Mathematical prediction model construction of network packet loss rate and nonlinear mapping user experience under the Internet of Things

Abstract

Abstract In order to further improve the prediction accuracy, the network packet loss rate (PLR) prediction mathematical model based on the Internet of Things (IoTs) was proposed. First, the network data transmission module was established, and the network PLR prediction process was developed based on IoTs; second, the prediction framework of PLR was designed to obtain more accurate prior information. The relationship between PLR and user experience quality QoE is univariate and nonlinear. The mapping between PLR and user experience quality QoE is established using univariate nonlinear regression analysis; finally, a mathematical model of network PLR prediction is constructed to further improve the prediction accuracy. Experimental results show that the delays of network nodes are all within 5 s, which can ensure the real-time nature of data transmission. When the total number of packets and the number of lost packets are the same, the PLR predicted by the mathematical model designed by the authors is consistent with the actual PLR. Conclusion: The prediction effect of the model is better and has higher promotion value.