Importance sampling for stochastic simulations
Management Science
IEEE/ACM Transactions on Networking (TON)
Use of &agr;-stable self-similar stochastic processes for modeling traffic in broadband networks
Performance Evaluation - Special issue on performance and control of network systems
An Introduction to the Regenerative Method for Simulation Analysis
An Introduction to the Regenerative Method for Simulation Analysis
On the use of fractional Brownian motion in the theory of connectionless networks
IEEE Journal on Selected Areas in Communications
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A technique for the fast simulation of broadband communication systems is proposed, which is based on regenerative Importance Sampling techniques and on large-deviation results. Our algorithm is applicable to estimate the probability of rare events when modeling the offered traffic using Fractional Stable Noise (FSN) processes (including Fractional Gaussian Noise as a particular case), which have been recently proved to be able to capture both the long-range dependence and the burstiness of today's aggregate network traffic. An exact description of FSN processes is given, as well as an approximation that allows for the application of Importance Sampling techniques. The results obtained for a simple example are also included.