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CygNet MaSoN: Analytics and Machine Learning Enabled Management System for 5G Networks
, Archana T., Deepika V., Babu Narayanan Koonampilli J.
Published in Institute of Electrical and Electronics Engineers Inc.
Pages: 94 - 96
Autonomous Networking is expected to be the mode of functioning by future networks, including 5G wireless networks. This requires intelligent data analytics and cognitive capabilities to be inherently supported as part of the networking functions, in addition to the current capabilities such as automation and correlation. This demonstration presents CygNet MaSoN, a management system that integrates multiple instances of radio access and core network functions of 5G networks supporting advanced aggregation and analytics features. This system continuously collects critical data related to network and system events, performance measurements and key performance indicators (KPIs) in real-time. It then uses the associated machine learning system to provide insights on network behaviour, estimation of service quality/experience and prediction of probable future network problems. Some of the analytics and machine learning use cases related to 5G networks and implemented on the MaSoN system are also described. © 2021 IEEE.
About the journal
JournalData powered by Typeset2021 International Conference on COMmunication Systems and NETworkS, COMSNETS 2021
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
Open AccessNo