Design and Application of Fog Computing Model Based on Big Data

Abstract

Fog computing based on big data is a hot topic in the research of computing technology at home and abroad. With the wide application and popularity of IoT (Internet of Things), the big data generated by edge devices is exploding, and cloud computing models are becoming increasingly inadequate to meet the needs of big data processing and communication, which is mainly manifested as follows. Slow data processing, insufficient storage space, prolonged communication and many other issues. Fog computing, of which the advantage is distributed computing, namely the „de-centralized„ mode calculation, is the suitable solution to solve these problems. In the IoT system, fog computing model based on big data is constructed to distribute the big data computing, storage and communication in the system to the edge device. The purpose is to make the system structure simpler, more modular and intelligent, duce network congestion, exploit advantages of edge devices and improve high quality intelligence of IoT applications, and moreover, to reduce the deployment of IoT hardware and operating costs. Taking the cloud robotics as an example, it is proposed to embed the fog computing technology in the cloud robotics system, which greatly improves the computing function of the cloud robotics system. In short, it provides theoretical support and scientific experimental basis for the informationization and intelligence of all walks of life, and its research has certain value and significance.