Cloud Network and Mathematical Model Calculation Scheme for Dynamic Big Data

Cloud network oriented to dynamics big data is a popular way of big data operation at present. It is a big data that can be applied to human behavior under dynamics. Time-based features include communication, network access and migration activities combined with unique physiological characteristics to complete big data. This paper aims to study a new cloud hybrid network architecture based on edge computing. This article uses this architecture to tectonic fog calculation layer between cloud servers and devices using edge devices such as communications and networks. After analysis, the obtained results are actively cached on the fog computing device and compared with the data of the telecommunication network detection terminal on the fog device. To consider the final result. The experimental data show that the distributed computing scheme can achieve the goal of minimizing the task processing delay. The experimental results show that the cloud network of the dynamic big data can meet the requirements of the contemporary big data completely, and the utilization ratio of the big data can reach 90%, and the calculation scheme of the mathematical model can run completely.