Title :
Wavelet-enabled Massive Data Compress Algorithm
Author :
Liu, C.H. ; Hu, X.
Author_Institution :
Sch. of Mech. & Electr. Eng., Guangzhou Univ., Guangzhou, China
Abstract :
This paper focuses on the issues on massive data compress such as massive data storage, complexity and variability in information processing system (IPS). In order to tackle these issues, this paper proposes an algorithm using multi-decomposition wavelet change for massive data compress (MDC). This algorithm concentrates on the multi-decomposition of data flow, vacuum, and parameters to form a data flow according to the date firstly. Secondly, multi-reversion methodology is used to convert the massive data flow. Finally, an experiment is executed to test this algorithm. The experiments illustrates that this algorithm using wavelet can achieve excellent compress efficiency and time cost while data searching under limited vacuum.
Keywords :
data compression; wavelet transforms; compress efficiency; data searching; information processing system; massive data flow; massive data storage; multidecomposition wavelet change; multireversion methodology; wavelet-enabled massive data compress algorithm; Dielectrics; Transform coding; Compress Algorithm; Massive Data; Wavelet;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620470