| The scale of data generated by complex engineering systems during the execution of tasks is also constantly expanding as the communication technology and sensor technology rapidly developing.These massive monitoring data are collected by various sensors in the system,which can not only be used to directly reflect the overall state,signs and operational trends of the system.It also provides data support for a series of datadriven decision control of the system.However,with the continuous development of system tasks,the working conditions of the system will also change.These phenomena will seriously reduce the transmission efficiency and quality of monitoring data,making the monitoring platform unable to obtain real-time updated information,which is detrimental to subsequent decision control.To solve these problems,although there are some data transmission optimization schemes such as improving the transport layer protocol in the network model,expanding the data cache,improving the network bandwidth of the public network of the system,etc.,the essential problems of big data transmission have not been solved.Therefore,according to the characteristics and applicable categories of various data transmission optimization methods,and combined with the characteristics of the research object,it is decided to introduce compression technology into the optimization decision of monitoring data transmission.However,the compressed transmission of data will increase the extra data processing time,coupled with the influence of network environment,resulting in the transmission optimiza tion scheme cannot effectively improve the transmission efficiency.Therefore,in order to solve the problem of monitoring data compression transmission efficiency,this paper regards the complex engineering system as the research object and proposes a dynamic data compression transmission optimization control scheme for the purpose of optimizing the overall transmission efficiency of data based on the network transmission environment.The main work is as follows:(1)From the complex engineering system in complex network environment faced by data transmission bottleneck as a breakthrough point,according to the characteristics of the data transmission optimization methods,combined with the feature of the object of study and solution implementation cost and the complexity of implementation,discusses the feasibility of the compression techniques are introduced to improve data transmission efficiency and effectiveness.The overall idea and technical route of monitoring data transmission optimization control for complex engineering system are also planned.(2)According to the data characteristics of the object of study,pick out the suitable compression technology abbreviated to transmit data information redundancy,explore analysis was carried out on the compression algorithm for compression/decompression time consuming and the quantitative relationship between the compression ratio,and combining the data compression techniques are introduced to the overall transmission time consuming structure,this paper proposes a transport time-consuming optimization strategy based on dynamic compression ratio.Improving data transmission efficiency from a global perspective.(3)For data transmission in the process,the subsequent network transmission rate for data compression transmission optimization strategy,created the "traditional +residual deep learning" hybrid forecasting model to forecast the subsequent network transmission rate analysis,based on the prediction of the network environment,builds the corresponding dynamic adjusting data compression transmission efficiency optimization model of the compression ratio.So as to reduce the influence of network transmission environment change on data transmission efficiency.Finally,the data transmission efficiency optimization control scheme proposed in this paper is applied to the monitoring data transmission process of the ground support monitoring system of a space launch center.The experimental results show that the transmission optimization method can reduce the overall data transmission time to within the data collection cycle,and ensure the timeliness and real-time performance of the monitoring data. |
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