A Hierarchical Storage Strategy Based on Block-Level Data Valuation

Hierarchical storage is the core for information lifecycle management (ILM), and data classification based on its value is the key issue for hierarchical storage. In this paper, a block-level valuation model is proposed to classify data in disk. The model parameters is determined by comparing the factors in the view of block-level with in the file-level view data value, and it also discussed how to gather and measure the parameters in the model from a real storage environment. At last the model is validated through a real case study. The experiment shows that the model is feasible and valuable for data classification in storage subsystem, even it knows nothing about the data context in the disk.