Methods for modelling and simulating network delays at coarse time-scales

This thesis introduces a novel model for characterising network delays and a method derived from it for generating representative synthetic network delays. The model of network delays is based on combining multiple Weibull probability distributions to accurately fit the delay histogram observed in the delay traces. The idea of using the Weibull distribution as a basis to build the delay histogram is based on earlier studies on queueing theory under self-similar input traffic. However, such theoretical results have not been validated in real end-to-end scenarios. In this work, a method for finding the optimal model parameters will be introduced, tested and validated with measurements collected under real network activity. Additionally, two extensions of this algorithm shall be introduced: a real-time modification for tracking network delays adaptively; and an algorithm for generating synthetic but statistically equivalent network delays. Finally, network research topics will be introduced as possible applications and further directions of research. These include: real-time network management, service differentiation, QoS routing and delay-based congestion-control.