Wireless Ad-hoc and Sensor Networks by Singh, Pawan; Kumar, Sudesh; Gupta, Sachin Kumar;

Short description:

The book explains the power, and routing optimization in underwater sensor networks, advanced cross-layer framework, challenges, security issues in underwater sensor networks, and the use of machine learning and deep learning techniques for security implementations in wireless ad-hoc and sensor networks.

Long description:

The book presents theoretical and experimental approaches, quantitative and qualitative analyses, and simulations in wireless ad-hoc and sensor networks. It further explains the power and routing optimization in underwater sensor networks, advanced cross-layer framework, challenges and security issues in underwater sensor networks, and the use of machine learning and deep learning techniques for security implementations in wireless ad-hoc and sensor networks.

This book:

• Discusses mobile ad-hoc network routing issues and challenges with node mobility and resource limitations


• Covers the internet of vehicles, autonomous vehicle architecture, and design of heterogeneous wireless sensor networks


• Presents various technologies of ad-hoc networks, use of machine learning, and deep learning techniques in wireless sensor networks


• Illustrates recent advancements in security mechanisms for information dissemination in mobile ad-hoc networks, vehicular ad-hoc networks, flying ad-hoc networks, and autonomous vehicles


• Highlights mathematical modeling and analysis of routing protocols for ad-hoc networks and underwater sensor networks

It is primarily written for undergraduate and graduate students, researchers, and academicians in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communications engineering.

Table of Contents:

1. Orthogonal Time Frequency Space Modulation and its Application to VANETs. 2. Semantic Representation and Communication in Ad Hoc Networks Enabling Intelligent Information Exchange and Collaboration. 3. The Diverse Technology of Flying Ad-hoc Networks (FANETs): An Extensive Survey. 4. Radio Frequency Based Drone Detection and Identification: Challenges and Opportunities. 5. Learning Processes for Internet of Autonomous Vehicles, Intelligent Transportation Systems. 6. Future Envision of UAVs Elevating Human Life: ITS in Smart Cities Lensing Wireless Applications. 7. An Analysis of Clustering Algorithms for Wireless Sensor Network Applications. 8. Hybrid Metaheuristic Optimization for Energy-Efficient Routing, Clustering, and Sleep Scheduling in WSNs. 9. Selection of Relay Node using Multi-Criteria Decision Making in Wireless Body Area Network. 10. Artificial Intelligence in Wireless Communication. 11. Leveraging AI-Enabled WSNs for Environmental Monitoring: An In-depth Analysis with RF-Pose Technology. 12. Cybersecurity Challenges for Social, Ad-Hoc, and Sensor Networks in IoT. 13. Detection of DDoS Attacks Using Machine Learning in Network Environments. 14. Predictive Malware Detection in SDN-enabled Wireless Networks: A Machine Learning Approach. 15. Enhancing Healthcare Wireless Communication Security with Deep Learning-Driven IDS. 16. Blockchain-Powered Defense: Securing WSN Against DDoS Attacks with Decentralized Authentication. 17.  An Analytical Study of Classification Techniques on Car Evaluation Data using Machine Learning Algorithms in IoT. 18. Deep Dive into Underwater Sensor Networks (UWSNs): Architecture, Protocols, Challenges, Applications, and Security.