Enhanced Handover Clustering and Forecasting Models Based on Machine Learning and Big Data

Authors

  • Luong Vy Le College of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan
  • Bao-Shuh Lin Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan Microelectronics & Information Research Center, National Chiao Tung University, Hsinchu, Taiwan
  • Li-Ping Tung Microelectronics & Information Research Center, National Chiao Tung University, Hsinchu, Taiwan
  • Sinh Do Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

DOI:

https://doi.org/10.14738/tmlai.65.5411

Keywords:

key performance indicators (KPIs), handover, Machine Learning, clustering, forecasting, SDN/NFV, SON, 5G, big data.

Abstract

In mobile networks, handover (HO) is one of the most important and complex KPIs (Key Performance Indicators), which directly affect to Quality of Service (QoS), Quality of Experience (QoE), and mobility performance. Moreover, its configuration parameters such as handover thresholds and handover neighbor lists are the key factors for implementing network optimization such as load balancing and energy saving. In a study before, the authors proposed clustering and forecasting models using ML algorithms and Time Series models to cluster, forecast, and manage the HO behavior of a huge number of cells.  In this study, on the other hand, the authors firstly investigated more network KPIs to analyze their relationship with HO KPIs, and then, proposed new clustering, forecasting, and abnormal detection models that are expected to make them much more comprehensive. Finally, the performances of the proposed models were evaluated by applying them to a real dataset collected from the HO KPIs and other KPIs of more than 6000 cells of a real network during the years, 2016 and 2017. The results showed that the study was successful in identifying the relationship among network KPIs and significantly improving the performance of the HO clustering, forecasting, abnormal detection models. Moreover, the study also introduced the integration of emerging technologies such as machine learning (ML), big data, software-defined network (SDN), and network functions virtualization (NFV) to establish a practical and powerful computing platform for future self-organizing networks (SON).

Author Biographies

Luong Vy Le, College of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan

Le Luong Vy (leluongvy.eed03g@nctu.edu.tw) received the B.S. degree in electronics and telecommunication engineering from Da Nang University of Technology, Vietnam, in 2009. From February 2009 to February 2010, He worked as a Network Optimization Engineer at Viettel Group, Vietnam. From February 2010 to 2013, He was an Operation and Maintenance Engineer at Gtel mobile, Vietnam. From February 2013 to January 2015, He was Graduate student researcher at Network Communications Laboratory, and He received his M.Sc. in Electrical Engineering and Computer Science in Jan 2015 National Chiao Tung University (NCTU), Taiwan, where He is currently working toward his Ph.D. degree. He is a researcher at SDN Technology Center, Broadband Mobile Lab（BML）, NCTU, Taiwan. His research interests include 5G network, big data, machine learning, SDN/NFV

Bao-Shuh Lin, Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan Microelectronics & Information Research Center, National Chiao Tung University, Hsinchu, Taiwan

Bao-Shuh Paul Lin received the Ph.D.  degree in computer science from the University of Illinois at   Chicago, IL, USA. He has been a Chair Professor with the Department of Computer Science and the   Chief   Director of Microelectronics and Information Research Center, National Chiao Tung University, Hsinchu, Taiwan, since 2009.  He has also been the Director of Committee of Communication Industry Development, Ministry of Economic Affairs since 2001.  He was the Vice President of Industrial Technology Research Institute (ITRI) from 2001 to 2009 and the General Director of the Information and Communications Research Laboratories (ICL), ITRI from 2001 to 2009. From 1979 to 1991, he was with Bell Labs of AT&T, Boeing, and two other high-tech firms before coming back to Taiwan in 1991.  From 1991 to 1998, he worked for ITRI and served as the Director of Computer Communications Research Division in CCL (the forerunner of ICL) and was later promoted to its Deputy General Director

Li-Ping Tung, Microelectronics & Information Research Center, National Chiao Tung University, Hsinchu, Taiwan

Dr. Li-Ping Tung received the B.Ed. degree in Information and Computer Education from National Taiwan Normal University in 2000, and Ph.D. degree in Computer Science from National Tsing Hua University in 2007. From 2007 to 2011, she joined the Institute of Information Science of Academia Sinica as Postdoctoral Fellow. She is currently an Associate Research Fellow at the Center for Open Intelligent Connectivity and SDN Technology Center of National Chiao Tung University. She also serves as an Adjunct Associate Professor at Department of Electrical and Computer Engineering, National Chiao Tung University. Her research interests are broadband wireless networks, mobile computing, and network measurements.

Sinh Do, Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

Do Sinh (dosinhuda.cs04g@nctu.edu.tw) received the B.S. degree in electronics and telecommunication engineering from Da Nang University of Technology, Vietnam, in 1997. From 1997 to 2007, He worked for the Ministry of Post and Telecommunications of Vietnam, and from 2007 to 2015 he was a lecturer in the Department of Information Technology, Dong A University, Da Nang, Vietnam. From 2003 to 2006, he also studied in the Department of Computer Science, Da Nang University of Technology. He received his M.Sc. in Computer Science in Sep 2006 Da Nang University of Technology, Vietnam. From 2015 to present, he is currently working toward his Ph.D. degree in the Department of Computer Science, National Chiao Tung University (NCTU), Taiwan. He is a researcher at SDN Technology Center, Broadband Mobile Lab, NCTU, Taiwan. His research interests include 5G network, SDN/NFV, Internet of Things, big data and machine learning.

References

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Published

2018-11-03

How to Cite

Le, L. V., Lin, B.-S., Tung, L.-P., & Do, S. (2018). Enhanced Handover Clustering and Forecasting Models Based on Machine Learning and Big Data. Transactions on Engineering and Computing Sciences, 6(5), 43. https://doi.org/10.14738/tmlai.65.5411

Issue

Vol. 6 No. 5 (2018): Transactions on Machine Learning and Artificial Intelligence

Section

Articles