Edge Intelligent Computing Systems in Different Domains
This book provides a comprehensive and systematic exploration of next-generation Edge Intelligence (EI) Networks. It delves deep into the critical design considerations within this context, emphasizing the necessity for functional and dependable interactions between networking strategies and the diverse application scenarios. This should help assist to encompass a wide range of environments.This book also discusses topics such as resource optimization, incentive mechanisms, channel prediction and cutting-edge technologies, which includes digital twins and advanced machine learning techniques. It underscores the importance of functional integration to facilitate meaningful collaborations between networks and systems, while operating across heterogeneous environments aiming support novel and disruptive human-oriented services and applications. Valuable insights into the stringent requirements for intelligence capabilities, communication latency and real-time response are discussed. This characterizes the new EI era, driving the creation of comprehensive cross-domain architectural ecosystems that infuse human-like intelligence into every aspect of emerging EI systems.This book primarily targets advanced-level students as well as postdoctoral researchers, who are new to this field and are searching for a comprehensive understanding of emerging EI systems. Practitioners seeking guidance in the development and implementation of EI systems in practical contexts will also benefit from this book.
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Picano, Benedetta; Fantacci, Romano
Benedetta Picano (M20) received the B.S. degree in Computer Science, as the M.Sc. degree in Computer Engineering, from the University of Florence, where she received the Ph.D. degree in Information Engineering. She was a visiting researcher at the University of Houston. Her research fields include matching theory, nonlinear time series analysis, digital twins, microservices, resource allocation in edge and fog computing infrastructures, and machine learning. Dr. Picano currently serves as Associate Editor for IEEE Transaction on Vehicular technology and Peer-to-peer Networking and Applications journal.Romano Fantacci (LF23) is a Full Professor of Computer Networks at the University of Florence, Florence, Italy. He was elected Fellow of the IEEE in 2005 for contributions to wireless communication networks. His research focuses on wireless communication networks, Edge intelligent networks, networks modeling and analysis. He has received several awards in recognition of his research contributions. These awards include the IEE Benefactor Premium, the 2002 IEEE Distinguished Contributions to Satellite Communications Award, the 2015 IEEE WTC Recognition Award, the IEEE sister society AEIT Young Research Award, and Best Paper awards at IEEE international conferences. He has actively participated in the organization and technical program committees of numerous IEEE international conferences. Additionally, he is a member of the Editorial Board for IEEE COMSOC Technical Journals. Currently, he is an IEEE Life Fellow and holds positions on the Steering Committee of IEEE Wireless Letters and the IEEE Fellows Committee.
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