QoE-Driven, Energy-Aware Video Adaptation in 5G Networks: The SELFNET Self-Optimisation Use Case

• Published in: International journal of distributed sensor networks Vol. 2016; no. 1; p. 7829305
• Main Authors: Nightingale, James, Wang, Qi, Alcaraz Calero, Jose M., Chirivella-Perez, Enrique, Ulbricht, Marian, Alonso-López, Jesús A., Preto, Ricardo, Batista, Tiago, Teixeira, Tiago, Barros, Maria Joao, Reinsch, Christiane
• Format: Journal Article
• Language: English
• Published: London, England Hindawi Publishing Corporation 01-01-2016; SAGE Publications; Sage Publications Ltd. (UK); Sage Publications Ltd; Hindawi - SAGE Publishing
• Subjects: Applied research; Decisions; Energy management; Fifth generation wireless technology; Management; Networks; Quality of service (Computer networks); Quality of service architectures; Streaming media; Traffic engineering; Traffic flow; Video transmission
• ISSN: 1550-1329; 1550-1477; 1550-1477
• DOI: 10.1155/2016/7829305

Sharp increase of video traffic is expected to account for the majority of traffic in future 5G networks. This paper introduces the SELFNET 5G project and describes the video streaming use case that will be used to demonstrate the self-optimising capabilities of SELFNET’s autonomic network management framework. SELFNET’s framework will provide an advanced self-organizing network (SON) underpinned by seamless integration of Software Defined Networking (SDN), Network Function Virtualization (NFV), and network intelligence. The self-optimisation video streaming use case is going beyond traditional quality of service approaches to network management. A set of monitoring and analysis components will facilitate a user-oriented, quality of experience (QoE) and energy-aware approach. Firstly, novel SON-Sensors will monitor both traditional network state metrics and new video and energy related metrics. The combination of these low level metrics provides highly innovative health of network (HoN) composite metrics. HoN composite metrics are processed via autonomous decisions not only maintaining but also proactively optimising users’ video QoE while minimising the end-to-end energy consumption of the 5G network. This contribution provided a detailed technical overview of this ambitious use case.