Changyan Yi – författare

Human digital twin (HDT) is a transformative technology poised to transform various human-centric systems. With its potential applications in personalized healthcare, HDT promises swift, precise, and efficient healthcare services through the integration of cutting-edge technologies such as artificial intelligence, data analytics, internet of things, cybersecurity as well as virtual and augmented reality. This book addresses the critical gap in the existing literature by offering a comprehensive exploration of connectivity solutions for HDT while prioritizing reliability, security, and privacy. Key topics covered include the foundational concept of HDT, its design requirements and associated challenges, edge-assisted human-to-virtual solutions, blockchain-enabled data-sharing mechanisms, and differentially private federated multi-task learning (DPFML) methodologies tailored for HDT.The discussion on the concept of HDT encompasses an overview of its applications and its specific characteristics when compared to the conventional digital twin models. In addressing the design requirements and challenges of HDT, the text delves into the complexities of securing high-quality data, ensuring ultra-reliable and low-latency communication, data privacy and integrity, while managing storage, computation and analytics. Exploring edge-assisted human-to-virtual solutions, the book also introduces a connectivity framework and details the modeling process for human-to-virtual twin connectivity. The book later presents an in-depth examination of the practical Byzantine fault tolerance framework, followed by a discussion on shard-based Byzantine fault-tolerant schemes tailored for HDT, along with analyses of latency and throughput.Furthermore, the book outlines the framework for DPFML-assisted human-to-virtual twin connectivity, accompanied by a novel consensus algorithm known as the proof of model quality. Finally, it presents future research directions aimed at addressing communication challenges hindering the seamless design and development of HDT. By offering this comprehensive exploration, the book serves as a valuable resource for researchers, practitioners, and policymakers seeking to navigate the evolving landscape of HDT and its transformative potential in various domains.

This book focuses on the integration of self-evolving Digital Twins (DTs) with wireless networks, exploring critical methodologies for dynamic twin construction and real-time service interaction. It addresses challenges posed by wireless environments, which are paramount for maintaining high-fidelity virtual replicas of physical systems. The content provides a comprehensive outline for building and managing DTs that can continuously adapt over wireless networks.The authors dedicated this book to innovative solutions for optimizing resource allocation and intelligent decision-making.  It includes game-theoretic online optimization for federated DT construction and generative artificial intelligence-aided framework for quality-of-experience driven DT service interaction. Furthermore, it shows the practical implementation of these technologies through detailed applications in intelligent vehicular networks.This book is appropriate for advanced-level students in computer science and electrical engineering, who are studying wireless communications, distributed systems, Internet of Things, and cyber-physical systems. Researchers and industry practitioners seeking to leverage DTs for innovation in smart manufacturing, intelligent transportation, and smart cities will find this book invaluable as well.