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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 19 | Page No.: 3569-3574
DOI: 10.3923/jas.2009.3569.3574
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Imitating K-Means to Enhance Data Selection

A. Jaradat, R. Salleh and A. Abid

In this study, a new approach that utilizes availability, security and time as selection criteria between different replicas is proposed. However, selecting the replica in accordance with the three factors simultaneously is complicated; therefore, concepts from the K-means clustering algorithm were adopted to create a balanced (best) solution. Numerical simulations were carried out to assess the proposed technique. The results show that the proposed system outperforms random algorithm by 17% and outperforms the round robin algorithm by 11%.
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  •    A Replica Selection Algorithm in Data Grid
  •    A Novel Detector Generation Scheme for Detecting the Level of Abnormality of Equipment
  •    A Modified Tabu Search Approach for the Clustering Problem
How to cite this article:

A. Jaradat, R. Salleh and A. Abid, 2009. Imitating K-Means to Enhance Data Selection. Journal of Applied Sciences, 9: 3569-3574.

DOI: 10.3923/jas.2009.3569.3574






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