Fog computing is a decentralized approach where computing resources are positioned between data sources and the cloud or other data centers. The term “fog” highlights its similarity to cloud computing, but with resources located closer to the ground—using edge devices to handle computation, storage, and communication locally. This proximity means that processed data is often immediately available to the devices that generated it, reducing latency and enabling faster responses. Fog computing has a wide range of applications, including industrial automation, smart cities, transportation, healthcare, and agriculture.
This book comprehensively addresses key aspects of fog computing systems, such as energy efficiency, quality of service (QoS), reliability, fault tolerance, load balancing, and scheduling. It pays special attention to emerging trends and industry requirements, including mobile edge computing, IoT integration, resource estimation, and virtualization within fog environments. The book delves into current research on automation, robotics, data privacy, security, and trust in fog computing. It also explores advanced techniques like deep learning, mobile edge computing, smart grids, and intelligent transportation systems, moving beyond foundational concepts to practical smart applications such as real-time traffic monitoring, interoperability in fog architectures, and smart homes and cities.
Enabling Technologies for Smart Fog Computing is designed for researchers in academia and industry, as well as lecturers, engineers, and advanced students seeking in-depth knowledge and insights into this evolving field.
