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

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A scalable user fairness model for adaptive video streaming over SDN-assisted future networks. / Mu, M.; Broadbent, M.; Farshad, A.; Hart, N.; Hutchison, D.; Ni, Q.; Race, N.

In: IEEE Journal on Selected Areas in Communications, Vol. 34, No. 8, 01.08.2016, p. 2168-2184.

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@article{11d81b2f643a48498718ffbc601d1cab,
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, 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 $^text HA$ , 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 $^text HA$ 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 = "Adaptive systems, Internet, Media, Protocols, Resource management, Streaming media, Video recording, Hierarchical resource allocation, QoE utility fairness, adaptive media streaming, human factor, network orchestration, software defined networking",
author = "M. Mu and M. Broadbent and A. Farshad and N. Hart and D. Hutchison and Q. Ni and N. Race",
note = "{\circledC}2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.",
year = "2016",
month = "8",
day = "1",
doi = "10.1109/JSAC.2016.2577318",
language = "English",
volume = "34",
pages = "2168--2184",
journal = "IEEE Journal on Selected Areas in Communications",
issn = "0733-8716",
publisher = "IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC",
number = "8",

}

RIS

TY - JOUR

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

AU - Mu, M.

AU - Broadbent, M.

AU - Farshad, A.

AU - Hart, N.

AU - Hutchison, D.

AU - Ni, Q.

AU - Race, N.

N1 - ©2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2016/8/1

Y1 - 2016/8/1

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, 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 $^text HA$ , 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 $^text HA$ 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, 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 $^text HA$ , 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 $^text HA$ 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 - Adaptive systems

KW - Internet

KW - Media

KW - Protocols

KW - Resource management

KW - Streaming media

KW - Video recording

KW - Hierarchical resource allocation

KW - QoE utility fairness

KW - adaptive media streaming

KW - human factor

KW - network orchestration

KW - software defined networking

U2 - 10.1109/JSAC.2016.2577318

DO - 10.1109/JSAC.2016.2577318

M3 - Journal article

VL - 34

SP - 2168

EP - 2184

JO - IEEE Journal on Selected Areas in Communications

JF - IEEE Journal on Selected Areas in Communications

SN - 0733-8716

IS - 8

ER -