Deep Learning in Ad-Hoc Wireless Networks / edited by Gokhan ALTAN, Ipek ABASIKELEŞ TURGUT

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Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Studies in Big Data ; 172Verlag: Cham : Springer Nature Switzerland, 2025Verlag: Cham : Imprint: Springer, 2025Auflage: 1st ed. 2025Beschreibung: 1 Online-Ressource(V, 123 p. 43 illus., 34 illus. in color.)ISBN:

9783031860751

Schlagwörter:

620.00285 23

DOI: DOI: 10.1007/978-3-031-86075-1Online-Ressourcen:

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Zusammenfassung: Recent Deep Learning based Trust Solutions -- Smart Mobility Solutions: The Role of Deep Learning in Traffic Management -- A Survey of Routing Protocols for Low Power and Lossy IoT Network -- Generative Artificial Intelligence Using Deep Learning on Wireless Ad-Hoc Networks.Zusammenfassung: This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.PPN: PPN: 1924770083Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-INR | ZDB-2-SXIT

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