Cognitive Radio-based Internet of Vehicles; Architectures, Applications and Open Issues by Syed Hashim Raza Bukhari & Muhammad Maaz Rehan & Mubashir Husain Rehmani instant download
The incorporation of Cognitive Radio (CR) into the Internet of Vehicles (IoV) has emerged as the Intelligent Transportation System (ITS). It covers the aspects of cognitive radio when it provides support to IoV and the challenges that limit the performance of ITS. These issues include unreliable delivery, the dynamic topology of IoV, routing overhead, scalability, and energy, to name a few. These challenges can be considered as future research directions for a promising intelligent transportation system. Machine learning (ML) is a promising discipline of Artificial Intelligence (AI) to train the CR-based IoV system. It also covers the applications of ML techniques to the CR-IoV systems and highlights their issues and challenges. Finally, it includes an examination of ML in conjunction with Data Science applications. In CR-IoV, ML and Data Science can be collaboratively used to further enhance road safety through inter-vehicle, intra-vehicle, and beyond-vehicle networks. The channel switching and routing overhead is an important issue in CR-based IoVs. To minimize the channel switching and routing overheads, an effective scheme has been presented in Section 4 to discuss the promising solutions and performance analysis. Meanwhile, IoV communication is a time-sensitive application that requires vehicles to be synchronized. The time synchronization in IoVs has been highlighted in Section 5 to elaborate further on the critical metrics, challenges, and advancements in synchronization of IoVs. As the vehicles exchange data using wireless channels, they are at risk of being exposed to various security threats. The eavesdropping, identity exposure, message tampering, or sinkhole attack to name a few. It needs time to discuss the security issues and their countermeasures to make the CR-IoV attack resilient. The book concludes by addressing security issues and maintaining the quality of service (QoS) of the CR-based IoVs. Key features: • The architecture and applications of In
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