Hybrid cloud storage method based on software-defined storage

Abstract

The invention relates to a hybrid cloud storage method based on software defined storage, which performs data cloud storage according to data characteristics, and comprises the following steps of: 1)acquiring data to be stored, and identifying a data label of the data to be stored; 2) searching according to the data label, judging whether the data label exists in a preset mapping table or not, ifso, executing a step 3), and if not, executing a step 4); 3) storing to-be-stored data according to a storage strategy corresponding to the current data label in the mapping table; and 4) performingmachine learning by using the data label and the historical data storage strategy to obtain an optimal storage strategy corresponding to the current data label, and storing the to-be-stored data by using the optimal storage strategy. Compared with the prior art, the method has the advantages of good storage effect, various storage modes and the like.

Description

technical field [0001] The invention relates to the technical field of data cloud storage, in particular to a hybrid cloud storage method based on software-defined storage. Background technique [0002] Today, with the maturity of cloud computing technology and the explosive growth of data, how to effectively store data has become a challenging topic. A cloud computing platform of a certain scale often includes a large number of different tenants, cloud hosts of different sizes, different types of images, and so on. Therefore, cloud storage needs to face complex business scenarios. [0003] If all data is stored without distinction, there are the following shortcomings: [0004] 1) Poor resource utilization [0005] Some unimportant data may occupy better storage resources, and the importance of storage resources is not related to the data. [0006] 2) Lack of elastic expansion [0007] Since the data is not stored in categories, when the storage resources are expanded,...

AI Technical Summary

Problems solved by technology

[0005] Some unimportant data may occupy better storage resources, and the importance of storage resources is not related to the data

[0006] 2) Lack of elastic expansion

[0007] Since the data is not stored in different categories, when the storage resources are expanded, the data is prone to confusion

[0008] 3) Retrieval is difficult

[0009] The data is not classified accordingly, and the complexity of data retrieval increases

[0010] 4) Single storage method

[0011] When storing data indiscriminately, the storage backend is often single and lacks elastic changes

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