There has been recently a big increase in the number of studies related to the statistical analysis and mathematical modeling of traffic measurements from modern communication networks. Long-range dependence occurs when the covariances decay slowly to zero slowly as the lag increases.
Heavy tails refer to the power decrease of the marginal distributions.
In the networking context, heavy tails abound and have been observed at practically all layers in the networking hierarchy. This research aims to develop physical models that can explain the joint presence of long-range dependence and heavy tails at the microscopic level. These models should be useful in practice, give rise to efficient traffic generation methods that result in synthetic traces with realistic features, and provide novel insights into the wide area of network performance analysis.