**Organization of the Book**

This edited book is organized into two sections with eleven chapters. The first section on "Edge Computing" looks generally at edge computing technologies like cloud, fog, network, and swarm computing. Chapter 1, "Cloud Computing to Fog Computing: A Paradigm Shift", provides an overview of healthcare services using cloud and fog computing. Chapter 2, "Perspective Chapter: A View – Cloud-Edge Computing Technology " looks at different types of cloud computing and edge computing services. Chapter 3, "Network Powered by Computing: Next Generation of Computational Infrastructure", deals with the convergence of data communications, cloud, and high-performance computing. Chapter 4, "Perspective Chapter: Cloud Lock-in Parameters – Service Adoption and Migration", highlights technical advancements that contribute to interoperable migration in heterogeneous cloud environments. The first section ends with Chapter 5, "Swarm Computing: The Emergence of a Collective Artificial Intelligence at the Edge of Internet", which provides a comprehensive vision of the key aspects of the swarm computing paradigm.

The next section is on "Edge Computing Applications". Edge computing has been applied to control unmanned aerial vehicles (UAVs), IoT, digital epidemiology, hyperparameter tuning, 5G emerging technologies, and the Industrial Internet of Things (IIoT). In Chapter 6, "Optimal Unmanned Aerial Vehicle Control and Designs for Load Balancing in Intelligent Wireless Communication Systems", the authors propose a methodology to significantly improve the system's performance. Chapter 7, "IoT on an ESP32: Optimization Methods Regarding Battery Life and Write Speed to an SD-Card", deals with optimizing battery life methods for microcontrollers. Chapter 8, "Perspective Chapter: 5G Enabling Technologies – Revolutionizing Transport, Environment, and Health", examines how 5G technologies can revolutionize transport, health, and the environment. Chapter 9, "Federated Learning Hyper-Parameter Tuning for Edge Computing", proposes to facilitate the integration of federated learning and edge computing by optimizing federated learning hyper-parameters, which can significantly reduce training overhead and make it more affordable for edge computing Chapter 10, "Perspective Chapter: Edge Computing in Digital

Epidemiology and Global Health", looks at the application of edge computing in public health, critical medicine, and epidemiology. Finally, Chapter 11, "Perspective Chapter: Edge-Cloud Collaboration for Industrial IoT – An Online Approach", proposes how edge and cloud should converge for Industrial Internet of Things (IIoT) applications.

I am proud to present *Edge Computing – Technology, Management and Integration* and I would like to thank the staff at Intech Open, especially Ana Javor and Kristina Cvitan, who have ably supported me in getting this book to press and publication. I would also like to humbly thank all the authors who submitted chapters to this book. Without their tireless efforts and contributions, this book would not have been possible. I hope we can collaborate again in the future and publish more books together.

I hope everyone will enjoy reading and learning from this book and I hope it will inspire and encourage future research on edge computing. The adoption of edge computing technologies brings forth a host of benefits, including reduced latency, enhanced security and privacy, and improved reliability.

Any comments or questions can be emailed to sam.goundar@gmail.com

**Sam Goundar** RMIT University, Hanoi, Vietnam Section 1

Edge Computing
