ABSTRACT
As the Internet of Things (IoT) continues to evolve, the demand for efficient and scalable computing solutions has become increasingly significant. This chapter explores the role of cloud computing, fog computing, and edge computing in facilitating the deployment and management of IoT applications. Specifically, the chapter delves into the application of cloud analytics for IoT, the emergence of the Cloud of Things (CoT), the concept of fog computing, and the growing importance of edge computing. The chapter begins by examining cloud analytics for IoT applications, highlighting the advantages of leveraging cloud-based analytics platforms to process and analyze vast amounts of IoT data. It discusses how cloud computing can enable real-time insights, predictive maintenance, and advanced analytics, empowering organizations to derive actionable intelligence from their IoT deployments. Next, the concept of the CoT is explored, emphasizing its role as an extension of cloud computing for IoT. The chapter elucidates how CoT enables seamless integration and interoperability across diverse IoT devices and services, fostering a cohesive ecosystem for data sharing, processing, and collaboration. Subsequently, the chapter delves into fog computing, a paradigm that aims to bridge the gap between cloud computing and edge computing. It explores the motivations behind fog computing, such as reducing latency, enhancing data privacy, and enabling real-time decision-making in close proximity to IoT devices. The chapter highlights the benefits of fog computing in scenarios in which low-latency, context-aware computing is essential, such as smart cities, industrial automation, and healthcare. Finally, the chapter discusses the significance of edge computing in the context of IoT deployments. It elucidates how edge computing leverages localized computing resources to process data near the source, enabling real-time analytics, reducing bandwidth consumption, and addressing concerns related to latency and data privacy.
