• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.1-12
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• 1998

We consider G/M/1 queues with multiple vacation disci-pline where at the end of every busy period the server stays idle in the system for a period of time called changeover time and then follows a vacation if there is no arrival during the changeover time. The vaca-tion time has a hyperexponential distribution. By using the methods of the shift operator and supplementary variable we explicitly obtain the queue length probabilities at arrival time points and arbitrary time points simultaneously.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.53-60
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• 2007

We consider the discrete-time $Geo^x/G/1$ queues under N-policy with multiple vacations (a single vacation) and setup time. In this queueing system, the server takes multiple vacations (a single vacation) whenever the system becomes empty, and he begins to serve the customers after setup time only if the queue length is at least a predetermined threshold value N. Using the heuristic approach, we derive the mean waiting time for both vacation models. We demonstrate that the heuristic approach is also useful for the discrete-time queues.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1111-1115
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• 2006

We present heuristic interpretations of the mean waiting time of $Geo^X/G/1$ vacation queues with set-up time. The heuristic interpretation of the mean waiting time is originally proposed for the continuous-time queues. We demonstrate that the heuristic approach is useful for the discrete-time queues as well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.91-105
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• 2019

Discrete-time Queueing models are frequently utilized to analyze the performance of computing and communication systems. The length of busy period is one of important performance measures for such systems. In this paper, we consider the busy period of the Geo/Geo/1/K queue with a single vacation. We derive the moments of the length of the busy (idle) period, the number of customers who arrive and enter the system during the busy (idle) period and the number of customers who arrive but are lost due to no vacancies in the system for both early arrival system (EAS) and late arrival system (LAS). In order to do this, recursive equations for the joint probability generating function of the busy period of the Geo/Geo/1/K queue starting with n, 1 ≤ n ≤ K, customers, the number of customers who arrive and enter the system, and arrive but are lost during that busy period are constructed. Using the result of the busy period analysis, we also numerically study differences of various performance measures between EAS and LAS. This numerical study shows that the performance gap between EAS and LAS increases as the system capacity K decrease, and the arrival rate (probability) approaches the service rate (probability). This performance gap also decreases as the vacation rate (probability) decrease, but it does not shrink to zero.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.107-114
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• 1990

A queueing system with compound Poisson arrival and server vacation is analyzed by including supplementary variables. We consider a vacation system in which the server leaves for a vacation as soon as the system empties. When he returns, if no customer is waiting for service, he waits until a group of customers arrive and then begins to serve. We obtain the system size distribution and the waiting time distribution. Additional performance measures will be also considered.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.2
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• pp.1-10
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• 1988

We consider a vacation system in which the server takes two different types of vacations alternately. We obtain the server idle probability and derive the system size distribution and the waiting time distribution by defining supplementary variables. We show that the decomposition property works for these mixed-vacation queues. We also propose a method directly to obtain the waiting time distribution without resorting to the system equations. The T-policy is revisited and is shown that the cost is minimized when the length of vacations are the same.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.51-63
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• 1993

We consider a cyclid server system under N-policy. This system consists of multiple queues served in a cyclic order by a single server. In this paper, we consider the following control policy. Every time server polls one queue, the server inspects the state of the queue. If the total number of units is found to have reached or exceeded a pre-specified value, the server begins to serve the queue until it is empty. As soon as the queue becomes empty, the server polls next queue. An approximate analysis of this system is presented. Sever vacation model is used as an analytical tool. However, server vacation periods are considered to be dependent on the service times of respective queues. The results obtained from the approximate analysis are ompared with simulation results.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.389-393
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• 2008

This paper describes a single-server queue where the server is unavailable during some intervals of time, which is referred to as vacations. The major contribution of this work is to derive general formulas for the additional delay in the vacation models of the single vacations, head of line priority queues with non-preemptive service, and multiple vacations and idle time.

• Communications of the Korean Mathematical Society
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• v.10 no.2
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• pp.443-460
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• 1995

We consider a G/M/1 vacation model where the vacation time has k-stages generalized Erlang distribution. By using the methods of the shift operator and supplementary variable, we explicitly obtain the limiting probabilities of the queue length at arrival time points and arbitrary time points simultaneously. Operational calculus technique is used for solving non-homogeneous difference equations.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1137-1140
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• 2005

We present the discrete-time version of the heuristic interpretation of the mean waiting time known well about the continuous-time version. The heuristic approach is mainly based on an arriving customer's viewpoint. We obtain the mean waiting time of $Geo^X/G/1$ queueing systems, including vacation queues.