Data management across geographically distributed autonomous systems: architecture, implementation, and performance evaluation
© 2019 IEEE. The issue of highly efficient geographically-distributed autonomous data management is one of the critical obstacles for opening up a big data era. It creates the need for investigating autonomous and distributed data management systems in big data environments. In this paper, a distributed autonomous data management system is put forward, exhibiting the following features. (1) A distributed architecture designed to meet the requirements of autonomous data management by allowing interconnection, intercommunication, and interoperation of multiple sites over the Internet. (2) An autonomous, multi-level, unstructured data storage system to meet high-efficiency storage needs, with reference to the distributed heterogeneous data storage theories. (3) A distributed autonomous data indexing and retrieval system to support metadata search & full-text searching, fast loading, remote access, and unified view. Experimental and application results demonstrate that the proposed system has high potential to reduce access time and improve storage efficiency, while maintaining satisfactory availability and scalability.
History
Pagination
2284-2292Location
Zhangjiajie, ChinaStart date
2019-08-10End date
2019-08-12ISBN-13
9781728120584Language
engPublication classification
E1 Full written paper - refereedTitle of proceedings
HPCC/SmartCity/DSS 2019 : IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and SystemsEvent
HPCC/SmartCity/DSS. Conferences (21st: 17th : 5th : 2019 : Zhangjiajie, China)Publisher
IEEEPlace of publication
Piscataway, N.J.Usage metrics
Categories
No categories selectedLicence
Exports
RefWorksRefWorks
BibTeXBibTeX
Ref. managerRef. manager
EndnoteEndnote
DataCiteDataCite
NLMNLM
DCDC