Covers applications of Internet of Things (IoT) in Vehicular ad-hoc network (VANETs). Discusses use of machine learning and other computing techniques for enhancing performance of networks. Covers game theory-based vertical handoffs in Heterogeneous Wireless Networks. Examines monitoring and surveillance of vehicles through the vehicular sensor network. Discusses theoretical approaches on software-defined vehicular Ad-hoc network.

Vehicular traffic congestion and accidents remain universal issues in today's world. Due to the continued growth in the use of vehicles, optimizing traffic management operations is an immense challenge. To reduce the number of traffic accidents, improve the performance of transportation systems, enhance road safety, and protect the environment, vehicular ad-hoc networks have been introduced. Current developments in wireless communication, computing paradigms, big data, and cloud computing enable the enhancement of these networks, equipped with wireless communication capabilities and high-performance processing tools. Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks is a pivotal reference source that provides vital research on cloud and data analytic applications in intelligent transportation systems. While highlighting topics such as location routing, accident detection, and data warehousing, this publication addresses future challenges in vehicular ad-hoc networks and presents viable solutions. This book is ideally designed for researchers, computer scientists, engineers, automobile industry professionals, IT practitioners, academicians, and students seeking current research on cloud computing models in vehicular networks.

The optimization of traffic management operations has become a considerable challenge in today's global scope due to the significant increase in the number of vehicles, traffic congestions, and automobile accidents. Fortunately, there has been substantial progress in the application of intelligent computing devices to transportation processes. Vehicular ad-hoc networks (VANETs) are a specific practice that merges the connectivity of wireless technologies with smart vehicles. Despite its relevance, empirical research is lacking on the developments being made in VANETs and how certain intelligent technologies are being applied within transportation systems. IoT and Cloud Computing Advancements in Vehicular Ad-Hoc Networks provides emerging research exploring the theoretical and practical aspects of intelligent transportation systems and analyzing the modern techniques that are being applied to smart vehicles through cloud technology. Featuring coverage on a broad range of topics such as health monitoring, node localization, and fault tolerance, this book is ideally designed for network designers, developers, analysists, IT specialists, computing professionals, researchers, academics, and post-graduate students seeking current research on emerging computing concepts and developments in vehicular ad-hoc networks.

Vehicular traffic congestion and accidents remain universal issues in today's world. Due to the continued growth in the use of vehicles, optimizing traffic management operations is an immense challenge. To reduce the number of traffic accidents, improve the performance of transportation systems, enhance road safety, and protect the environment, vehicular ad-hoc networks have been introduced. Current developments in wireless communication, computing paradigms, big data, and cloud computing enable the enhancement of these networks, equipped with wireless communication capabilities and high-performance processing tools. Cloud-Based Big Data Analytics in Vehicular Ad-Hoc Networks is a pivotal reference source that provides vital research on cloud and data analytic applications in intelligent transportation systems. While highlighting topics such as location routing, accident detection, and data warehousing, this publication addresses future challenges in vehicular ad-hoc networks and presents viable solutions. This book is ideally designed for researchers, computer scientists, engineers, automobile industry professionals, IT practitioners, academicians, and students seeking current research on cloud computing models in vehicular networks.

The optimization of traffic management operations has become a considerable challenge in today's global scope due to the significant increase in the number of vehicles, traffic congestions, and automobile accidents. Fortunately, there has been substantial progress in the application of intelligent computing devices to transportation processes. Vehicular ad-hoc networks (VANETs) are a specific practice that merges the connectivity of wireless technologies with smart vehicles. Despite its relevance, empirical research is lacking on the developments being made in VANETs and how certain intelligent technologies are being applied within transportation systems. IoT and Cloud Computing Advancements in Vehicular Ad-Hoc Networks provides emerging research exploring the theoretical and practical aspects of intelligent transportation systems and analyzing the modern techniques that are being applied to smart vehicles through cloud technology. Featuring coverage on a broad range of topics such as health monitoring, node localization, and fault tolerance, this book is ideally designed for network designers, developers, analysists, IT specialists, computing professionals, researchers, academics, and post-graduate students seeking current research on emerging computing concepts and developments in vehicular ad-hoc networks.