Measurement and modelling of self-similar traffic in computer networks

Measurement and Modelling of Self-Similar Traffic in Computer Networks

We report results from the analysis of traffic measured over a departmental switched Ethernet. Self-similar characteristics are seen throughout the network, for example at the compute servers, web server and intermediate routers. We show that data shipped by the web server (i.e. including both static files from a filer server and dynamically-generated data) has a heavy-tailed distribution which...

Self-generated Self-similar Traffic

Self-similarity in the network traffic has been studied from several aspects: both at the user side and at the network side there are many sources of the long range dependence. Recently some dynamical origins are also identified: the TCP adaptive congestion avoidance algorithm itself can produce chaotic and long range dependent throughput behavior, if the loss rate is very high. In this paper w...

A measurement-based congestion alarm for self-similar traffic

Abstrucf-Self-similar traffic is distinguished by positive correlation, which can be exploited for better traffic management. Inspired hy measurement-based admission control schemes, a measurement-based congestion alarm is proposed. The aggregate traffic at an output port of a switch or router in a high-speed network is modeled by a fractional Gaussian noise process. Traffic measurements are pe...

Self-similar Traffic Models

Neural Approach Self-Similar Traffic Prediction in ATM Networks

Recent studies have shown that conventional traffic models are unable to capture the real nature of traffic pattern in high-speed networks, such as ATM Networks. Instead, they found that self-similar model is a better model in representing this type of traffic pattern. The differences between conventional and self-similar models have significant implications in network design, management and an...