In this paper we discuss the estimation of the loss probability in a queueing system with finite buffer fed by Brownian traffic, the Gaussian counterpart of the well-known Poisson process. The independence among arrivals in consecutive time slots allows the application of regenerative simulation technique, combined with the so-called Delta-method to construct confidence intervals for the stationary loss probability. Numerical simulation are carried out to verify the efficiency of the regenerative approach for different values of the queue parameters (buffer size and utilization) as well as simulation settings (digitization step and generalizations of the regeneration cycle)
Multiclass open queueing networks find wide applications in communication, computer, and fabrication...
We propose nonstandard simulation estimators of expected time averages over finite intervals [0, t],...
We study congestion periods in a finite fluid buffer when the net inputrate depends upon a recurrent...
We discuss the application of the regenerative simulation of estimate the loss probability in a queu...
Brownian input is an important particular case of the Gaussian processes, which are now well-recogni...
We discuss the application of the simulation to estimate the loss probability in a queueing system w...
Abstract—This paper proposes an approximate yet accurate ap-proach to calculate the loss probabiliti...
Time-sharing queueing systems in random environments allow only a limited-depth analytical study. In...
The special structure of regenerative processes is exploited to derive a new point estimate with ver...
Performance-oriented studies typically rely on the assumption that the stochastic process modeling t...
We investigate correctness of the classical loss probability formula for regener-ative queueing syst...
This paper is concerned with computing large-deviation asymptotics for the loss process in a stylize...
Conceptually, under restrictions, multiclass open queueing networks are positive Harris recurrent Ma...
Conceptually, under restrictions, multiclass open queueing networks are positive Harris recurrent Ma...
Abstract: A recently developed method for estimating confidence intervals when simulating stochastic...
Multiclass open queueing networks find wide applications in communication, computer, and fabrication...
We propose nonstandard simulation estimators of expected time averages over finite intervals [0, t],...
We study congestion periods in a finite fluid buffer when the net inputrate depends upon a recurrent...
We discuss the application of the regenerative simulation of estimate the loss probability in a queu...
Brownian input is an important particular case of the Gaussian processes, which are now well-recogni...
We discuss the application of the simulation to estimate the loss probability in a queueing system w...
Abstract—This paper proposes an approximate yet accurate ap-proach to calculate the loss probabiliti...
Time-sharing queueing systems in random environments allow only a limited-depth analytical study. In...
The special structure of regenerative processes is exploited to derive a new point estimate with ver...
Performance-oriented studies typically rely on the assumption that the stochastic process modeling t...
We investigate correctness of the classical loss probability formula for regener-ative queueing syst...
This paper is concerned with computing large-deviation asymptotics for the loss process in a stylize...
Conceptually, under restrictions, multiclass open queueing networks are positive Harris recurrent Ma...
Conceptually, under restrictions, multiclass open queueing networks are positive Harris recurrent Ma...
Abstract: A recently developed method for estimating confidence intervals when simulating stochastic...
Multiclass open queueing networks find wide applications in communication, computer, and fabrication...
We propose nonstandard simulation estimators of expected time averages over finite intervals [0, t],...
We study congestion periods in a finite fluid buffer when the net inputrate depends upon a recurrent...