Picano, Benedetta. creator author. aut http://id.loc.gov/vocabulary/relators/aut Fantacci, Romano. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XIV, 88 p. 41 illus., 38 illus. in color. online resource. 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. Preface -- Chapter. 1. Emerging Technologies for Edge Intelligent Computing Systems -- Chapter. 2. Offloading Methodologies for Air-Ground Edge Intelligent Computing Systems -- Chapter. 3. Edge Intelligent Computing enabled Federating Learning in 6G wireless systems -- Chapter. 4. Edge Intelligent Computing in aqua environments -- Chapter. 5. Application of the Digital Twin technology in Novel Edge Intelligent Computing Systems. by Benedetta Picano, Romano Fantacci. Machine learning Wireless communication systems Mobile communication systems Computer networks  Machine Learning Wireless and Mobile Communication Computer Communication Networks Q325.5-.7 9783031494727 https://doi.org/10.1007/978-3-031-49472-7 https://doi.org/10.1007/978-3-031-49472-7 240110 20251030110918.0 978-3-031-49472-7