Distributed Intelligence Empowered 6G Internet of Vehicles: Safety, Security and Applications
1Xidian University, Xi'an, China
2Virginia Tech, Blacksburg, USA
3Communication Theory Lab. School of Electrical Engineering Royal Institute of Technology (KTH), Stockholm, Sweden
4State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China
Distributed Intelligence Empowered 6G Internet of Vehicles: Safety, Security and Applications
Description
Sixth generation (6G) networks combine various sub-network together, aiming to establish a highly dynamic and intelligent system with a heterogeneous structure. With the advance of network performance in 6G, Internet of Vehicles (IoV) will be further developed whereby the fully connected vehicle-road-cloud intelligent perception and collaborative decision-making system will significantly improve the road safety, traffic efficiency, and driving experience. Nevertheless, this could introduce new security and privacy challenges into the system design. In addition, the 6G integrated space-air-ground communication system will help to realize autonomous driving in all scenarios; the intelligent mobile edge computing system will promote the large-scale application of low-cost intelligent vehicles; the digital twin system covering all areas will realize data-driven intelligent city-level traffic management; the blockchain-enabled distributed system will provide distributed trust and security concerns during the data sharing and transactions dealing around vehicles.
To achieve these goals, strict and customized quality-of-service requirements should be satisfied. Therefore, the enormous amount of IoV data needs to be effectively processed, and the diversified resources, e.g., communication, computing, and storage resources should be flexibly managed in different granularities. To meet the diversified requirements of the above-mentioned systems, Edge Intelligence (AI) is a promising technique to address these issues. On the other hand, because of the limitation of the centralized system on time-sensitive analysis, low bandwidth transmission, cost constraint scenario, and privacy protection applications, there exists an urgent demand for decentralized training and learning technologies.
This Special Issue aims to collect original research and review articles on the use of distributed intelligent technologies in the development of safety-guaranteed, security-enhanced, and diversify QoS-satisfied applications for 6G IoV.
Potential topics include but are not limited to the following:
- Scalable/hybrid systems using distributed intelligence for secure 6G IoV
- Novel cloud/edge/end cooperated architecture for secure 6G IoV
- Novel mobile/multi-access edge computing skills for secure 6G IoV
- Vehicular digital-twin system design with distributed intelligence
- Distributed privacy-protected learning methods and algorithms for 6G IoV
- Blockchain-enabled security enhancement using distributed intelligence for 6G IoV
- Space-Air-Ground integrated services using Distributed intelligence for secure 6G IoV
- Safe 6G IoV with Distributed intelligence for cooperated sensing
- Safe 6G IoV with Distributed intelligence for cooperated decision making
- Safe 6G IoV with Distributed intelligence for cooperated control and action
- Novel intelligent model for emerging network management, service, and automation in 6G IoV