Task view reduction Algorithm based on Rough sets in Gloud Storage

Yiyi Xu

Abstract


Knowledge reduction is one of the important research issues in rough set theory, which applies knowledge reduction theory to reduction the massive task sets in Gloud storage. At first, an equivalence class evolved from subviews will be obtained after task update, Then, a parallel running strategy is designed for large-scale data , and calculate the optimal attributes based on the task set with minimal time overhead, to this end, delete redundant views according to the optimal attribute sets. Finally, the optimized task combination views are obtained. Simulation results shows it has better overall performance in time span, runtime, speed-up ratio and scalability when compared with the original algorithm that under same conditions, the actual examples used in analysis indicate the effectiveness of this method.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4282


Keywords


Rough set, Knowledge reduction, Task view, MapReduce

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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