[Objective]To meet the requirements of timeliness,accuracy,and completeness of delay data in delay-sensitive appli-cation scenarios,it is necessary to implement end-to-end service delay estimation in Optical Transport Networks(OTN).[Methods]This paper first analyzes the transmission characteristics of OTN services,and collects service routing information according to the sub-net connections.Next,it discretizes the basic data such as Network Elements(NE),links,and cross-con-nection in service route.Then the characteristic variables for delay estimation are obtained.Finally,the paper proposes a delay estimation model based on engineering live network,and compares the simulation results of various machine learning algo-rithms.[Results]The Mean Absolute Percentage Errors(MAPE)of the delay estimation results based on Support Vector Re-gression(SVR)and decision tree regression were 3.362 8％and 1.284 9％,respectively.[Conclusion]The OTN service delay estimation method based on machine learning and the characteristic of OTN transmission in this paper has high accuracy and wide application scenarios.
维普
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