A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway
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-comput...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2012/396387 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849409890797223936 |
|---|---|
| author | Hanning Wang Weixiang Xu Futian Wang Chaolong Jia |
| author_facet | Hanning Wang Weixiang Xu Futian Wang Chaolong Jia |
| author_sort | Hanning Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-7f9eb298157f4af593a010d319e71040 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-7f9eb298157f4af593a010d319e710402025-08-20T03:35:20ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2012-01-01201210.1155/2012/396387396387A Cloud-Computing-Based Data Placement Strategy in High-Speed RailwayHanning Wang0Weixiang Xu1Futian Wang2Chaolong Jia3State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing JiaoTong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaAs 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.http://dx.doi.org/10.1155/2012/396387 |
| spellingShingle | Hanning Wang Weixiang Xu Futian Wang Chaolong Jia A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway Discrete Dynamics in Nature and Society |
| title | A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway |
| title_full | A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway |
| title_fullStr | A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway |
| title_full_unstemmed | A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway |
| title_short | A Cloud-Computing-Based Data Placement Strategy in High-Speed Railway |
| title_sort | cloud computing based data placement strategy in high speed railway |
| url | http://dx.doi.org/10.1155/2012/396387 |
| work_keys_str_mv | AT hanningwang acloudcomputingbaseddataplacementstrategyinhighspeedrailway AT weixiangxu acloudcomputingbaseddataplacementstrategyinhighspeedrailway AT futianwang acloudcomputingbaseddataplacementstrategyinhighspeedrailway AT chaolongjia acloudcomputingbaseddataplacementstrategyinhighspeedrailway AT hanningwang cloudcomputingbaseddataplacementstrategyinhighspeedrailway AT weixiangxu cloudcomputingbaseddataplacementstrategyinhighspeedrailway AT futianwang cloudcomputingbaseddataplacementstrategyinhighspeedrailway AT chaolongjia cloudcomputingbaseddataplacementstrategyinhighspeedrailway |