Machine Learning for Network Slicing Resource Management: A Comprehensive Survey
January 22, 2020 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: Machine Learning for Network Slicing Resource Management: A Comprehensive Survey"
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Authors
Bin Han, Hans D. Schotten
arXiv ID
2001.07974
Category
cs.NI: Networking & Internet
Cross-listed
cs.LG
Citations
28
Venue
arXiv.org
Last Checked
2 days ago
Abstract
The emerging technology of multi-tenancy network slicing is considered as an essential feature of 5G cellular networks. It provides network slices as a new type of public cloud services, and therewith increases the service flexibility and enhances the network resource efficiency. Meanwhile, it raises new challenges of network resource management. A number of various methods have been proposed over the recent past years, in which machine learning and artificial intelligence techniques are widely deployed. In this article, we provide a survey to existing approaches of network slicing resource management, with a highlight on the roles played by machine learning in them.
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