Big Data and Machine Learning Driven Open5GMEC for Vehicular Communications

Authors

  • Luong Vy Le College of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan
  • Sinh Do Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan
  • Bao-Shuh Paul 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

DOI:

https://doi.org/10.14738/tnc.65.5410

Keywords:

Vehicular communication, V2X, Automotive driving, SDN/NFV, Machine Learning, Big Data, 5G, MEC

Abstract

Mobile Edge Computing (MEC) is an emerging technology and an essential component of 5G networks to bring cloud services closer to users. That means data collection, storage, processing, computing, communication, and network control are implemented at network edges. MEC is expected to be able to satisfy a variety of delay-sensitive services and applications. On the other hand, the development of vehicles to everything (V2X) communication brings many requirements to future networks to guarantee full intelligence, automatic, and faster computation, management, and optimization to fulfill network QoS (quality of service) and QoE (quality of experience). To deal with those requirements, recently, software-defined networking (SDN), network functions virtualization (NFV), big data, and machine learning (ML) have been proposed as emerging technologies and the necessary tools for MEC and vehicular networks. This study aims to integrate those technologies to build a comprehensive architecture and an experimental framework for future 5G MEC called Open5GMEC. Moreover, the authors analyzed challenges and proposed relevant solutions for future vehicular communications in 5G networks.  Finally, based on this framework, we successfully implemented several powerful ML-based applications for V2X such as object detection, network slicing, and migration services, which are executed at Broadband Mobile Lab (BML), National Chiao Tung University (NCTU).

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

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.

Bao-Shuh Paul 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.

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Published

2018-11-04

How to Cite

Le, L. V., Do, S., Lin, B.-S. P., & Tung, L.-P. (2018). Big Data and Machine Learning Driven Open5GMEC for Vehicular Communications. Transactions on Networks and Communications, 6(5), 103. https://doi.org/10.14738/tnc.65.5410