• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.941-948
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• 2013

We introduce the $P^M_{{\lambda},{\tau}}$ service policy, as a generalized two-stage service policy of the $P^M_{\lambda}$ policy of Bae et al. (2002) for an M/G/1 queueing system. By using the level crossing theory and solving the corresponding integral equations, we obtain the explicit expression for the stationary distribution of the workload in the system.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.203-206
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• 2003

This paper studies constrained optimization of an M/G/1 queue with a server that can be switched on and off. One criterion is an average number of customers in the system and another criterion is an average operating cost per unit time, where operating costs consist of switching and running costs. With the help of queueing theory, we solve the problems of optimization of one of these criteria under a constraint for another one.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.179-186
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• 1993

We derive the arbitrary time point system size distribution of M/ $G^{B}$1 queue in which late arrivals are not allowed to join the on-going service. The distribution is given by P(z) = $P_{4}$(z) $S^{*}$ (.lambda.-.lambda.z) where $P_{4}$ (z) is the probability generating function of the queue size and $S^{*}$(.theta.) is the Laplace-Stieltjes transform of the service time distribution function. We also derive the distribution of the service siez at arbitrary point of time. time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2450-2469
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• 2018

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.1-10
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• 2016

In this paper, we present a new way to derive the mean cycle time of the G/G/m failure prone queue when the loading of the system approaches to zero. The loading is the relative ratio of the arrival rate to the service rate multiplied by the number of servers. The system with low loading means the busy fraction of the system is low. The queueing system with low loading can be found in the semiconductor manufacturing process. Cluster tools in semiconductor manufacturing need a setup whenever the types of two successive lots are different. To setup a cluster tool, all wafers of preceding lot should be removed. Then, the waiting time of the next lot is zero excluding the setup time. This kind of situation can be regarded as the system with low loading. By employing absorbing Markov chain model and renewal theory, we propose a new way to derive the exact mean cycle time. In addition, using the proposed method, we present the cycle times of other types of queueing systems. For a queueing model with phase type service time distribution, we can obtain a two dimensional Markov chain model, which leads us to calculate the exact cycle time. The results also can be applied to a queueing model with batch arrivals. Our results can be employed to test the accuracy of existing or newly developed approximation methods. Furthermore, we provide intuitive interpretations to the results regarding the expected waiting time. The intuitive interpretations can be used to understand logically the characteristics of systems with low loading.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.1035-1045
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• 2001

We present two decomposition approximations for the mean sojourn times in open single class queing networks. If there is a single bottleneck station, the approximations are asymptotically exact in both light and heavy traffic. When applied to a Jackson network or an M/G/1 queue, these approximations are exact for all values of the traffic intensity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.841-844
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• 2002

Recently there has been an increasing interest in queueing models with disasters. Upon arrival of a disaster, all the customers present are noshed out. Queueing models with disasters have been applied to the problems of failure recovery in many computer networks systems, database systems and telecommunication networks in this paper, we suffest the steady state and sojourn time distributions of the M/G/l model with disaster and mass alway when the system is empty.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.71-79
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• 2014

Purpose: The purpose of this study is to develop the methods for evaluating patients' queue environment using decision tree and queueing theory. Methods: This study uses CHAID decision tree and M/G/1 queueing theory to estimate pain point and patients waiting time for medical service. This study translates hospital physical data process to logical process to adapt queueing theory. Results: This study indicates that three nodes of the system has predictable problem with patients waiting time and can be improved by relocating patients to other nodes. Conclusion: This study finds out three seek points of the hospital through decision tree analysis and substitution nodes through the queueing theory. Revealing the hospital patients' queue environment, this study has several limitations such as lack of various case and factors.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.23-38
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• 2005

The state of channel between two or more wireless terminals is changed frequently due to noise or multiple environmental conditions in wireless network. In this paper, we analyze packet transmission time and queue length in a time-varying channel of packet based Wireless Networks. To reflect the feature of the time-varying channel, we model the channel as two-state Markov model and three-state Markov model Which are transformed to SFG(Signal Flow Graph) model, and then the distribution of the packet transmission can be modeled as Gaussian distribution. If the packet is arrived with Poisson distribution, then the packet transmission system is modeled as M/G/1. The average transmission time and the average queue length are analyzed in the time-varying channel, and are verified with some simulations.

• East Asian mathematical journal
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• v.24 no.1
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• pp.45-55
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• 2008

We consider an M/G/1 queue with $P^M_{\lambda}$-service policy, which is a two-stage service policy. The server starts to serve with rate 1 if a job arrives to the sever in idle state. If the workload of the system upcrosses $\lambda$, then the service rate is changed to M and this rate continues until the system is empty. It costs to change the service rate to M and maintaining the rate. When the expectation of the stationary workload is supposed to be less than a given value, we derive the optimal value of M.