Springer - Deep Learning in Ad-Hoc Wireless Networks (172)

Explore the intersection of artificial intelligence and wireless communication with Deep Learning in Ad-Hoc Wireless Networks. Published by Springer as part of the Studies in Big Data series, this book addresses the most pressing challenges in modern network environments. It provides a deep look into how deep learning techniques can solve problems related to trust, routing, traffic management, and intrusion detection within ad-hoc networks. By integrating advanced AI models with real-world scenarios, this work offers a multidisciplinary approach that bridges theoretical insights with practical frameworks. It is designed to help readers improve network reliability, security, and efficiency through novel technological solutions. Whether you are looking to understand the mechanics of AI-driven network management or seeking new methods for securing wireless communications, this text provides the necessary technical foundation. This volume is an essential resource for researchers, engineers, and graduate students working at the cutting edge of computer science and wireless technology.