Design And Implementation Of Industrial Internet Of Things Cloud Platform Architecture Based On Edge Computing

For the industrial Internet of things cloud platform,the cloud data center is usually designed as the core,which provides many functions such as device access,rule engine,service management,big data analysis,3D display,etc.The rule engine plays a key role in the Industrial Internet of Things.The rule engine is a functional module that filter device data and executes certain specific operations on the filtered data,including material allocation,quality control,production safety control,production mode control,storage control,environmental control and many other controls directly related to the production of the factory rely on rule engine.However,during use,it was found that due to the remote location of the factory site and the poor network environment,the response time of the rule processing ranged from 2-3 seconds to 1 minute,and there was a packet loss rate of 5%-10%,resulting in data loss and rule invalid.In addition,because the cloud data center of an industrial enterprise needs to carry all device data of all factory sites,the cloud needs to process more than 5,000 pieces of equipment data per minute,which is prone to data backlogs.As the factory sites and the scale of usage continue to grow,the processing pressure is still increasing.In view of these problems,this paper designs an edge-cloud collaborative Internet of things platform,which uses the characteristics of edge end near data source to obtain device data through LAN and processes rule to reduce delay and ensure stability.For this system,the research content of this paper mainly includes the following three points:1.The rule discrimination to promote the edge rule processing to play the largest advantage.2.The edge resource management and control strategy to ensure the continuous and stable operation of the edge end.3.Offline processing to ensure that the edge rule processing results are not lost in case of disconnection.In addition,it also includes high-concurrent streaming data processing rule engines at both ends of the edge and cloud to achieve efficient data processing;edge-side data filtering and data compression,reducing cloud data center bandwidth pressure,and reducing cloud receiving device data frequency.Finally,a complete of edge-cloud collaborative Internet of things cloud platform is implemented according to the design of this paper.The functional test and performance test of the system are carried out respectively by using real equipment to simulate the real scene and simulating equipment to regulate data flow.Through performance tests,it is verified that the edge latency of system of about 10 seconds lower than the cloud under the condition that both sides are over 80%load.The edge resource management strategy can limit the edge resource occupation within the set threshold range.In addition,cloud bandwidth and computing pressure have been reduced by about 70%when using this system,verifying that the system has significant effects in reducing latency,increasing stability,and reducing cloud pressure.