Proof of a fundamental result in self-similar traffic modeling
ACM SIGCOMM Computer Communication Review
Fluid models for single buffer systems
Frontiers in queueing
Heavy Tails and Long Range Dependence in On/Off Processes and Associated Fluid Models
Mathematics of Operations Research
Macroscopic models for long-range dependent network traffic
Queueing Systems: Theory and Applications
On–off fluid models in heavy traffic environment
Queueing Systems: Theory and Applications
Sample-path large deviations for generalized processor sharing queues with Gaussian inputs
Performance Evaluation - Long range dependence and heavy tail distributions
A Tandem Queue With LÉVY Input: A New Representation Of The Downstream Queue Length
Probability in the Engineering and Informational Sciences
Open problems in Gaussian fluid queueing theory
Queueing Systems: Theory and Applications
Gaussian queues in light and heavy traffic
Queueing Systems: Theory and Applications
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Highly-aggregated traffic in communication networks is often modeled as fractional Brownian motion (fBm). This is justified by the theoretical result that the sum of a large number of on–off inputs, with either on-times or off-times having a heavy-tailed distribution with infinite variance, converges to fBm, after rescaling time appropriately. For performance analysis purposes, the key question is whether this convergence carries over to the stationary buffer content process. In this paper it is shown that, in a heavy-traffic queueing environment, this property indeed holds.