Network tomography for internal delay estimation

On-line, spatially localized information about internal network performance can greatly assist dynamic routing algorithms and traffic transmission protocols. However, it is impractical to measure network traffic at all points in the network. A promising alternative is to measure only at the edge of the network and infer internal behavior from these measurements. In this paper we concentrate on the estimation and localization of internal delays based on end-to-end delay measurements from sources to receivers. We develop an EM algorithm for computing MLEs of the internal delay distributions in cases where the network dynamics are stationary over the observation period. For time-varying cases, we propose a sequential Monte Carlo procedure capable of tracking non-stationary delay characteristics. Simulations are included to demonstrate the promise of these techniques.