Application of the stochastic fluid flow model for bottleneck identification and classification

Network performance management is facing the challenge of provisioning advanced services with stringent delay and throughput requirements. For this reason, shortage of network capacity implying delay or loss, so-called bottlenecks, have to be identified and to be classified. The latter tasks imply the need for tractable analytical performance models. We identify the stochastic fluid flow model, which is based on bit rates and its statistics, as a possible candidate of being capable of describing qualitative behaviour of bottlenecks. In this work, we show how total and individual bit rate statistics at the output of a bottleneck are calculated via the stochastic fluid flow model. From this, we deduce some general behaviours and classification criteria for bottlenecks.