Embedded OPC UA Server Design And Resource Scheduling Research

In recent years,the increase of data acquisition communication protocols and inconvenience of integration on industrial sites have brought great challenges to data interaction.Due to the need for information exchange between the equipment and the industrial cloud,the data interaction between the industrial field servers and the industrial cloud is becoming more and more frequent.Therefore,the study on embedded OPC UA server and resource scheduling has important theoretical significance and engineering practice value.Aiming at the two issues of how industrial equipment implements a unified industrial data communication protocol and resource scheduling after uploading industrial data to the industrial cloud.First,based on the open source OPC UA project Open62541,it designs and develops an embedded OPC UA server to unify the data collection interface of the four-axis industrial robot.Then,the model of embedded OPC UA server and industrial cloud is established,on this basis,an improved particle swarm task scheduling algorithm and load balancing virtual machine migration algorithm are proposed.Finally,build a test platform to verify the performance of the developed embedded OPC UA server and the designed algorithm.The work of this thesis mainly includes the following parts:1.The key technologies related to OPC UA,cloud computing and Cloudsim are studied.It mainly includes OPC UA data interaction architecture,OPC UA application development architecture,cloud computing features,cloud computing virtualization technology,cloud computing migration technology,Cloudsim system architecture and Cloudsim working model.2.The embedded OPC UA server is designed.The SDK for developing embedded OPC UA server is expensive,opaque,and difficult to carry out secondary development.Using the industrial four-axis robot in the laboratory as a representative of the industrial site,the embedded OPC UA server was developed using the open source OPC UA project Open62541 API to unify the data exchange interface of the industrial four-axis robot,and the function test of the server was carried out.3.Designed an improved particle swarm task scheduling algorithm.Aimed at the problems of slow speed in the early stage of resource scheduling algorithm used in industrial field and industrial cloud,easy to fall into local optimal in the later stage,and imbalance of virtual machine load.First,build a model of embedded OPC UA server and industrial cloud.Then,use the data collected by the embedded OPC UA server to generate a data set as the data input for building the model.Finally,on this basis,an improved particle swarm task scheduling algorithm is designed.4.Build a test platform and complete the test verification.The data acquisition function of the embedded OPC UA server developed was verified on the industrial fouraxis robot in the laboratory.Using the data collected by the embedded OPC UA server to randomly generate 1000 data sets as Cloudism's data input,and load the designed algorithm and other scheduling algorithms on the Cloudsim simulation platform.The performance of the improved particle swarm task scheduling algorithm is verified.The test results show that the embedded OPC UA server designed in this thesis implements the core functions of OPC UA,unifies the data collection protocol,breaks the limitations of the platform,and meets the needs of real-time data collection in industrial fields.The improved particle swarm task scheduling algorithm designed in this thesis has better performance than other proposed algorithms and achieves the expected results.