Independent mirror image management method suitable for intelligent gateway

Abstract

The invention discloses an independent mirror image management method suitable for an intelligent gateway, and the method comprises the steps: preprocessing a collected mirror image file corresponding to a current cloud platform, and obtaining a mirror image file data set; building an independent mirror image management model based on a deep neural network, sequentially performing grid division according to mirror image file attributes in the mirror image file data set, and judging positive and negative independent mirror image tendency; setting a data query period in combination with a judgment result according to an intelligent gateway polling rule; and performing periodic data query on the divided mirror image file data set, and if a message queue exists, transmitting the mirror image file data set to a cloud platform. According to the method, the mirror image files are screened through preprocessing, the screened mirror image files are further judged in combination with the model, irrelevant data are removed, the cache space of data transmission is reduced, blank files without messages are removed in a polling mode. The independent management efficiency of the mirror image file is greatly improved, and the starting and running speed of the mirror image file can be increased.

Description

technical field [0001] The invention relates to the technical field of independent image management of intelligent gateways, in particular to an independent image management method suitable for intelligent gateways. Background technique [0002] In a virtualized data center environment, computing, storage, and network resources are delivered to users in the form of virtual machines. On storage devices, virtual machines exist in the form of image files. Because image files are large and highly reusable , usually choose a KEY-VALUE type cloud storage asset library with high scalability characteristics to centrally manage image files. [0003] In the prior art, the storage topology of the traditional virtualized data center is used to manage the image files, that is, the image files are stored in the cloud storage space in practical applications. To start and run the image files, the image files need to be copied from the cloud storage space to The storage space is managed dur...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, the storage topology of the traditional virtualized data center is used to manage the image files, that is, the image files are stored in the cloud storage space in practical applications. To start and run the image files, the image files need to be copied from the cloud storage space to The storage space is managed during the running period, and then the server where the shared storage space is located executes the image file. However, the virtual machine image file is large and the amplitude time is long, which leads to the problem that the image file starts and runs slowly.

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