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

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

Research output: Contribution to journalArticleResearch

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. Meanwhile, 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. The 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.
Original languageEnglish
JournalIEEE Journal on Selected Areas in Communications
Early online date6 Jun 2016
DOIs
Publication statusE-pub ahead of print - 6 Jun 2016

Fingerprint

HTTP
Video streaming
Internet
Media streaming
Multimedia services
Heterogeneous networks
Testbeds
Network architecture
Throughput
Network protocols
Software defined networking
Costs

Keywords

  • Hierarchical resource allocation
  • adaptive media streaming
  • software defined networking
  • QoE utility fairness
  • network orchestration
  • human factor

Cite this

Mu, Mu ; Broadbent, Matthew ; Farshad, Arsham ; Hart, Nicholas ; Hutchison, David ; Ni, Qiang ; Race, Nicholas. / A scalable user fairness model for adaptive video streaming over SDN-assisted future networks. In: IEEE Journal on Selected Areas in Communications. 2016.
@article{4e1c0268854a4e4a83fcce50743d0915,
title = "A scalable user fairness model for adaptive video streaming over SDN-assisted future networks",
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. Meanwhile, 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. The 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.",
keywords = "Hierarchical resource allocation, adaptive media streaming, software defined networking, QoE utility fairness, network orchestration, human factor",
author = "Mu Mu and Matthew Broadbent and Arsham Farshad and Nicholas Hart and David Hutchison and Qiang Ni and Nicholas Race",
year = "2016",
month = "6",
day = "6",
doi = "10.1109/JSAC.2016.2577318",
language = "English",
journal = "IEEE Journal on Selected Areas in Communications",
issn = "0733-8716",
publisher = "Institute of Electrical and Electronics Engineers",

}

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.

In: IEEE Journal on Selected Areas in Communications, 06.06.2016.

Research output: Contribution to journalArticleResearch

TY - JOUR

T1 - A scalable user fairness model for adaptive video streaming over SDN-assisted future networks

AU - Mu, Mu

AU - Broadbent, Matthew

AU - Farshad, Arsham

AU - Hart, Nicholas

AU - Hutchison, David

AU - Ni, Qiang

AU - Race, Nicholas

PY - 2016/6/6

Y1 - 2016/6/6

N2 - 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. Meanwhile, 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. The 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.

AB - 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. Meanwhile, 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. The 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.

KW - Hierarchical resource allocation

KW - adaptive media streaming

KW - software defined networking

KW - QoE utility fairness

KW - network orchestration

KW - human factor

U2 - 10.1109/JSAC.2016.2577318

DO - 10.1109/JSAC.2016.2577318

M3 - Article

JO - IEEE Journal on Selected Areas in Communications

JF - IEEE Journal on Selected Areas in Communications

SN - 0733-8716

ER -