Round Trip Time Prediction Using the Symbolic Function Network Approach

TL;DR

This paper introduces a symbolic function network model for predicting Internet round trip time, demonstrating improved generalization and simpler representation over traditional neural network models.

Contribution

The paper presents a novel symbolic neural network approach for round trip time prediction, offering better generalization and interpretability.

Findings

Good generalization performance

Simpler model representation

Outperforms multilayer perceptron predictors

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.