SDN/NFV, Machine Learning, and Big Data Driven Network Slicing for 5G

Luong Vy Le, Bao-Shuh Lin , Li Ping Tung, Do Sinh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations


5G networks are expected to be able to satisfy a variety of vertical services for mobile users, business demands, and automotive industry. Network slicing is a promising technology for 5G to provide a network as a service (NaaS) for a wide range of services that run on different virtual networks deployed on a shared network infrastructure. Moreover, the SON (self-organizing network) in 5G is expected as a significant evolution to guarantee for full intelligence, automatic, and faster management and optimization. To deal with those requirements, recently, software-defined networking (SDN), network functions virtualization (NFV), big data, and machine learning have been proposed as emerging technologies and the necessary tools for 5G, especially, for network slicing. This study aims to integrate various machine learning (ML) algorithms, big data, SDN, and NFV to build a comprehensive architecture and an experimental framework for the future SONs and network slicing. Finally, based on this framework, we successfully implemented an early state traffic classification and network slicing for mobile broadband traffic applications implemented at Broadband Mobile Lab (BML), National Chiao Tung University (NCTU).

Original languageEnglish
Title of host publicationIEEE 5G World Forum, 5GWF 2018 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538649824
StatePublished - 31 Oct 2018
Event1st IEEE 5G World Forum, 5GWF 2018 - Santa Clara, United States
Duration: 9 Jul 201811 Jul 2018

Publication series

NameIEEE 5G World Forum, 5GWF 2018 - Conference Proceedings


Conference1st IEEE 5G World Forum, 5GWF 2018
CountryUnited States
CitySanta Clara


  • 5G
  • Application identification.
  • Big Data
  • Machine Learning
  • Network slicing
  • SON

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