Round Trip Time Prediction Using the Symbolic Function Network Approach

Abstract

In this paper, we develop a novel approach to model the Internet round trip time using a recently proposed symbolic type neural network model called symbolic function network. The developed predictor is shown to have good generalization performance and simple representation compared to the multilayer perceptron based predictors.

Round-trip time estimation in telecommunication networks using composite expanding and fading memory polynomials

“…On the other hand, relatively few methods are applied on this problem that have resulted in better performance due to the non stationarity nature of the system [7]. Some system identification techniques are applied in [7] [8].…”

“…On the other hand, relatively few methods are applied on this problem that have resulted in better performance due to the non stationarity nature of the system [7]. Some system identification techniques are applied in [7] [8]. In addition, some machine learning methods are investigated; a recurrent neural network based predictor is developed in [9] [10] to produce single step and multi step ahead prediction of the RTT time series.…”