| The application of massive data leads vigorous increasing of simultaneously data access of distributed file system, which results the bottleneck took into account of file IO. With the difference of performance and cost of different storage devices , temporal locality and spatial locality of data access, multi-tiered storage is needed so that the frequently accessed data is storaged in the high performance equipment and recently less frequently accessed data is storaged in the low performance equipment. For the frequently change rule of data, variety of data accessed frequency, the big proportion of static data in storage system for cloud data and limitation of high performance storage equipments, migrate data based on multi-tiered storage technology.The typical value judgment based on file level and the architecture of migration need improving, and recently there are many factors relative with the value of data which advantage and disadvantage should be measured. The improving of value judgement based on file level is required in order to fit for the access of storage equipment. For the practical application of high frequently data access, advanced strategy of data migration is proposed which is used to optimize the delay of storage equipment.Aim at the above issue, a value judgement and an architecture of data migration are proposed in this paper propose. Define some factors evaluating the value judgement and modify the existing model of value judgement based on file level. With analysis of existing application environment and modified value judgement model, a data migration algorithm based on file level is proposed. Migrate data with heavy access resulting from simultaneously data access, and use the test tool of web simultaneously data access to measure the hardware access. Test the responsing time of simultaneously data access of a web server, which shows that comparing to the normal data migration , the algorithm improves the performance of system. |
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