Research on Particle Swarm Optimization Clustering Algorithm for Big Data Based on Cloud Storage Environment

Abstract

With the development of the times, the amount of various data increases exponentially in the process of information processing, and all walks of life use computers to manage and count a large amount of data. There are more and more data piled up in the database, and the scale of data is unprecedented. It is difficult for ordinary database technology to efficiently manage and utilize these data and their hidden important information. Under the background of cloud computing, the main purpose of big data information processing is to realize data clustering. Cluster analysis is an unsupervised learning process, which aims to classify the data of a group of category attribute positions under certain requirements, and make the data similarity between these categories as low as possible, and the data similarity within the categories as high as possible. In this paper, an optimized clustering algorithm for big data in cloud storage based on optimized particle swarm optimization algorithm is proposed, and the improved design of big data clustering algorithm is carried out by using particle swarm optimization algorithm.