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Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment

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Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment

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Najm, IA.; Hamoud, AK.; Lloret, J.; Bosch Roig, I. (2019). Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment. Electronics. 8(6):1-23. https://doi.org/10.3390/electronics8060607

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/155959

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Title: Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment
Author: Najm, Ihab Ahmed Hamoud, Alaa Khalaf Lloret, Jaime Bosch Roig, Ignacio
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Issued date:
Abstract:
[EN] The 5G network is a next-generation wireless form of communication and the latest mobile technology. In practice, 5G utilizes the Internet of Things (IoT) to work in high-tra_ c networks with multiple nodes/ sensors ...[+]
Subjects: Machine learning , Decision tree algorithm , IoT , WSN , C4.5 , Congestion control , 5G network
Copyrigths: Reconocimiento (by)
Source:
Electronics. (eissn: 2079-9292 )
DOI: 10.3390/electronics8060607
Publisher:
MDPI AG
Publisher version: https://doi.org/10.3390/electronics8060607
Type: Artículo

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