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    Data-Driven Intelligence in Wireless Networks

    Concepts, Solutions, and Applications

    AvMuhammad Khalil Afzal,Muhammad Ateeq

    Häftad, Engelska, 2024

    723 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    This book highlights the importance of data-driven techniques to solve wireless communication problems. It presents a number of problems (e.g., related to performance, security, and social networking), and provides solutions using various data-driven techniques, including machine learning, deep learning, federated learning, and artificial intelligence.This book details wireless communication problems that can be solved by data-driven solutions. It presents a generalized approach toward solving problems using specific data-driven techniques. The book also develops a taxonomy of problems according to the type of solution presented and includes several case studies that examine data-driven solutions for issues such as quality of service (QoS) in heterogeneous wireless networks, 5G/6G networks, and security in wireless networks. The target audience of this book includes professionals, researchers, professors, and students working in the field of networking, communications, machine learning, and related fields.

    Produktinformation

    • Utgivningsdatum:2024-12-19
    • Mått:156 x 234 x 18 mm
    • Vikt:490 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:252
    • Förlag:Taylor & Francis Ltd
    • ISBN:9781032107738

    Utforska kategorier

    • Energiteknik inom Naturvetenskap och teknik
    • Systemvetenskap och AI inom Data och IT
    • Nätverk och kommunikation inom Data och IT

    Mer om författaren

    MUHAMMAD KHALIL AFZAL (SM'16) received his MCS and M.S degrees in Computer Science from COMSATS Institute of Information Technology, Wah Campus, Pakistan in 2004 and 2007, respectively, and his PhD. degree from the Department of Information and Communication Engineering, Yeungnam University, South Korea, in December 2014. He has several research projects funded by the Higher Education Commission (HEC), Pakistan, and National Grassroots ICT Research Initiative, Ignite. His research interests include wireless sensor networks, ad hoc networks, data-driven intelligence in wireless networks, smart cities, 5G, and IoT. MUHAMMAD ATEEQ received his bachelor’s degree from Bahauddin Zakariya University at Multan, in 2005, and his MS and Ph.D. degree from COMSATS University Islamabad, Wah Campus, in 2007 and 2021, respectively. He has been in academia for the last 15 years. He is currently an Assistant Professor of Computer Science with The Islamia University of Bahawalpur. His research interests include using data-driven techniques to improve the quality of service in wireless communication. SUNG WON KIM received his B.S. and M.S. degrees from the Department of Control and Instrumentation Engineering, Seoul National University, South Korea, in 1990 and 1992, respectively, and a Ph.D. degree from the School of Electrical Engineering and Computer Sciences, Seoul National University, in 2002. From 1992 to 2001, he was a researcher with the Research and Development Center, LG Electronics, South Korea. From 2001 to 2003, he was a researcher with the Research and Development Center, AL Tech, South Korea. From 2003 to 2005, he was a postdoctoral researcher with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA. In 2005, he joined the Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, South Korea, where he is currently a Professor. His research interests include resource management, wireless networks, mobile networks, performance evaluation, and machine learning.

    Innehållsförteckning

    • Part 1: Data-Driven Wireless Networks: Design and ApplicationsChapter 1: Data-Driven Wireless Networks: A PerspectiveChapter 2: A Collaborative Data-Driven Intelligence for Future Wireless NetworksChapter 3: Federated learning Technique in Enabling Data-driven Design for Wireless CommunicationChapter 4: Application of Wireless Network Data Driver using Edge Computing and Deep Learning in Intelligent TransportationChapter 5: Data-Driven Agriculture and the Role of AI in Smart FarmingPart II: Data-Driven Techniques and Security Issues in Wireless NetworksChapter 6: Data-Driven Techniques and Security Issues in Wireless NetworkChapter 7: Data-Driven Techniques for Intrusion Detection in Wireless NetworksPart III: Advanced Topics in Data-Driven Intelligence for Wireless NetworksChapter 8: Policy-based Data Analytic for Software-Defined WirelessChapter 9: Data-Driven Coexistence in Next-Generation Heterogeneous Cellular NetworksChapter 10: Programming Languages, Tools, and Technique