AI-enabled communication protocols for vehicular ad hoc networks (VANETs): fundamentals and future challenges
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Abstract
Vehicular ad hoc networks (VANETs) merging with 5G technology will result in cognitive transportation system. As for optimal data transmission, 5G is utilized to reduce the burden on mobile networks. VANETs are emerged from mobile ad hoc networks. Parameters like distance, nodes movement, mobility models, link stability, and speed need to be improved accordingly. This survey study mainly focuses on the types of ad hoc networks, comparative analysis of wireless communication technologies, and routing protocols for VANETs. Also, different techniques like machine learning, deep learning, metaheuristic search algorithms, and optimization techniques are discussed to enhance the capabilities of VANETs. In addition, for secure communication in VANETs, intrusion detection systems are studied to identify different security attacks.
Abstract
Vehicular ad hoc networks (VANETs) merging with 5G technology will result in cognitive transportation system. As for optimal data transmission, 5G is utilized to reduce the burden on mobile networks. VANETs are emerged from mobile ad hoc networks. Parameters like distance, nodes movement, mobility models, link stability, and speed need to be improved accordingly. This survey study mainly focuses on the types of ad hoc networks, comparative analysis of wireless communication technologies, and routing protocols for VANETs. Also, different techniques like machine learning, deep learning, metaheuristic search algorithms, and optimization techniques are discussed to enhance the capabilities of VANETs. In addition, for secure communication in VANETs, intrusion detection systems are studied to identify different security attacks.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- About the editors IX
- Toward the Internet of vehicles: challenges and solutions 1
- AI-enabled communication protocols for vehicular ad hoc networks (VANETs): fundamentals and future challenges 19
- Applying machine learning algorithms to improve intrusion detection system in IoV 35
- Auto steering control in a self-driving car using deep learning model 51
- Semantic segmentation with transfer learning for self-driving cars 63
- An improved anomaly detection process in smart vehicle using a supervised ensemble-learning framework 83
- Survey on AI-based IoT and drone-equipped smart agriculture 101
- General parametric of four hybrid microconcentrator photovoltaic systems for electric car charging station 115
- The influence of social media in improving supply chain intelligence using deep learning 139
- Index 153
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- About the editors IX
- Toward the Internet of vehicles: challenges and solutions 1
- AI-enabled communication protocols for vehicular ad hoc networks (VANETs): fundamentals and future challenges 19
- Applying machine learning algorithms to improve intrusion detection system in IoV 35
- Auto steering control in a self-driving car using deep learning model 51
- Semantic segmentation with transfer learning for self-driving cars 63
- An improved anomaly detection process in smart vehicle using a supervised ensemble-learning framework 83
- Survey on AI-based IoT and drone-equipped smart agriculture 101
- General parametric of four hybrid microconcentrator photovoltaic systems for electric car charging station 115
- The influence of social media in improving supply chain intelligence using deep learning 139
- Index 153
