Research and Simulation of Large Data Differentiation Classification Technology under the Internet of Things

Differential classification of large data in the environment of Internet of things can improve the clustering ability of large data, a large data dissimilation classification method is proposed based on fuzzy C mean clustering and piecewise fusion scheduling. The large data set under the Internet of things is divided into several subsets by using the method of grid region segmentation, feature matching and redundant filtering for large data of mass Internet of things is taken by piecewise matching detection, adaptive attribute merging of large data differentiation characteristics in physical network is realized. The high order spectral features of the large data flow of the Internet of things are excavated, and the fuzzy C means clustering algorithm is used to cluster the difference characteristics of large data. Combining the piecewise fusion matching scheduling method to improve the feature matching ability of large data classification, and realize the classification and optimization of large data differentiation under the Internet of things. The simulation results show that this method is used to classify large data under the Internet of things, the accuracy of differential feature extraction is higher, the clustering of data classification is better, and the misclassification rate of large data classification is low.

I. Introductions

With the rapid development of information technology and data processing technology, using large data networking information processing method for data processing, data acquisition and scheduling can improve the classification ability. Large data information processing under the Internet of things is a distributed computing and parallel computing, a large number of large data of the Internet of things are distributed in the large data processing grid space of the Internet of things. In the cloud storage system, because the influence of the coupling interference of the storage medium and the network intrusion, it makes the challenges for secure storage of data, in order to solve the problem of large data security storage in the Internet of things, it is necessary to classify the large data differently for optimization partition and grid optimization design of large data storage space in Internet of things. Therefore, there are great significances to study the method of optimizing the large data classification of the Internet of things^[1]