Key Technology Research Of Evaluation Of Credibility Of Network Simulation Based On User's Perspective

Simulation credibility evaluation refers to the quantification of the credibility,when the simulation user or the decision maker apply the simulation model to solve the problem defined by themselves.The evaluation of credibility is of great significance to the application of simulation and the decision-making based on simulation.Network modeling and simulation is a specific field of modeling and simulation research,of which mainstream is based on some mature network simulation modeling tools.Therefore,the current network simulation is mainly from the perspective of the user,and the simulation program is a gray box for the user.Therefore,on the network simulation credibility evaluation,from the perspective of user,which aspects should be used to examine the credibility of the network simulation,and how to measure the performance of the simulation results in various aspects,is the key technologies for advance the level of confidence of application,as the network simulation user apply its modeling results.Therefore,this paper studies the key technologies of credibility evaluation of network simulation from the perspective of users,including:1.The method framework of network simulation credibility evaluation from the perspective of users is introduced.According to the characteristics of current network modeling and simulation and the key issues to be considered in the evaluation of simulation credibility,the framework of credibility evaluation of network simulation based on user's perspective is presented,then detailed process of the credibility evaluation of network simulation as well as the key technologies therein is introduced.2.The approach of analysis of effectiveness of network simulation data is studied.Effective simulation of simulation is credible premise.Sensitivity analysis is the main content of the effectiveness analysis of network simulation.Since the output of network simulation has certain mutual influences,in order to comprehensively analyze the influence degree of the input parameters of the simulation on the simulation output response,Auto-Encoder-RFR,the combined model of Auto-Encoder and random forest regression,is proposed.Auto-Encoder is used to extract the comprehensive characteristics of network performance indicators,and the extracted features and network simulation input parameters are used to construct a random forest regression model.Degree of influence by network simulation input parameters of the output response is measured via the variable importance score of random forest.3.The method of accuracy measurement of network simulation data is studied.The accuracy quantification is the goal of network simulation credibility evaluation.It mainly measures the similarity between network simulation data and reference data.Based on the topological data analysis,the correct estimation of the data set topology property is performed,then,the similarity of the topological properties of the simulation data and the reference data is quantified by the JS divergence of the probability distribution of the “holes” number of the simulation data set and the reference data set.That is,the similarity between the simulation data and the reference data in terms of global structure and behavior.The method proposed in this paper is suitable for users to verify and analyze the results of network simulation output.It is a global comprehensive analysis method combining qualitative verification and objective quantitative analysis.Which is feasible,effective,operational,and interpretable,and finally,it is verified by a data center network performance simulation analysis case.