Predictive Modeling of Video Packet Delay in IP Networks

This paper studies linear prediction algorithms for packet-delay modeling. A detailed examination of the delay traces collected from video streams encoded at different bitrates, suggests that autoregressive (AR) models can exploit the correlation among the delay samples and produce the best estimates in terms of the mean-squared error criterion. Simulation results show that AR prediction can reduce the average prediction-error power significantly as compared to the exponentially-weighted moving average prediction as well as the recursive weighted median filtering. This is a promising result since many layers in the multimedia communication protocol stack, e.g., rate control, error control and network adaptation, can greatly benefit from accurate packet-delay prediction.