Design of Space Remote Sensing Data Storage Platform Based on Distributed File System

被引：0
|
作者：
Li, Di [1 ,2 ]
Peng, Yizhun [1 ,2 ]
Bai, Ruixiang [1 ,2 ]
Chen, Zhenjiang [1 ,2 ]
Zhao, Lianchen [1 ,2 ]
机构：
[1] Tianjin Univ Sci & Technol, Coll Elect Informat & Automat, Tianjin 300222, Peoples R China
[2] Tianjin Univ Sci & Technol, Adv Struct Integr Int Joint Res Ctr, Tianjin 300222, Peoples R China
来源：
PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB2020) | 2020年
关键词：
Namenode; Datanode; HDFS; Space remote sensing data; Hadoop;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Due to the large space remote sensing data, a space remote sensing data has seven or eight hundred megabytes or more, and a large amount of space remote sensing data is generated every day for hundreds of GB, TB or even more, so a large amount of space is needed for storage. Space remote sensing data. In order to solve such problems, this paper prepares for the analysis of the subsequent space remote sensing data and combines the distributed file system to store the space remote sensing data. The installation of the CentOS 6.5 virtual machine through VMware to build an HDFS cluster, through a Namenode, three Datanode nodes to achieve access to space remote sensing data. Through the upload of the server, the space remote sensing data can be uploaded to the client, and the space remote sensing data can be downloaded through the client.
引用
收藏
页码：560 / 563
页数：4
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