An Efficient Storage Service Method for Multidimensional Meteorological Data in Cloud Environment

Abstract

Meteorological data have many features, such as a large amount of information, multidimensionality, and high precision. Cloud computing technology has been applied to the storage and service of meteorological big data. Although the constant evolution of big data storage technology is improving meteorological data storage and access, storage and service efficiency is still far from meeting big data requirements. Traditional methods have been used for the storage and service of meteorological data, and some problems still persist, such as a lack of unified storage structure and poor scalability. In this study, an efficient storage and service method for multidimensional meteorological data is designed based on NoSQL big data storage technology and the multidimensional characteristics of meteorological data. In the data storage process, multidimensional block compression technology and data structures are applied to store and transmit meteorological data. In service, heterogeneous NoSQL common components are designed to improve the heterogeneity of the NoSQL database. The research results show that the proposed method has good storage transmission efficiency and versatility and can effectively improve the efficiency of meteorological data storage and service in meteorological applications.