Advances in Underwater Communication and Networking

Syed Ali Hassan serves as a professor at the National University of Sciences and Technology (NUST), Pakistan, where he directs the Information Processing and Transmission Laboratory. His research primarily addresses theoretical aspects of wireless communications, with over 300 published articles in this filed. He obtained a PhD in electrical engineering from Georgia Institute of Technology, United States.Huma Ghafoor holds the position of assistant professor at the School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Pakistan. Until January 2019, she worked as a postdoctoral researcher at Inha University, South Korea. Her research interests include vehicular ad hoc networks, maritime networks, and underwater sensor networks. She completed her PhD in electrical engineering from the University of Ulsan, South Korea, in 2018.

• Chapter 1: The 6G internet of underwater things (6G-IoUT)Chapter 2: Software-defined underwater acoustic communicationChapter 3: Exploring the TCP/IP protocol stack in underwater networks: adapting to SDN-based 6G underwater networksChapter 4: Integrating SDN and NFV to deploy early warning systems in marine distributed underwater networks (MDUN)Chapter 5: NOMA-based underwater acoustic communicationChapter 6: Reconfigurable intelligent surfaces in challenging underwater environmentChapter 7: Routing strategies for 6G underwater communication networksChapter 8: Energy-efficient routing protocols in underwater acoustic networksChapter 9: Impact of the provision of constrained energy on UAV-enabled 6G underwater networksChapter 10: Optimizing UAV battery usage for supporting underwater acoustic networksChapter 11: Crypto-secure UASN: secure communication for the network layer of underwater acoustic sensor networksChapter 12: Secure underwater acoustic communication using 6G technologiesChapter 13: AI for securing data integrity in acoustic communication linksChapter 14: Underwater acoustic communications powered by machine learningChapter 15: Machine learning techniques for optimizing underwater acoustic signal transmissionChapter 16: Exploring the underwater acoustic environment through deep learningChapter 17: Deep learning techniques for optimizing underwater acoustic communicationChapter 18: Underwater acoustic communications powered by hybrid intelligent modelsChapter 19: AI-based seismic monitoring using underwater acoustic sensingChapter 20: Detection of tsunamis and earthquakes through underwater sensor networksChapter 21: Underwater SONAR image classification and analysis with the aid of AIChapter 22: Intelligent evaluation and categorization nof SONAR imagesChapter 23: Real-time modeling and verification of SONAR systems