干旱区生态环境知识资源中心(Arid): MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage

Arid

DOI	10.26599/TST.2021.9010082
	MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage
	Wu, Jiashu; Xiong, Jingpan; Dai, Hao; Wang, Yang; Xu, Chengzhong
通讯作者	Wang, Y
来源期刊	TSINGHUA SCIENCE AND TECHNOLOGY
ISSN	1007-0214
EISSN	1878-7606
出版年	2022
卷号	27 期号:6 页码:881-893
英文摘要	A large volume of Remote Sensing (RS) data has been generated with the deployment of satellite technologies. The data facilitate research in ecological monitoring, land management and desertification, etc. The characteristics of RS data (e.g., enormous volume, large single-file size, and demanding requirement of fault tolerance) make the Hadoop Distributed File System (HDFS) an ideal choice for RS data storage as it is efficient, scalable, and equipped with a data replication mechanism for failure resilience. To use RS data, one of the most important techniques is geospatial indexing. However, the large data volume makes it time-consuming to efficiently construct and leverage. Considering that most modern geospatial data centres are equipped with HDFS-based big data processing infrastructures, deploying multiple geospatial indices becomes natural to optimise the efficacy. Moreover, because of the reliability introduced by high-quality hardware and the infrequently modified property of the RS data, the use of multi-indexing will not cause large overhead. Therefore, we design a framework called Multi-IndeXing-RS (MIX-RS) that unifies the multi-indexing mechanism on top of the HDFS with data replication enabled for both fault tolerance and geospatial indexing efficiency. Given the fault tolerance provided by the HDFS, RS data are structurally stored inside for faster geospatial indexing. Additionally, multi-indexing enhances efficiency. The proposed technique naturally sits on top of the HDFS to form a holistic framework without incurring severe overhead or sophisticated system implementation efforts. The MIX-RS framework is implemented and evaluated using real remote sensing data provided by the Chinese Academy of Sciences, demonstrating excellent geospatial indexing performance.
英文关键词	Fault tolerance Satellites File systems Fault tolerant systems Distributed databases Memory Geospatial analysis Remote Sensing (RS) data geospatial indexing multi-indexing mechanism Hadoop Distributed File System (HDFS) Multi-IndeXing-RS (MIX-RS)
类型	Article
语种	英语
开放获取类型	Green Submitted, gold
收录类别	SCI-E
WOS记录号	WOS:000814631700004
WOS关键词	BIG DATA ; MANAGEMENT ; FRAMEWORK ; IMAGES
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Engineering, Electrical & Electronic
WOS研究方向	Computer Science ; Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394748
推荐引用方式 GB/T 7714	Wu, Jiashu,Xiong, Jingpan,Dai, Hao,et al. MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage[J],2022,27(6):881-893.
APA	Wu, Jiashu,Xiong, Jingpan,Dai, Hao,Wang, Yang,&Xu, Chengzhong.(2022).MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage.TSINGHUA SCIENCE AND TECHNOLOGY,27(6),881-893.
MLA	Wu, Jiashu,et al."MIX-RS: A Multi-Indexing System Based on HDFS for Remote Sensing Data Storage".TSINGHUA SCIENCE AND TECHNOLOGY 27.6(2022):881-893.