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Discrete Dynamics in Nature and Society
Volume 2012 (2012), Article ID 396387, 15 pages
http://dx.doi.org/10.1155/2012/396387
Research Article

A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway

1State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
2School of Traffic and Transportation, Beijing JiaoTong University, Beijing 100044, China

Received 28 August 2012; Revised 31 October 2012; Accepted 21 November 2012

Academic Editor: Wuhong Wang

Copyright © 2012 Hanning Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

As an important component of China’s transportation data sharing system, high-speed railway data sharing is a typical application of data-intensive computing. Currently, most high-speed railway data is shared in cloud computing environment. Thus, there is an urgent need for an effective cloud-computing-based data placement strategy in high-speed railway. In this paper, a new data placement strategy named hierarchical structure data placement strategy is proposed. The proposed method combines the semidefinite programming algorithm with the dynamic interval mapping algorithm. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices, while the dynamic interval mapping algorithm ensures better self-adaptability of the data storage system. A hierarchical data placement strategy is proposed for large-scale networks. In this paper, a new theoretical analysis is provided, which is put in comparison with several other previous data placement approaches, showing the efficacy of the new analysis in several experiments.