We develop a stochastic foundation for bandwidth estimation of networks with
random service, where bandwidth availability is expressed in terms of bounding
functions with a defined violation probability. Exploiting properties of a
stochastic max-plus algebra and system theory, the task of bandwidth estimation
is formulated as inferring an unknown bounding function from measurements of
probing traffic. We derive an estimation methodology that is based on iterative
constant rate probes.
Fractional Brownian motion (fBm) emerged as a useful model for self-similar
and long-range dependent Internet traffic. Approximate performance measures are
known from large deviations theory for single queuing systems with fBm through
traffic. In this paper we derive end-to-end performance bounds for a through
flow in a network of tandem queues under fBm cross traffic. To this end, we
prove a rigorous sample path envelope for fBm that complements previous
approximate results.