The field of edge computing is advancing quickly, with new algorithms, architectures, and use cases emerging regularly. Intelligent mobile edge computing includes various domains--such as IoT, AI, and telecommunications--making it essential to provide a holistic view that bridges these areas for researchers and practitioners. There is a growing need for practical insights and case studies that illustrate how mobile edge computing can be effectively implemented in industries like healthcare, smart cities, and manufacturing. This book aims to tackle real-world challenges, offering strategies for deployment, network structure, resource optimization, beamforming, and so on.
This book explores the potential of mobile edge computing in wireless intelligent and sensing environments. This comprehensive guide delves into cutting-edge technologies that enable computing resource optimization and decision-making at the edge or cloud, reducing latency and bandwidth consumption. It provides a comprehensive and accessible resource that addresses the rapidly mobile edge computing related technologies. As the demand for real-time data processing and low-latency applications grows for future 6G wireless communications, this book can help readers to understand the implications, challenges, and opportunities presented by these innovations.
Wanming Hao, received the Ph. D. degree from School of Electrical and Electronic Engineering, Kyushu University, Japan, in 2018. He worked as a Research Fellow at the 5G Innovation Center, Institute of Communication Systems, University of Surrey, U.K. Now, he is an Associate Professor at the School of Electrical and Information Engineering, Zhengzhou University, China. His research interests include mobile edge computing, RIS, and mmWave. He is a Highly Cited Researcher and on the World's Top 2% Scientists list by Stanford University. He has published more then 100+ journal and conference papers. He is the Associate Editor of IEEE O-JCS and IEEE TVT.
Fuhui Zhou is currently a Full Professor at Nanjing University of Aeronautics and Astronautics. His research interests focus on cognitive intelligence, knowledge graph, edge computing, and resource allocation. He was awarded as IEEE ComSoc Asia-Pacific Outstanding Young Researcher and Young Elite Scientist Award of China and URSI GASS Young Scientist. He is a Highly Cited Researcher and on the World's Top 2% Scientists list by Stanford University. He has published more then 200+ journal and conference papers. He has served as an Editor of IEEE Transactions on Communications, IEEE Systems Journal, IEEE Wireless Communications Letters, IEEE Access and Physical Communications.
Zihan Gao received her B.Sc. degree in Communication Engineering from the School of Information Engineering, Zhengzhou University, Zhengzhou, China in 2016 and received the MSc. degree in signal processing and communication from the University of Edinburgh, UK in 2018. She received a Ph.D. degree from the School of Electrical and Information Engineering, Zhengzhou University, China. Now, she is working in the School of Computer and Information Engineering, at Henan University of Economics and Law. Her research interests include mobile cloud computing, cognitive radio networks, and reinforcement learning.
Nana Li received the B.S. degree from Hunan University of Technology, Zhuzhou, China, in 2018. She obtained her Ph.D. degree in information and communication engineering with Zhengzhou University, Zhengzhou, China, in 2024 Her research interests include mobile edge computing and intelligent reflecting surface.
