An efficient storage and service method for multi-source merging meteorological big data in cloud environment

With the development of the meteorological IoT (Internet of Things) and meteorological sensing network, the collected multi-source meteorological data have the characteristics of large amount of information, multidimensional and high accuracy. Cloud computing technology has been applied to the stora...

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Veröffentlicht in:EURASIP journal on wireless communications and networking Jg. 2019; H. 1; S. 1 - 12
Hauptverfasser: Yang, Ming, He, Wenchun, Zhang, Zhiqiang, Xu, Yongjun, Yang, Heping, Chen, Yufeng, Xu, Xiaolong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 29.10.2019
Springer Nature B.V
SpringerOpen
Schlagworte:
Big Data
Cloud computing
Communications Engineering
Data compression
Data management
Data storage
Data structures
Distributed NoSQL
Efficiency
Engineering
Information Systems Applications (incl.Internet)
Internet of Things
Meteorological data service
Meteorological data storage
Meteorological satellites
Multi-modal Sensor Data Fusion in Internet of Things
Multi-source merging sensors data
Networks
Semi/unstructured data
Signal,Image and Speech Processing
Transmission efficiency
Distributed NoSQL
Multi-source merging sensors data
Meteorological data storage
Semi/unstructured data
Meteorological data service
ISSN:1687-1499, 1687-1472, 1687-1499
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Zusammenfassung:With the development of the meteorological IoT (Internet of Things) and meteorological sensing network, the collected multi-source meteorological data have the characteristics of large amount of information, multidimensional and high accuracy. 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 the storage and access of meteorological data, storage and service efficiency is still far from meeting multi-source big data requirements. Traditional methods have been used for the storage and service of meteorological data, and a number of problems still persist, such as a lack of unified storage structure, poor scalability, and poor service performance. 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 process of data storage, 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 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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-019-1576-0