Research Article
Flash Crowd Management in Beyond 5G Systems
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@INPROCEEDINGS{10.1007/978-3-030-78459-1_4, author={Valentin Rakovic and Hristijan Gjoreski and Marija Poposka and Daniel Denkovski and Liljana Gavrilovska}, title={Flash Crowd Management in Beyond 5G Systems}, proceedings={Future Access Enablers for Ubiquitous and Intelligent Infrastructures. 5th EAI International Conference, FABULOUS 2021, Virtual Event, May 6--7, 2021, Proceedings}, proceedings_a={FABULOUS}, year={2021}, month={6}, keywords={Flash crowd Radio virtualization Machine learning}, doi={10.1007/978-3-030-78459-1_4} }- Valentin Rakovic
Hristijan Gjoreski
Marija Poposka
Daniel Denkovski
Liljana Gavrilovska
Year: 2021
Flash Crowd Management in Beyond 5G Systems
FABULOUS
Springer
DOI: 10.1007/978-3-030-78459-1_4
Abstract
Wireless network (radio) virtualization and its synergy with ML/AI-based technologies is a novel concept that can efficiently address problems of legacy networks, such as flash crowds. This paper discusses the integration aspects of intelligence-based technologies with Sate-of-the-Art end-to-end reconfigurable, flexible and scalable network architecture, capable of handling demands in flash crowd scenarios. The presented results, demonstrate that advanced solutions based on ML can significantly improve the network proactivity and adaptivity by reliably predicting flash crowd scenarios. The results also show that in case of low dataset fidelity, conventional statistical models are a more suitable option.
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