  This paper studies and analyses the behavior of the Long-Range Dependence in
network traffic after classifying traffic flows in aggregated time series.
Following Differentiated Services architecture principles, the generic Quality
of Service applications that requirements and use the transport control
protocol, a basic classification criterion of time series is established. Using
the fractal theory, the resulting time series are analyzed. The Hurst exponent
is estimated and used as a measure of traffic burstiness and Long-Range
Dependency in each traffic class. The traffic volume per class is also
measured. The study uses traffic traces collected at the core switch at the
Electric Engineering Department at Universidad de Santiago de Chile in
different periods of network activity.
