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Research on a Hierarchical Storage Framework and Algorithm of High-Speed Railway Maintenance Big-Data Based on Multi Metric Features

Aiming at the problems of low storage and retrieval efficiency and high execution cost caused by the current unified storage method of high-speed railway maintenance big-data, a data hierarchical storage method based on multi metric features was proposed. Firstly, the data hierarchical storage requirements of high-speed railway maintenance data asset collection platform were analyzed. The data hierarchical storage architecture was proposed. Secondly, considering the business and attribute characteristics of high-speed railway maintenance big-data, a data value evaluation system was established in this paper. For the initially stored data, a data hierarchical storage algorithm was proposed. For the already stored data, a data migration algorithm based on generation countermeasure network was proposed. Finally, the existing data of the platform has been taken as the experimental sample for verification. The experimental results show that the accuracy rate of the data layering algorithm proposed in this paper is 88%, which realizes the efficient storage of data and reduces the storage cost.