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To meet the challenging key performance indicators of the fifth generation (5G) system, the network infrastructure becomes more heterogeneous and complex. This will bring a high pressure on the reduction of OPEX and the improvement of the user experience. Hence, shifting today’s manual and semi-automatic network management into an autonomic and intelligent framework will play a vital role in the upcoming 5G system. Based on the cutting-edge technologies, such as Software-Defined Networking and Network Function Virtualization, a novel management framework upon the software-defined and Virtualized Network is proposed by EU H2020 SELFNET project. In the paper, the reference architecture of SELFNET, which is divided into Infrastructure Layer, Virtualized Network Layer, SON Control Layer, SON Autonomic Layer, NFV Orchestration and Management Layer, and Access Layer, will be presented. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]