Applying Big Data, Machine Learning, and SDN/NFV to 5G Traffic Clustering, Forecasting, and Management

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

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

15 Scopus citations

Abstract

Traffic clustering, forecasting, and management play a crucial role in improving network efficiency, network quality, load balancing (LB), and energy saving of mobile networks. Especially, in 5G networks, a dense heterogeneous architecture of various types of cells (macro cells and small cells) make traffic management become more complicated. Moreover, investigating and understanding traffic patterns of a huge number of cells are challenging issues, but valuable for network operators. On the other hand, big data, machine learning (ML), software-defined network (SDN), and network functions virtualization (NFV) have recently been proposed as emerging technologies and the necessary tools for empowering the SON of 5G to address the intensive computation and optimization issues. In this study, the authors applied those technologies to build a practical and powerful framework for clustering, forecasting, and managing traffic behaviors for a huge number of base stations with different statistical traffic characteristics of different types of cells (GSM, 3G, 4G). Besides, several applications based on traffic forecasting were also introduced. Finally, the performance of the proposed models was evaluated by applying them to a real dataset that collected traffic KPIs (key performance indicators) of more than 6000 cells of a real network during the years, 2016 and 2017.

Original languageEnglish
Title of host publication2018 4th IEEE Conference on Network Softwarization and Workshops, NetSoft 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages207-211
Number of pages5
ISBN (Print)9781538646335
DOIs
StatePublished - 10 Sep 2018
Event4th IEEE Conference on Network Softwarization and Workshops, NetSoft 2018 - Montreal, Canada
Duration: 25 Jun 201829 Jun 2018

Publication series

Name2018 4th IEEE Conference on Network Softwarization and Workshops, NetSoft 2018

Conference

Conference4th IEEE Conference on Network Softwarization and Workshops, NetSoft 2018
CountryCanada
CityMontreal
Period25/06/1829/06/18

Keywords

  • 5G
  • Big data
  • Machine Learning
  • SDN/NFV
  • SON
  • Traffic clustering
  • Traffic forecasting

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