scholarly journals A simple proof of a result of Iglehart and Shedler

1985 ◽  
Vol 17 (01) ◽  
pp. 239-241
Author(s):  
Mark Berman
Keyword(s):  
Confidence Intervals ◽  
Simple Proof ◽  
Passage Time ◽  
Alternative Proof ◽  
Multiclass Networks ◽  
Simple Alternative ◽  
General Service Times ◽  
Service Times ◽  
General Service ◽  
Networks Of Queues

Iglehart and Shedler (1983) prove that the ‘labelled jobs’ method for estimation of passage-time characteristics in closed multiclass networks of queues with general service times provides asymptotically shorter confidence intervals than does the ‘marked job’ method. A simple alternative proof of this result, under slightly more restrictive conditions, is given here.

scholarly journals A simple proof of a result of Iglehart and Shedler

1985 ◽  
Vol 17 (1) ◽  
pp. 239-241
Author(s):  
Mark Berman
Keyword(s):  
Confidence Intervals ◽  
Simple Proof ◽  
Passage Time ◽  
Alternative Proof ◽  
Multiclass Networks ◽  
Simple Alternative ◽  
General Service Times ◽  
Service Times ◽  
General Service ◽  
Networks Of Queues

Iglehart and Shedler (1983) prove that the ‘labelled jobs’ method for estimation of passage-time characteristics in closed multiclass networks of queues with general service times provides asymptotically shorter confidence intervals than does the ‘marked job’ method. A simple alternative proof of this result, under slightly more restrictive conditions, is given here.

Statistical efficiency of regenerative simulation methods for networks of queues

1983 ◽  
Vol 15 (1) ◽  
pp. 183-197 ◽  
Author(s):  
Donald L. Iglehart ◽  
Gerald S. Shedler
Keyword(s):  
Passage Time ◽  
General Function ◽  
Simulation Methods ◽  
Statistical Efficiency ◽  
Multiclass Networks ◽  
Regenerative Simulation ◽  
Time Information ◽  
General Service ◽  
Networks Of Queues ◽  
Passage Times

This paper is concerned with the assessment of the statistical efficiency of proposed regenerative simulation methods. We compare the efficiency of the ‘marked job' and ‘labelled jobs' methods for estimation of passage times in multiclass networks of queues with general service times. Using central limit theorem arguments, we show that the confidence intervals constructed for the expected value of a general function of the limiting passage time using the labelled jobs method are shorter than those obtained from the marked job method. This is consistent with intuition since the labelled jobs method extracts more passage-time information from a fixed-length simulation run.

Statistical efficiency of regenerative simulation methods for networks of queues

1983 ◽  
Vol 15 (01) ◽  
pp. 183-197 ◽  
Author(s):  
Donald L. Iglehart ◽  
Gerald S. Shedler
Keyword(s):  
Passage Time ◽  
General Function ◽  
Simulation Methods ◽  
Statistical Efficiency ◽  
Multiclass Networks ◽  
Regenerative Simulation ◽  
Time Information ◽  
General Service ◽  
Networks Of Queues ◽  
Passage Times

This paper is concerned with the assessment of the statistical efficiency of proposed regenerative simulation methods. We compare the efficiency of the ‘marked job' and ‘labelled jobs' methods for estimation of passage times in multiclass networks of queues with general service times. Using central limit theorem arguments, we show that the confidence intervals constructed for the expected value of a general function of the limiting passage time using the labelled jobs method are shorter than those obtained from the marked job method. This is consistent with intuition since the labelled jobs method extracts more passage-time information from a fixed-length simulation run.

scholarly journals Cyclic queueing networks with subexponential service times

2004 ◽  
Vol 41 (03) ◽  
pp. 791-801
Author(s):  
H. Ayhan ◽  
Z. Palmowski ◽  
S. Schlegel
Keyword(s):  
Queueing Networks ◽  
Time Distribution ◽  
Waiting Times ◽  
Queueing Network ◽  
Service Time Distribution ◽  
Tail Behavior ◽  
Cycle Times ◽  
General Service Times ◽  
Service Times ◽  
General Service

For a K-stage cyclic queueing network with N customers and general service times, we provide bounds on the nth departure time from each stage. Furthermore, we analyze the asymptotic tail behavior of cycle times and waiting times given that at least one service-time distribution is subexponential.

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