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  4. System Failure Prediction within Software 5G Core Networks using Time Series Forecasting
 
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2021
Conference Paper
Titel

System Failure Prediction within Software 5G Core Networks using Time Series Forecasting

Abstract
5G network is very flexible because of the two concepts Network Functions Virtualization (NFV) and the Software Defined Networks (SDN). There are various use cases for 5G technology and for different cases different configuration of the network will be needed. 5G Technology will bring intelligence within the network. The ability to support massive connectivity across diverse devices will result in enormous data volume within the 5G network. Continuous monitoring and traffic log analysis in such a complex architecture will not be sufficient to ensure availability and reliability within the network. The integration of data analytics within the 5G network can leverage the potential of automation. By introducing automation in the monitoring process better Quality of Services (QoS) can be achieved and analysing the network traffic load for better bandwidth utilization within the network. This article proposes a solution to integrate time series based analytics with 5G core and predicting any threats within the system which can lead to system failure. To validate the proposal Fraunhofer FOKUS Open5GCore toolkit is used.
Author(s)
Chakrabourty, Pousaly
Corici, Marius
Magedanz, Thomas
Hauptwerk
IEEE International Conference on Communications Workshops (ICC Workshops) 2021. Proceedings
Konferenz
International Conference on Communications (ICC) 2021
DOI
10.1109/ICCWorkshops50388.2021.9473530
File(s)
N-638319.pdf (680.83 KB)
Language
English
google-scholar
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
Tags
  • machine learning

  • time series forecasting

  • 3GPP 5G Core

  • Open5GCore toolkit

  • failure prediction

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