Importance sampling, jump distributions and event-time distributions

Author

Frater, Michael R. ; Anderson, Brian D O

Author_Institution

Dept. of Electr. Eng., Australian Defence Force Acad., Canberra, ACT, Australia

fYear

1991

fDate

11-13 Dec 1991

Firstpage

1525

Abstract

Two different methods have been proposed for performing asymptotically optimal simulation to obtain the statistics of buffer overflows in queueing networks, with both using large deviations and importance sampling. In the first, based on heuristic arguments, the distributions of interarrival and virtual service times are analyzed to find the simulation system. In the second, it is the distribution of jumps occurring in a Markov chain that is examined. The authors show that the approaches produce identical fast simulation systems for an arbitrary G1/G1/1 queue

Keywords

graph theory; heuristic programming; queueing theory; statistical analysis; G1/G1/1 queue; Markov chain; asymptotically optimal simulation; buffer overflow statistics; event-time distributions; heuristic arguments; importance sampling; interarrival times; jump distributions; jumps distribution; large deviations; virtual service times; Analytical models; Australia; Buffer overflow; Discrete event simulation; Educational institutions; Modeling; Monte Carlo methods; Random variables; Statistical distributions; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1991., Proceedings of the 30th IEEE Conference on

Conference_Location

Brighton

Print_ISBN

0-7803-0450-0

Type

conf

DOI

10.1109/CDC.1991.261657

Filename

261657