DocumentCode
1796502
Title
Using client-side access partitioning for data clustering in big data applications
Author
Dapeng Liu ; Shaochun Xu ; Zengdi Cui
Author_Institution
GradientX, Santa Monica, CA, USA
fYear
2014
fDate
June 30 2014-July 2 2014
Firstpage
1
Lastpage
5
Abstract
Big data has been playing a critical role in modern information technology. In some big data management systems, to simplify client design, data requests from clients are even distributed to all nodes and then are routed to the final correct data storage inside the data cluster. After performing analysis on this working mechanism, we point out some design problems and advocate the client-side access partitioning, i.e., clients know precisely which node of the cluster should be accessed for sought information. This approach could provide a fast access. We also implement a first-stage application based on client-side access partitioning for evaluation purpose and the result demonstrates our approach is effective.
Keywords
Big Data; pattern clustering; storage management; very large databases; big data management systems; client-side access partitioning; data clustering; data requests; data storage; information technology; Big data; Computers; Distributed databases; Educational institutions; Partitioning algorithms; Telecommunication traffic; Client-Side Partitioning; data clustering; data security; load balance; performance;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2014 15th IEEE/ACIS International Conference on
Conference_Location
Las Vegas, NV
Type
conf
DOI
10.1109/SNPD.2014.6888697
Filename
6888697
Link To Document