The IEEE Open Journal on Vehicular Technology is calling for papers for the upcoming Special Section on Distributed Intelligence for Future Vehicular Networks. Manuscripts are due 15 April 2021.
Future vehicular networks have become an important component of the next generation communication technologies such as the 5G, 6G, and beyond. With the widespread use of automobile and other vehicles, research studies of future vehicular networks are urgently needed to meet the service requirements of connected vehicular users pave the way for the future development of autonomous ecosystems.
The future vehicular networks can become much more challenging than current conventional vehicular systems in terms of autonomous controls, security, and high mobility, connectivity and compatibility. With the emergence of new communication technologies and applications, the important features such as intelligent network functionalities, large-scale network deployments, and smart integrated services are greatly in demand.
Recently, machine learning (ML) and artificial intelligence (AI) enabled distributed intelligence has become a promising approach to address the aforementioned intelligent data and service challenges in the premise of large-scale decentralized vehicular networks. Distributed intelligence exploits the computational capabilities of edge components (e.g., vehicles) in future vehicular networks.
Previously unmanageable network and service problems under centralized system architectures can be efficiently solved by applying distributed approaches, e.g., crowd intelligence, multi-agent learning, and edge computing. Future vehicular networks will benefit from distributed intelligence. Therefore, it is essential to develop novel vehicular network techniques enabled by distributed intelligence, addressing various challenges related to future vehicular networks.
Topics of interest include but are not limited to:
- Distributed intelligence theories, frameworks, and algorithms for future vehicular networks
- Distributed intelligence for physical layer and infrastructure issues in future vehicular networks
- Distributed intelligence for MAC and network routing in future vehicular networks
- Distributed intelligence empowered vehicular networks in the 5G, 6G systems and beyond
- Mobile and edge intelligence frameworks and algorithms design for future vehicular networks
- Distributed and collaborative machine learning for future vehicular networks
- Distributed data privacy, security, and data persistence approaches in future vehicular networks
- Distributed intelligence enabled green and energy-efficient vehicular networks
- Market models and network economics in future vehicular networks with distributed intelligence
- Simulations, experiments, and testbeds of distributed intelligence for future vehicular networks
- Distributed intelligence in automatic driving, traffic engineering, and other related transportation studies
- Use cases and applications highlighting distributed intelligence for future vehicular networks
Manuscripts Due: 15 April 2021
First Decision: 15 June 2021
Revised Manuscripts Due: 30 June 2021
Final Editorial Decision: 15 July 2021
Final Papers Due: 30 July 2021
Publication: 4th Quarter 2021
Zhu Han, University of Houston, USA
Yang Zhang, Wuhan University of Technology, China
Zehui Xiong, Singapore University of Technology and Design, Singapore
Dinh Thai Hoang, University of Technology Sydney, Australia
Mérouane Debbah, CentraleSupélec, France
Dusit Niyato, Nanyang Technological University, Singapore