Data-Driven Intelligence in Wireless Networks

Auteur

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.

Texte du rabat

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 AI.

Contenu

Part 1: Data-Driven Wireless Networks: Design and Applications

Chapter 1: Data-Driven Wireless Networks: A Perspective

Chapter 2: A Collaborative Data-Driven Intelligence for Future Wireless Networks

Chapter 3: Federated learning Technique in Enabling Data-driven Design for Wireless Communication

Chapter 4: Application of Wireless Network Data Driver using Edge Computing and Deep Learning in Intelligent Transportation

Chapter 5: Data-Driven Agriculture and the Role of AI in Smart Farming

Part II: Data-Driven Techniques and Security Issues in Wireless Networks

Chapter 6: Data-Driven Techniques and Security Issues in Wireless Network

Chapter 7: Data-Driven Techniques for Intrusion Detection in Wireless Networks

Part III: Advanced Topics in Data-Driven Intelligence for Wireless Networks

Chapter 8: Policy-based Data Analytic for Software-Defined Wireless

Chapter 9: Data-Driven Coexistence in Next-Generation Heterogeneous Cellular Networks

Chapter 10: Programming Languages, Tools, and Technique