Rights statement: ©ACM, 2013. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in FhMN '13 Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking http://dx.doi.org/10.1145/2491172.2491181
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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Towards network-wide QoE fairness using openflow-assisted adaptive video streaming
AU - Georgopoulos, Panagiotis
AU - Elkhatib, Yehia
AU - Broadbent, Matthew
AU - Mu, Mu
AU - Race, Nicholas
N1 - ©ACM, 2013. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in FhMN '13 Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking http://dx.doi.org/10.1145/2491172.2491181
PY - 2013/8
Y1 - 2013/8
N2 - Video streaming is an increasingly popular way to consume media content. Adaptive video streaming is an emerging delivery technology which aims to increase user QoE and maximise connection utilisation. Many implementations naively estimate bandwidth from a one-sided client perspective, without taking into account other devices in the network. This behaviour results in unfairness and could potentially lower QoE for all clients. We propose an OpenFlow-assisted QoE Fairness Framework that aims to fairly maximise the QoE of multiple competing clients in a shared network environment. By leveraging a Software Defined Networking technology, such as OpenFlow, we provide a control plane that orchestrates this functionality. The evaluation of our approach in a home networking scenario introduces user-level fairness and network stability, and illustrates the optimisation of QoE across multiple devices in a network.
AB - Video streaming is an increasingly popular way to consume media content. Adaptive video streaming is an emerging delivery technology which aims to increase user QoE and maximise connection utilisation. Many implementations naively estimate bandwidth from a one-sided client perspective, without taking into account other devices in the network. This behaviour results in unfairness and could potentially lower QoE for all clients. We propose an OpenFlow-assisted QoE Fairness Framework that aims to fairly maximise the QoE of multiple competing clients in a shared network environment. By leveraging a Software Defined Networking technology, such as OpenFlow, we provide a control plane that orchestrates this functionality. The evaluation of our approach in a home networking scenario introduces user-level fairness and network stability, and illustrates the optimisation of QoE across multiple devices in a network.
KW - software defined networking
KW - sdn
KW - Quality of experience
KW - QoE
KW - fairness
KW - computer network management
U2 - 10.1145/2491172.2491181
DO - 10.1145/2491172.2491181
M3 - Conference contribution/Paper
SN - 9781450321839
SP - 15
EP - 20
BT - FhMN '13
PB - ACM
CY - New York
ER -