Characterization and control of highly correlated traffic in high speed networks

By assuming network traffic to be independent from each other, the analysis of network performance can be simplified. However, the real traffic sources may have some correlation which makes their behavior tend to converge or diverge. This phenomenon has a tremendous influence on congestion control. In this paper, we explain the possible reasons for correlated behavior, namely, top-down and client-server correlation, and analyze their impacts. We also use the rapid matrix-geometric solution to investigate the cost to pay when applying the leaky bucket input control scheme to the independent traffic sources (e.g. Poisson) and the correlated traffic sources (such as on-off and HAP (hierarchical arrival process))