| Autor: |
Daniel Denkovski, Valentin Rakovic, Hristijan Gjoreski, Marija Poposka, Liljana Gavrilovska |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030784584 |
| DOI: |
10.1007/978-3-030-78459-1_4 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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