Cloud storage of massive remote sensing data based on distributed file system

Ziwen Chi, Feng Zhang, Zhenhong Du, Ren-yi Liu
{"title":"Cloud storage of massive remote sensing data based on distributed file system","authors":"Ziwen Chi, Feng Zhang, Zhenhong Du, Ren-yi Liu","doi":"10.1109/ICSPCC.2013.6663922","DOIUrl":null,"url":null,"abstract":"Cloud storage is an effective means to solve the storage and management challenges of the growing mass remote sensing data products. In order to settle the problems existing in the application of cloud storage for remote sensing data, a distributed storage module based on image blocks organization was put forward, and the inefficient problem of distributed file system in massive image blocks storage was solved. In the combination of the module and HDFS, the efficient distributed storage and retrieval of image data were implemented, and the ability of spatial data access of the remote sensing data cloud storage was enabled. As built upon distributed file system, the storage system has a good scalability to meet the requirements of data growing. The experiment and analysis showed that the storage system could maintain a high throughput and stability under multiple concurrent connections.","PeriodicalId":124509,"journal":{"name":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCC.2013.6663922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Cloud storage is an effective means to solve the storage and management challenges of the growing mass remote sensing data products. In order to settle the problems existing in the application of cloud storage for remote sensing data, a distributed storage module based on image blocks organization was put forward, and the inefficient problem of distributed file system in massive image blocks storage was solved. In the combination of the module and HDFS, the efficient distributed storage and retrieval of image data were implemented, and the ability of spatial data access of the remote sensing data cloud storage was enabled. As built upon distributed file system, the storage system has a good scalability to meet the requirements of data growing. The experiment and analysis showed that the storage system could maintain a high throughput and stability under multiple concurrent connections.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于分布式文件系统的海量遥感数据云存储
云存储是解决海量遥感数据产品存储和管理挑战的有效手段。为了解决遥感数据云存储应用中存在的问题,提出了一种基于图像块组织的分布式存储模块,解决了海量图像块存储中分布式文件系统效率低下的问题。通过模块与HDFS的结合,实现了图像数据的高效分布式存储和检索,实现了遥感数据云存储的空间数据访问能力。存储系统建立在分布式文件系统的基础上,具有良好的可扩展性,可以满足数据增长的需求。实验和分析表明,该存储系统在多并发连接情况下仍能保持较高的吞吐量和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Direction of arrival estimation via sparse representation of fourth order statistics Analysis of accurate signal propagation model for through-wall imaging radar using compressive sensing Research on smart antenna beamforming by generalized regression neural network 3D underwater topography rebuilding based on single beam sonar Noise performance of a new FM-DCSK communication system
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1