Research on cloud platform architecture of flight big data

Author(s):  
Fengqin Wang ◽  
Tingxue Xu ◽  
Shigai Li
Author(s):  
Corentin Dupont ◽  
Tomas Bures ◽  
Mehdi Sheikhalishahi ◽  
Congduc Pham ◽  
Abdur Rahim

2020 ◽  
Vol 12 (38) ◽  
pp. 43009-43017 ◽  
Author(s):  
Jian Huang ◽  
Jian Zhou ◽  
Yangmei Luo ◽  
Gan Yan ◽  
Yi Liu ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yueqin Zhu ◽  
Yongjie Tan ◽  
Xiong Luo ◽  
Zhijie He

Cloud computing as a powerful technology of performing massive-scale and complex computing plays an important role in implementing geological information services. In the era of big data, data are being collected at an unprecedented scale. Therefore, to ensure successful data processing and analysis in cloud-enabled geological information services (CEGIS), we must address the challenging and time-demanding task of big data processing. This review starts by elaborating the system architecture and the requirements for big data management. This is followed by the analysis of the application requirements and technical challenges of big data management for CEGIS in China. This review also presents the application development opportunities and technical trends of big data management in CEGIS, including collection and preprocessing, storage and management, analysis and mining, parallel computing based cloud platform, and technology applications.


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