 Through 17-10-2019

PY - 2020/2/13

Y1 - 2020/2/13

N2 - Video applications are expected to increasingly dominate the traffic of mobile networks in the 5G era, and thus a real-time adaptation of these high resource demanding network applications is crucial in optimising the overall 5G networks. In this manuscript, we leverage Virtual Network Function (VNF) techniques to implement a video adaptation service that automatically adapts the quality of video transmissions depending on the status of the network. Furthermore, Network Function Virtualisation (NFV) techniques are employed here to simplify, optimise and speed up the deployment process of the aforementioned video adapter service (vAdapter), and therefore, allowing its on-demand deployment in a flexible way. We design, implement and test the scheme in a realistic virtualised 5G testbed. Empirical results focus on the scalability evaluation and performance as well as demonstrates a significant bandwidth reduction without compromising the final user’s video quality expectations.

AB - Video applications are expected to increasingly dominate the traffic of mobile networks in the 5G era, and thus a real-time adaptation of these high resource demanding network applications is crucial in optimising the overall 5G networks. In this manuscript, we leverage Virtual Network Function (VNF) techniques to implement a video adaptation service that automatically adapts the quality of video transmissions depending on the status of the network. Furthermore, Network Function Virtualisation (NFV) techniques are employed here to simplify, optimise and speed up the deployment process of the aforementioned video adapter service (vAdapter), and therefore, allowing its on-demand deployment in a flexible way. We design, implement and test the scheme in a realistic virtualised 5G testbed. Empirical results focus on the scalability evaluation and performance as well as demonstrates a significant bandwidth reduction without compromising the final user’s video quality expectations.

KW - Real-time

KW - Multimedia

KW - Adaptive

KW - SDN

KW - NFV

KW - 5G

KW - Network management

KW - QoS

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BT - 2019 IEEE 44th Conference on Local Computer Networks (LCN)

A2 - Andersson, Karl

A2 - Tan, Hwee-Pink

A2 - Oteafy, Sharief

PB - IEEE

ER -

Real-time video adaptation in virtualised 5G networks

Abstract

Bibliographical note

Keywords

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