Fog Computing: An Overview of Big IoT Data Analytics

TLDR

IoT generates an explosive amount of data that overwhelms traditional cloud processing, prompting the emergence of fog computing, which deploys micro‑clouds at the network edge to enable big‑data analytics and support smart decision‑making. This survey reviews the challenges and opportunities of fog computing for big IoT data analytics on fog networks. The authors discuss key fog applications—healthcare monitoring, smart cities, connected vehicles, and smart grids—to illustrate a green computing paradigm for next‑generation IoT. They conclude that fog computing’s distinctive features make it an appropriate platform for the growing array of IoT devices, services, and applications.

Abstract

A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well‐organized green computing paradigm to support the next generation of IoT applications.