FALCON: joint fair airtime allocation and rate control for DASH video streaming in software defined wireless networks

Altres títols

Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video

Autor/a

Betzler, August

Camps, Daniel

Catalan, Miguel

Montagud, Mario

Data de publicació

2020-06-10



Resum

Software Defined Wireless Networks offer an opportunity to enhance the performance of specific services by applying centralized mechanisms which make use of a global view of the network resources. This paper presents FALCON, a novel solution that jointly optimizes fair airtime allocation and rate recommendations for Server and Network Assisted DASH video streaming, providing proportional fairness among the wireless DASH clients. Since this problem is NP-hard and its resolution in dense scenarios is too computationally expensive to be applied in practice, FALCON introduces a novel heuristic algorithm that is proved to achieve almost optimal results in a significantly lower time. The performance of FALCON is also evaluated when used in conjunction with three referent Adaptive Bit Rate strategies (PANDA, BOLA and RobustMPC) in a simulated realistic ultra-dense scenario based on an In-flight Entertainment System with up to 175 clients. The obtained results show that FALCON provides significant benefits by minimizing instability and buffer underruns, while obtaining a fair video rate and airtime allocation among clients, thus contributing to an enhanced Quality of Experience.

Tipus de document

Edició preliminar

Llengua

Anglès

Matèries CDU

621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions

Paraules clau

Xarxes d'àrea extensa (Ordinadors); Mobile Wireless Internet

Pàgines

7 p.

Publicat per

Association for Computing Machinery (ACM)

És versió de

NOSSDAV '20: Proceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video

Documents

4 - FALCON-MigueCatalanCid-i2CAT-NOSSDAV20-preprint (1).pdf

1.053Mb

 

Drets

© {Camps, Daniel | ACM} {2021use. Not for redistribution. The definitive Version of Record was published in {Association for Computing Machinery}, https://doi.org/10.1145/3386290.3396931{NOSSDAV '20}.

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