Title :
Estimating computation times of data-intensive applications
Author :
Krishnaswamy, Shonali ; Loke, Seng Wai ; Zaslavsky, Arkady
Author_Institution :
Monash Univ., Clayton, Vic., Australia
fDate :
4/1/2004 12:00:00 AM
Abstract :
We present a holistic approach to estimation that uses rough sets theory to determine a similarity template and then compute a runtime estimate using identified similar applications. We tested the technique in two real-life data-intensive applications: data mining and high-performance computing.
Keywords :
computational complexity; data mining; parallel processing; rough set theory; scheduling; application runtime prediction algorithm; computation time; data mining; data-intensive grid environment; rough-set-based estimation; scheduling algorithm; Accuracy; Computer applications; History; Information systems; Linear regression; Processor scheduling; Rough sets; Runtime environment; Scheduling algorithm; Testing;
Journal_Title :
Distributed Systems Online, IEEE
DOI :
10.1109/MDSO.2004.1301253
