Cloud data uploading method and system based on multi-node edge computing equipment

Abstract

The invention provides a cloud data uploading method and system based on multi-node edge computing equipment. The method comprises the steps: determining the image quality information of a monitoring image generated by a plurality of monitors, so as to judge the uploading feasibility of monitoring image data; corresponding uploading queues are generated according to the data volumes of the monitoring image data with uploading feasibility, and then the uploading time interval between every two adjacent monitoring image data in the uploading queues is adjusted according to the current data receiving busy and idle state of the cloud terminal. In this way, data parts, which do not meet the corresponding resolution requirements, in the monitoring image data can be removed in a targeted manner, so that the data volume of the monitoring image data needing to be uploaded is effectively compressed; in addition, the data uploading efficiency of the cloud terminal is improved and the situation of data uploading congestion is avoided by adjusting the uploading time interval between two adjacent monitoring image data in the uploading queue.

Description

technical field [0001] The invention relates to the technical field of computer data processing, in particular to a cloud data upload method and system based on multi-node edge computing devices. Background technique [0002] The distributed monitoring system obtains corresponding monitoring information by setting monitors in different monitoring areas, and then processes the monitoring information and uploads it to the cloud terminal. The distributed monitoring system uses monitors distributed in different monitoring areas as a computing node, which can greatly improve the monitoring comprehensiveness and real-time performance of the distributed monitoring system. However, since multiple computing nodes need to upload their corresponding monitoring image data to the cloud terminal, not all the monitoring image data obtained by the monitoring of computing nodes meet the corresponding resolution requirements. If all the monitoring image data are directly uploaded To the clou...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the defects existing in the prior art, the present invention provides a cloud data upload method and system based on a multi-node edge computing device, which obtains the monitoring image data generated by several monitors in their corresponding monitoring areas, and determines the corresponding monitoring image data. According to the image quality information, the uploading feasibility of the monitoring image data is judged according to the image quality information, and according to the judgment result of the uploading feasibility of the monitoring image data, a collection of monitoring image data to be uploaded about all monitors is generated, and Generate an upload queue for each surveillance image data in the surveillance image data set to be uploaded according to the respective data volumes of the surveillance image data, and then adjust two adjacent surveillance images in the upload queue according to the current data receiving status of the cloud terminal The upload time interval between the data, so as to upload all the monitoring image data of the upload queue to the cloud terminal; it can be seen that the cloud data upload method and system based on multi-node edge computing equipment determine the monitoring images produced by several monitors The image quality information of the monitoring image data is used to judge the uploading feasibility of the monitoring image data, and the corresponding upload queue is generated according to the respective data volume of the monitoring image data with the uploading feasibility, and then the uploading is adjusted according to the current data receiving status of the cloud terminal. The upload time interval between two adjacent monitoring image data in the queue, so that the data part of the monitoring image data that does not meet the corresponding resolution requirements can be eliminated in a targeted manner, so as to effectively compress the data of the monitoring image data that needs to be uploaded In addition, by adjusting the upload time interval between two adjacent monitoring image data in the upload queue, the data upload efficiency of the cloud terminal is improved and data upload congestion is avoided.

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