| With the development of intelligent manufacturing and the Internet of Things,the current manufacturing industry is developing towards informatization and datamation,and the demand for industrial field data collection is expanding.At the same time,the rapid growth of data size and the real-time requirements also make the application of edge computing more urgent.To solve these problems,a data acquisition gateway based on edge computing is designed,which can realize a more reliable industrial field data acquisition and make the deployment of edge computing more flexible.At first,the hardware platform of the gateway is designed.According to the different characteristics of industrial field data acquisition objects,the data sources are divided into equipment data,low-speed sensor data,and high-speed analog signals.Different acquisition schemes are designed for each type of data,and the flexibility of data acquisition is enhanced by using interface modularization.Then,a gateway hierarchical software service is built based on the Linux system.The entire software service is organized by the application layer,business layer,service layer,and system layer.While realizing the online configuration and data acquisition function of the gateway,it also provides a complete edge calculation deployment service,which can provide a flexible data analysis function locally.Finally,an edge computing offloading service framework is proposed.The local server is used to accelerate the edge computing task processing of gateway nodes,and a multi-user computing offloading strategy is formulated based on the potential game,which can make the service run stably and efficiently.Experiments show that the industrial data acquisition gateway can handle complex industrial data acquisition effectively.At the same time,the gateway can provide powerful edge computing processing ability based on edge computing offloading,and has more advantages when compared to the traditional edge computing model. |
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