Video cloud storage system based storage and extraction performance balancing method and device

Abstract

The invention relates to video cloud storage and discloses a video cloud storage system based storage and extraction performance balancing method and device. The method includes: dividing acquired data into data blocks according to capacity and storing the data into different storage equipment of at least one storage server in a scattered manner; when extracting the data, acquiring information of the storage servers where the to-be-extracted data are located, wherein the information includes the size of the data blocks and the level of system loads; under the premise that scattered storage priority is guaranteed, formulating extraction strategies with user defined priority according to the information of the storage servers; concurrently extracting the data from the storage servers according to the extraction strategies. The data are stored in the different stored servers in a scattered manner, so that system resources are effectively utilized; under the premises that the scattered storage priority is guaranteed, the data are concurrently extracted from the different storage servers according to the extraction strategies, data security is guaranteed, the data can be extracted effectively, and confliction in preemption of the system resources in data storage and extraction is reduced.

Description

technical field [0001] The invention relates to the field of video cloud storage, in particular to a method and device for balancing storage and retrieval performance based on a video cloud storage system. Background technique [0002] Video cloud storage is an extension and development of the concept of cloud computing, through the cluster application, grid technology or fractional file system and other functions, through the collection of application software to work together to provide efficient video data storage and business access functions of a system. [0003] With the development of technology, the scale of video cloud deployment is getting larger and larger, and the amount of data is increasing by the order of tens of millions. At the same time, users have higher and higher requirements for video cloud storage performance and application experience. The performance requirements mainly include: fast storage speed, high data security and high practicality of the ove...

AI Technical Summary

Problems solved by technology

[0004] At present, when storing and extracting data, many systems mostly adopt the method of sequential storage and sequential extraction and block storage and sequential extraction. These two methods are not only inefficient but also poor in user experience. Data loss and other exceptions often occur during concurrent volume extraction. The actual scene description is as follows: figure 1 and figure 2 shown

in, figure 1 It is the application scenario of the normal environment of the video cloud storage system. In the normal use environment, the video cloud storage system first needs to meet the storage of big data and ensure data safety and reliability. However, this usage scenario is often only an ideal environment. Video cloud storage can To store massive amounts of data, there will be a large number of users who need to extract data at the same time, which will not only put pressure on the network but also seriously affect the system of the video cloud storage system, such as figure 2 The real operating environment of the video cloud storage system is shown

In an abnormal environment, due to the high load of the storage server of video cloud storage, it will not only affect the extraction efficiency, but more importantly, it will affect the normal data storage function, which may cause data loss and other problems, and may also cause more serious consequences.

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