Rough set clustering approach to replica selection in data grids (RSCDG)

In data grids, the fast and proper replica selection decision leads to better resource utilization due to reduction in latencies to access the best replicas and speed up the execution of the data grid jobs. In this paper, we propose a new strategy that improves replica selection in data grids with t...

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Bibliographic Details
Published in2010 10th International Conference on Intelligent Systems Design and Applications pp. 1195 - 1200
Main Authors Almuttairi, R M, Wankar, R, Negi, A, Chillarige, R R
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2010
Subjects
Algorithm design and analysis
Availability
Clustering algorithms
Data Grid
Data mining
Kmeans
Quickreduct
Replica Selection Strategies
Rough Set Theory (RST)
Rule Algorithm
Security
Set theory
Silicon
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ISBN1424481341
9781424481347
ISSN2164-7143
DOI10.1109/ISDA.2010.5687024

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Summary:In data grids, the fast and proper replica selection decision leads to better resource utilization due to reduction in latencies to access the best replicas and speed up the execution of the data grid jobs. In this paper, we propose a new strategy that improves replica selection in data grids with the help of the reduct concept of the Rough Set Theory (RST). Using Quickreduct algorithm the unsupervised clustering is changed into supervised reducts. Then, Rule algorithm is used for obtaining optimum rules to derive usage patterns from the data grid information system. The experiments are carried out using Rough Set Exploration System (RSES) tool.
ISBN:1424481341
9781424481347
ISSN:2164-7143
DOI:10.1109/ISDA.2010.5687024