Cloud manufacturing data efficient processing system based on edge computing

Abstract

The invention discloses a cloud manufacturing data efficient processing system based on edge computing, including a data acquisition module, a data processing module, an equipment management module, a data distribution module, a cloud server, a management module and a storage module; the invention collects data through the equipment management module. The module manages the operating status of each device that collects data, and prioritizes the operating data generated by the device; through the data processing module, the data is preliminarily processed, the defective data is repaired, the useless data is deleted, and the data contained in the collected data is removed. Garbled and repeated parts, and length control of the collected data to achieve data standardization; the data distribution module divides the data stream into multiple block files to achieve global optimization of computing resources and storage resource allocations; the intelligent allocation module It enables tasks to be executed with the maximum degree of parallelism, thereby improving execution efficiency, reducing data handling time, and adding minutes and seconds to enterprise decision-making.

Description

technical field [0001] The invention relates to the technical field of data application processing, in particular to a cloud manufacturing data efficient processing system based on edge computing. Background technique [0002] Edge computing is a distributed computing model. As the middle layer of cloud data centers and IoT devices, it provides computing, network and storage functions, so that cloud data center-based services can be closer to IoT devices. The introduction of the concept of edge computing is also to deal with the challenges faced by traditional cloud computing in IoT applications. Edge computing lets data be processed at the edge network. The edge network is basically composed of terminal devices (such as mobile phones and smart devices), edge devices (such as border routers, set-top boxes, network bridges, base stations, wireless access points), edge servers, and the like. These devices have certain performance to support edge computing. As a localized co...

AI Technical Summary

Problems solved by technology

It is increasingly difficult for the existing ETL performance to meet the requirements of the enterprise, resulting in data delay and incomplete data, affecting enterprise decision-making analysis and cross-departmental collaboration, and becoming a bottleneck for the future development of the enterprise

[0004] In the field of server data processing, at present, single or multiple servers are used for simultaneous processing. When processing through a single server, the processing capacity of a single server is limited, and when multiple servers are used, it is easy to cause waste of server resources. This problem has not been reasonably resolved.

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