Accelerated buffer overflow simulation in self-similar queuing networks with long-range dependent processes and finite buffer capacity

The paper recommends an approach to estimate effectively the probability of buffer overflow in high-speed communication networks, capable of carrying diverse traffic, including self-similar teletraffic, and supporting diverse levels of quality of service. Simulations with stochastic, long-range dependent self-similar traffic source models are conducted. A new efficient algorithm, based on a variant of the RESTART/LRE method, is developed and applied to accelerate the buffer overflow simulation in a finite buffer single server model under long-range dependent self-similar traffic load with different buffer sizes. Numerical examples and simulation results are shown.