Guest Editors
Prof. Qiong Wu, Jiangnan University, China
Prof. Ke Xiong, Beijing Jiaotong University, China
Prof. Yunquan Dong, Nanjing University of Information Science & Technology, China
Prof. Zhengchuan Chen, Chongqing University, China
Summary
The Internet of Things (IoT) and the Internet of Vehicles (IoV) have extensive potential applications in various fields, such as smart healthcare, smart industry, intelligent agriculture, and transportation. Despite these promising prospects, designing productive IoT and IoV systems involves several major challenges. For example, communication networks must be fault-resistant in order to achieve reliable information distribution; data collection, processing and transmission may incur excessive delay and data loss, which would reduce the reliability of IoT and IoV; ensuring the security and privacy of users in heterogeneous IoT and IoV is not straightforward. The newest developments including edge computing, 5G communication technologies, reinforcement learning, federated learning, and other technologies provide effective solutions to these problems.
The goal of this Special Issue is to focus on security, reliability, resource optimization, sensor topology optimization, and sensor information collection and analysis in IoT and IoV systems. We particularly welcome the achievements yielded by the investigation of novel communication and networking technologies in IoT and IoV, such as ultra-reliable and low-latency communication, intelligent communication network collaboration, communication performance analysis and optimization. This Research Topic invites novel contributions from academia and industrial sectors to research, develop and investigate the opportunities, challenges, and solutions related to the implementation of innovative architectures, methods, approaches, and technologies for IoT and IoV.
Keywords
Ultra-reliable and low-latency communications (URLLC) for IoT and IoV.
New communication technologies and other applications for IoT and IoV.
Modeling routing and MAC protocols for IoT and IoV.
Federated-learning-based security and privacy issues for IoT and IoV.
Machine-learning-based resource management for IoT and IoV.
Reinforcement learning for IoT and IoV.
Artificial-intelligence-assisted data collection and analysis for IoT and IoV.
Collaborative communication and self-organization technologies for IoT and IoV.
Sensing for IoT and IoV.
Positioning for IoT and IoV.
Cloud computing and edge computing for IoT and IoV.
Emerging applications for IoT and IoV.
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