Computational Intelligence For Unmanned Aerial Vehicles Communication Networks
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Computational Intelligence for Unmanned Aerial Vehicles Communication Networks
This book aims to provide a vision that can combine the best of both Artificial Intelligence (AI) and communication networks for designing the deployment trajectory to establish flexible Unmanned Aerial Vehicles (UAV) communication networks.This book will discuss the major challenges that can face deploying unmanned aerial vehicles in emergent networks. It will focus on possible applications of UAV in a Smart City environment where they can be supported by Internet of Things (IoT), wireless sensor networks, as well as 5G, and beyond. This book presents the possible problems and solutions, the network integration of the UAV and compare the communication technologies to be used.This book will be a collection of original contributions regarding state of the art AI/ML based solutions in UAV communication networks which can be used for routing protocol design, transport layer optimization, user/application behaviour prediction, communication network optimization, security, and anomaly detection.
Machine Learning for Drone-Enabled IoT Networks
This book aims to explore the latest developments, challenges, and opportunities in the application of machine learning techniques to enhance the performance and efficiency of IoT networks assisted by aerial unmanned vehicles (UAVs), commonly known as drones. The book aims to include cutting edge research and development on a number of areas within the topic including but not limited to: •Machine learning algorithms for drone-enabled IoT networks •Sensing and data collection with drones for IoT applications •Data analysis and processing for IoT networks assisted by drones •Energy-efficient and scalable solutions for drone-assisted IoT networks •Security and privacy issues in drone-enabled IoT networks •Emerging trends and future directions in ML for drone-assisted IoT networks.
Wireless Ad-hoc and Sensor Networks
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.