Research Output
Towards network-wide QoE fairness using openflow-assisted adaptive video streaming
  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

  • Date:

    16 August 2013

  • Publication Status:

    Published

  • DOI:

    10.1145/2491172.2491181

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Georgopoulos, P., Elkhatib, Y., Broadbent, M., Mu, M., & Race, N. (2013). Towards network-wide QoE fairness using openflow-assisted adaptive video streaming. In FhMN '13: Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking (15-20). https://doi.org/10.1145/2491172.2491181

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