TY - JOUR
T1 - QoE-driven, energy-aware video adaptation in 5G networks
T2 - the SELFNET self-optimisation use case
AU - Nightingale, James
AU - Wang, Qi
AU - Alcarez Calero, Jose Maria
AU - Chirvella-Perez, Enrique
AU - Ulbricht, Marian
AU - Alonso-López, Jess A.
AU - Preto, Ricardo
AU - Batista, Tiago
AU - Teixeira, Tiago
AU - Barros, Maria Joao
AU - Reinsch, Christiane
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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.
AB - 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.
KW - SELFNET
KW - energy-aware video adaptation
KW - 5G networks
UR - http://www.scopus.com/inward/record.url?scp=84958019949&partnerID=8YFLogxK
U2 - 10.1155/2016/7829305
DO - 10.1155/2016/7829305
M3 - Article
AN - SCOPUS:84958019949
SN - 1550-1329
VL - 2016
JO - International Journal of Distributed Sensor Networks
JF - International Journal of Distributed Sensor Networks
M1 - 7829305
ER -