Leveraging SDN to provide an in-network QoE measurement framework

Arsham Farshad, Panagiotis Georgopoulos, Matthew Broadbent, Mu Mu, Nicholas Race

Research output: Contribution to Book/Report typesConference contribution

Abstract

Online video streaming using HTTP Adaptive Streaming (HAS) is becoming the most popular content delivery mechanism for media services. Network and content providers would like to ensure a high degree of video Quality of Experience (QoE) for their end-users. However, traditional network-level metrics do not necessarily reflect the end-users' true perception of delivered content.We introduce an in-network QoE measurement framework (IQMF) that provides QoE monitoring for HAS streams as a service. The framework leverages Software Defined Networking for its control plane functionality to streamline non-intrusive quality monitoring and to offer a closed control loop for QoE-aware service management. IQMF adopts two specifically designed QoE metrics to capture the user experience of HAS streams with respect to video fidelity and switching impact. Finally, we used a pan-European SDN testbed to demonstrate how IQMF can be used as a foundation for in-network QoE measurement and service optimisation.
Original languageEnglish
Title of host publicationCNTCV 2015: 2nd workshop on communication & networking techniques for contemporary video 2015
PublisherIEEE
ISBN (Electronic)978-1-4673-7131-5
DOIs
Publication statusPublished - 6 Aug 2015
EventCNTCV 2015: 2nd Workshop on Communication & Networking Techniques for Contemporary Video 2015 - Hong Kong, China
Duration: 26 Apr 20151 May 2015
https://ieeexplore.ieee.org/document/7179285

Conference

ConferenceCNTCV 2015: 2nd Workshop on Communication & Networking Techniques for Contemporary Video 2015
CountryChina
CityHong Kong
Period26/04/151/05/15
Internet address

Fingerprint

HTTP
Monitoring
Video streaming
Testbeds
Software defined networking

Bibliographical note

© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Keywords

  • Streaming media
  • Quality assessment
  • Video recording
  • Bit rate
  • Switches
  • Monitoring

Cite this

Farshad, A., Georgopoulos, P., Broadbent, M., Mu, M., & Race, N. (2015). Leveraging SDN to provide an in-network QoE measurement framework. In CNTCV 2015: 2nd workshop on communication & networking techniques for contemporary video 2015 IEEE. https://doi.org/10.1109/INFCOMW.2015.7179391
Farshad, Arsham ; Georgopoulos, Panagiotis ; Broadbent, Matthew ; Mu, Mu ; Race, Nicholas. / Leveraging SDN to provide an in-network QoE measurement framework. CNTCV 2015: 2nd workshop on communication & networking techniques for contemporary video 2015. IEEE, 2015.
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title = "Leveraging SDN to provide an in-network QoE measurement framework",
abstract = "Online video streaming using HTTP Adaptive Streaming (HAS) is becoming the most popular content delivery mechanism for media services. Network and content providers would like to ensure a high degree of video Quality of Experience (QoE) for their end-users. However, traditional network-level metrics do not necessarily reflect the end-users' true perception of delivered content.We introduce an in-network QoE measurement framework (IQMF) that provides QoE monitoring for HAS streams as a service. The framework leverages Software Defined Networking for its control plane functionality to streamline non-intrusive quality monitoring and to offer a closed control loop for QoE-aware service management. IQMF adopts two specifically designed QoE metrics to capture the user experience of HAS streams with respect to video fidelity and switching impact. Finally, we used a pan-European SDN testbed to demonstrate how IQMF can be used as a foundation for in-network QoE measurement and service optimisation.",
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Farshad, A, Georgopoulos, P, Broadbent, M, Mu, M & Race, N 2015, Leveraging SDN to provide an in-network QoE measurement framework. in CNTCV 2015: 2nd workshop on communication & networking techniques for contemporary video 2015. IEEE, CNTCV 2015: 2nd Workshop on Communication & Networking Techniques for Contemporary Video 2015 , Hong Kong, China, 26/04/15. https://doi.org/10.1109/INFCOMW.2015.7179391

Leveraging SDN to provide an in-network QoE measurement framework. / Farshad, Arsham; Georgopoulos, Panagiotis; Broadbent, Matthew; Mu, Mu; Race, Nicholas.

CNTCV 2015: 2nd workshop on communication & networking techniques for contemporary video 2015. IEEE, 2015.

Research output: Contribution to Book/Report typesConference contribution

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N2 - Online video streaming using HTTP Adaptive Streaming (HAS) is becoming the most popular content delivery mechanism for media services. Network and content providers would like to ensure a high degree of video Quality of Experience (QoE) for their end-users. However, traditional network-level metrics do not necessarily reflect the end-users' true perception of delivered content.We introduce an in-network QoE measurement framework (IQMF) that provides QoE monitoring for HAS streams as a service. The framework leverages Software Defined Networking for its control plane functionality to streamline non-intrusive quality monitoring and to offer a closed control loop for QoE-aware service management. IQMF adopts two specifically designed QoE metrics to capture the user experience of HAS streams with respect to video fidelity and switching impact. Finally, we used a pan-European SDN testbed to demonstrate how IQMF can be used as a foundation for in-network QoE measurement and service optimisation.

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Farshad A, Georgopoulos P, Broadbent M, Mu M, Race N. Leveraging SDN to provide an in-network QoE measurement framework. In CNTCV 2015: 2nd workshop on communication & networking techniques for contemporary video 2015. IEEE. 2015 https://doi.org/10.1109/INFCOMW.2015.7179391