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The Design and Evaluation of a Strategy of Data Placement in Cloud Computing Platform

Open Access
|Mar 2014

Abstract

Cloud computing has become a new platform for personal computing. However, while designing the strategy of data placement, there still lacks the consideration of systematic diversity of distributed transaction costs. This paper proposes the use of genetic algorithms to address the data placement problem in cloud computing. This strategy has adequately considered the correlation between data slices to minimize the total cost of distributed transactions. Compared to other methods, genetic algorithms have proven to comprehensively consider the correlation between the data slices in cloud computing, therefore greatly reducing the amount and cost of distributed transactions.

Language: English
Page range: 13 - 30
Submitted on: Oct 10, 2013
Accepted on: Feb 2, 2014
Published on: Mar 1, 2014
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2014 Wei Guo, Kaibo Luo, Xinjun Wang, Lizhen Cui, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.