Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks

The Internet of Things (IoT) is applied to vehicular ad-hoc networks (VANETs), enhancing performance through machine learning and game theory-based vertical handoffs. Vehicle sensor networks enable monitoring and surveillance. Software-defined vehicular Ad-hoc networks are discussed theoretically.

Format: Hardback
Length: 272 pages
Publication date: 02 March 2022
Publisher: Taylor & Francis Ltd

The Internet of Things (IoT) has revolutionized the way we interact with the world, and its applications in vehicular ad-hoc networks (VANETs) are no exception. VANETs are a network of vehicles that communicate with each other in real-time, providing a wide range of benefits such as improved traffic safety, reduced congestion, and enhanced fuel efficiency.

One of the key challenges in VANETs is the efficient use of limited resources, such as bandwidth and energy. Machine learning and other computing techniques can be used to enhance the performance of VANETs by optimizing network parameters, such as route selection and packet scheduling. For example, machine learning algorithms can be used to predict traffic patterns and optimize route selection, reducing the time and energy required for communication.

Another area of interest in VANETs is game theory-based vertical handoffs. Vertical handoffs are the process of transferring a mobile device from one network to another when the current network is not able to provide the desired quality of service. Game theory-based vertical handoffs can be used to optimize the handoff process by considering the preferences of the mobile devices and the network resources.

Monitoring and surveillance of vehicles through the vehicular sensor network is another important application of IoT in VANETs. Vehicle sensors can be used to collect data about the vehicle's location, speed, and other parameters, which can be used to improve traffic management, prevent accidents, and enhance safety.

The theoretical approaches on software-defined vehicular Ad-hoc network are also an area of interest. Software-defined VANETs are a new approach to VANETs that uses software-defined networking (SDN) to manage the network. SDN allows for more flexible and scalable networks, which can be adapted to changing traffic conditions and requirements.

In conclusion, the applications of IoT in VANETs are numerous and diverse. Machine learning and other computing techniques can be used to enhance the performance of VANETs, while game theory-based vertical handoffs and monitoring and surveillance of vehicles through the vehicular sensor network can improve safety and efficiency. The theoretical approaches on software-defined vehicular Ad-hoc network are also promising for the future of VANETs.

Dimension: 234 x 156 (mm)
ISBN-13: 9780367754426