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A scalable user fairness model for adaptive video streaming over SDN-assisted future networks

Mu, Mu; Broadbent, Matthew; Farshad, Arsham; Hart, Nicholas; Hutchison, David; Ni, Qiang; Race, Nicholas

Authors

Mu Mu

Arsham Farshad

Nicholas Hart

David Hutchison

Qiang Ni

Nicholas Race



Abstract

The growing demand for online distribution of high quality and high throughput content is dominating today's Internet infrastructure. This includes both production and user-generated media. Among the myriad of media distribution mechanisms, HTTP adaptive streaming (HAS) is becoming a popular choice for multi-screen and multi-bitrate media services over heterogeneous networks. HAS applications often compete for network resources without any coordination between each other. This leads to quality of experience (QoE) fluctuations on delivered content, and unfairness between end users, while new network protocols, technologies, and architectures, such as software defined networking (SDN), are being developed for the future Internet. The programmability, flexibility, and openness of these emerging developments can greatly assist the distribution of video over the Internet. This is driven by the increasing consumer demands and QoE requirements. This paper introduces a novel user-level fairness model UFair and its hierarchical variant UFair HA , which orchestrate HAS media streams using emerging network architectures and incorporate three fairness metrics (video quality, switching impact, and cost efficiency) to achieve user-level fairness in video distribution. UFair HA has also been implemented in a purpose-built SDN testbed using open technologies, including OpenFlow. Experimental results demonstrate the performance and feasibility of our design for video distribution over future networks.

Citation

Mu, M., Broadbent, M., Farshad, A., Hart, N., Hutchison, D., Ni, Q., & Race, N. (2016). A scalable user fairness model for adaptive video streaming over SDN-assisted future networks. IEEE Journal on Selected Areas in Communications, 34(8), 2168-2184. https://doi.org/10.1109/JSAC.2016.2577318

Journal Article Type Article
Acceptance Date Feb 16, 2016
Online Publication Date Jun 6, 2016
Publication Date 2016-08
Deposit Date Mar 8, 2022
Journal IEEE Journal on Selected Areas in Communications
Print ISSN 0733-8716
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 34
Issue 8
Pages 2168-2184
DOI https://doi.org/10.1109/JSAC.2016.2577318
Keywords Hierarchical resource allocation, adaptive media streaming, software defined networking, QoE utility fairness, network orchestration, human factor
Public URL http://researchrepository.napier.ac.uk/Output/2844169