DocumentCode :
3476596
Title :
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
Link To Document :
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