Edge Computing: Systems and Applications

Preface

Over the past decade, edge computing’s rapid evolution has fundamentally transformed how data is processed, stored, and utilized across multiple industry sectors, such as smart manufacturing, healthcare, smart cities, and transportation. As a critical enabler of technologies such as the Internet of Things (IoT), autonomous systems, and real-time analytics, edge computing has progressed from a nascent concept to widespread adoption. Despite this remarkable growth, there remains a lack of educational resources dedicated to equipping the next generation of the workforce with the knowledge and skills needed to advance edge computing further.

This book was motivated to address that gap, offering a comprehensive introduction to edge computing’s principles, architectures, applications, and challenges. It aims to provide readers, ranging from students to professionals, with a solid foundation in edge computing, enabling them to understand its current state, tackle its challenges, and drive its development. By bridging theory and practice, this book aspires to inspire innovation, foster collaboration, and promote growth in this rapidly evolving field.

Designed as both a textbook and a reference guide, this book includes practice questions, course projects, and curated reading materials for each chapter to enhance learning. Readers with diverse interests and goals can navigate directly to the chapters most relevant to them, making the book a flexible resource for students, educators, researchers, and professionals alike.

The book is structured into nine chapters. Chapter 1 introduces the importance of edge computing, providing its background and evolutionary history. Chapter 2 lays the groundwork, covering fundamental principles, models, and technologies that underpin edge computing. Chapter 3 delves into the architecture and components of edge computing, including infrastructure and collaborative models. Chapter 4 transitions into edge intelligence by highlighting the integration of artificial intelligence with edge computing. Chapter 5 addresses key challenges such as programmability, resource optimization, and security, while proposing potential solutions. Chapter 6 looks to the future, discussing emerging paradigms like sky computing, 6G, and edge computing in space exploration. Chapter 7 provides practical insights through real-world case studies, illustrating edge computing’s impact on industries such as manufacturing, healthcare, smart cities, and more. Chapter 8 examines privacy concerns and the digital divide, exploring biases, their impacts, and mitigation strategies in edge computing. Chapter 9 concludes the book.

This endeavor would not have been possible without the unwavering dedication and expertise of the team behind this book. We are deeply grateful to the contributors, editors, and reviewers whose insights and hard work shaped this book. In particular, we extend our heartfelt thanks to Dr. Haihua Chen (University of North Texas), Dr. Shihong Hu (Hohai University), Dr. Sidi Lu (William & Marry), Dr. Kewei Sha (University of North Texas), Dr. Qingyang Zhang (Anhui University), Dr. Xingzhou Zhang (Chinese Academy of Science), and PhD students Komala Subramanyam Cherukuri (University of North Texas), Yuankai He (University of Delaware), Shaibal Saha (Oakland University), Qiren Wang (University of Delaware), Yichen Xia (University of Delaware), and Yongtao Yao (University of Delaware).

To all the readers, we hope you enjoy reading the book and find the book serves as both a resource and an inspiration as you explore the exciting world of edge computing.