Please accept our sincere apologies if you receive multiple copies of this CFP.

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CALL FOR PAPERS - Manuscript submission before 15 April, extended

IEEE Open Journal of Vehicular Technology (OJVT)

special issue on

Distributed Intelligence for Future Vehicular Networks

https://vtsociety.org/wp-content/uploads/2020/11/OJVT-SI-CFP-20201107.pdf

(note: deadline extended to 15 April)

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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



IMPORTANT DATES

Manuscript submission: 15 April 2021
Notification of Authors: 15 June 2021
Revised Manuscripts Due: 30 June 2021
Final Editorial Decision: 15 July 2021
Final Papers Due: 30 July 2021
Publication Date: Fourth Quarter 2021

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SUBMISSION GUIDELINES

Manuscripts need to be submitted through the journal’s submission website at https://mc.manuscriptcentral.com/ojvt. You will need to register and then proceed to the author center. On the manuscript details page, please select “Special Issue - Distributed Intelligence for Future Vehicular Networks” from the type list.

No page limits, no over-length page charges, with a processing fee of USD $1750 per article, with discounts for IEEE members / IEEE VTS members. Please refer to the OJVT website for more information: https://vtsociety.org/learn/ieee-open-journal-of-vehicular-technology-ojvt/

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GUEST EDITORS

Zhu Han (University of Houston, US), Email: zhan2@uh.edu

Yang Zhang (Wuhan University of Technology, China), Email: yangzhang@whut.edu.cn

Zehui Xiong (Singapore University of Technology and Design, Singapore), Email: Zehui_xiong@sutd.edu.sg

Dinh Thai Hoang (University of Technology Sydney, Australia), Email: hoang.dinh@uts.edu.au

Mérouane Debbah (CentraleSupélec, Huawei France R&D, France), Email: merouane.debbah@centralesupelec.fr

Dusit Niyato (Nanyang Technological University, Singapore), Email: dniyato@ntu.edu.sg


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Please kindly contact Yang Zhang (yangzhang@whut.edu.cn) for any technical issues / information during the submission process.