A Retrial Queue with a Constant Retrial Rate, Server Downs and Impatient Customers

2005 ◽  
Vol 21 (2-3) ◽  
pp. 531-550 ◽  
Author(s):  
Hui Li ◽  
Yiqiang Q. Zhao
Keyword(s):  
Retrial Queue ◽  
Impatient Customers ◽  
Constant Retrial Rate

Analysis of a retrial queue with group service of impatient customers

2019 ◽  
Vol 11 (6) ◽  
pp. 2591-2599 ◽  
Author(s):  
M. P. D’Arienzo ◽  
A. N. Dudin ◽  
S. A. Dudin ◽  
R. Manzo
Keyword(s):  
Retrial Queue ◽  
Impatient Customers ◽  
Group Service

scholarly journals A discrete-time Geo/G/1 retrial queue with preferred and impatient customers

2013 ◽  
Vol 37 (4) ◽  
pp. 2552-2561 ◽  
Author(s):  
Jinbiao Wu ◽  
Jianxin Wang ◽  
Zaiming Liu
Keyword(s):  
Discrete Time ◽  
Retrial Queue ◽  
Impatient Customers

scholarly journals Approximation of the steady state system state distribution of the M/G/1 retrial queue with impatient customers

2012 ◽  
Vol 22 (2) ◽  
pp. 285-296 ◽  
Author(s):  
Nadjet Stihi ◽  
Natalia Djellab
Keyword(s):  
Steady State ◽  
Retrial Queue ◽  
Mean Value ◽  
Retrial Queues ◽  
System State ◽  
Impatient Customers ◽  
State Distribution ◽  
Information Theoretic ◽  
Principle Of Maximum Entropy ◽  
Principle Of Maximum

For M/G/1 retrial queues with impatient customers, we review the results, concerning the steady state distribution of the system state, presented in the literature. Since the existing formulas are cumbersome (so their utilization in practice becomes delicate) or the obtaining of these formulas is impossible, we apply the information theoretic techniques for estimating the above mentioned distribution. More concretely, we use the principle of maximum entropy which provides an adequate methodology for computing a unique estimate for an unknown probability distribution based on information expressed in terms of some given mean value constraints.

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