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QoESoft : QoE management architecture for softwarized 5G networks

Barakabitze, Alcardo Alex; Liyanage, Madhusanka; Hines, Andrew (2020-07-21)

 
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https://doi.org/10.1109/ICCWorkshops49005.2020.9145229

Barakabitze, Alcardo Alex
Liyanage, Madhusanka
Hines, Andrew
Institute of Electrical and Electronics Engineers
21.07.2020

A. A. Barakabitze, M. Liyanage and A. Hines, "QoESoft: QoE Management Architecture for Softwarized 5G Networks," 2020 IEEE International Conference on Communications Workshops (ICC Workshops), Dublin, Ireland, 2020, pp. 1-6, doi: 10.1109/ICCWorkshops49005.2020.9145229

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doi:https://doi.org/10.1109/ICCWorkshops49005.2020.9145229
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Abstract

For 5G network softwarization, Software Defined Networking (SDN) and Network Function Virtualization (NFV) have emerged as key technologies to enable efficient network management. 5G network virtualization will allow multiple service providers to share a single physical infrastructure offering an abstraction between the user and physical resources. As we move towards softwarized 5G networks, scalability issues, network performance with respect to Quality of Service (QoS) and Quality of Experience (QoE) and QoE-aware resource management remain less studied topics. In this paper, we adopt the SDN control logic to perform an autonomic QoE-aware resource management approach in virtualized 5G networks. We propose QoESoft, a network softwarization strategy for multimedia streaming services that performs a dynamic link and switch resources management in softwarized 5G systems. With QoESoft, we aim to improve user QoE for multimedia services through efficient monitoring and adaptation of the average load of the substrate links and switches and resource costs of mapped virtual links in 5G networks. The performance of the proposed approach is analysed in testbed environments. Preliminary results indicate that, QoESoft achieves better performance than the compared baseline approach in terms of link and switch resources utilization by 78% and 70% respectively. A video reception quality ratio metric and visual inspection on the output video both confirmed significant improvements in video QoE.

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