User-Oriented Virtual Mobile Network Resource Management for Vehicle Communications

• Published in: IEEE transactions on intelligent transportation systems Vol. 22; no. 6; pp. 3521 - 3532
• Main Authors: Lu, Huimin, Zhang, Yin, Li, Yujie, Jiang, Chi, Abbas, Haider
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-06-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; artificial intelligence; data analytics; Industries; Network architecture; network optimization; Optimization; Quality of service; Resource management; Resource utilization; User experience; Vehicle networks; Virtual networks; Voice communication
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2020.2991766

Currently, advanced communications and networks greatly enhance user experiences and have a major impact on all aspects of people's lifestyles in terms of work, society, and the economy. However improving competitiveness and sustainable vehicle network services, such as higher user experience, considerable resource utilization and effective personalized services, is a great challenge. Addressing these issues, this paper proposes a virtual network resource management based on user behavior to further optimize the existing vehicle communications. In particular, ensemble learning is implemented in the proposed scheme to predict the user's voice call duration and traffic usage for supporting user-centric mobile services optimization. Sufficient experiments show that the proposed scheme can significantly improve the quality of services and experiences and that it provides a novel idea for optimizing vehicle networks.