• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.1-14
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• 1994

In this paper, an analytical model of the message delay in the DQDB (Distributed Queue Dual Bus) network is investigated. The DQDB network has been adopted as a subnetwork for the IEEE 802 MAN (Metropolitan Area Network) standard. The DQDB network consists of two high speed undirectional buses and a series of stations attached to both of the buses. Massages arriving at each station consists of severla packets according to its size. This system is approximated into " $B^{[x]}$/G/1 with exceptional first service queueing " by defining the concept of service time on a packet. The service time for a packet is defined as the time from the instant the packet arrives at the transmission buffer until the time the packet is fully transmitted. By using the BASTA property and the average work in the system, the mean message delay time is obtained.age work in the system, the mean message delay time is obtained.d.

• Journal of Nutrition and Health
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• v.31 no.8
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• pp.1347-1354
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• 1998

The purposes of this study were to : (a) anlayze wating time, service rate, arrival rate, and coustomer expectations/satisfaction in cafeteria business foodservices and (b) identify the differences in those factors between foodservices by menu managmenet systems. The samples were two business foodservices operated by contract management in Seoul. The queue, laptime , service rate, and arrival rate were measured at each foodservice by stopwatch observation. The menu type, delivery system, number of meals served , servide time, and turnover rate of each foodservic was investigated. Questionnaires were developed to survey customer expectations and satisfaction. Satistical data analysis was completed using the SAS package programs for descriptive analysis and t-test. The mean waiting time of island type dafeteria system with separte set -menu was shorter than that of the other. In both foodservices, arrival rates were not significantly different from one another , but sevice rates were significnatly high in dafeteria menu systems. The peak time of the queue was found out at combination set menu line. The separate set menu line had a higher servide rate than the combination set menu line. The mean waiting time of the island type cafeteria line was shorter than that of the straifth type . At the straight type dafeterial line, both arrival rate and service rate were higher than those of island-type. The results of this study suggested that a separate set-menu would be more desirable than a combination set-menu in case of providing set menu with cafeteria menu.

• 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 the Korean Statistical Society
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• v.33 no.3
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• pp.283-298
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• 2004

We present a trial solution approach to GI/M/l queues with generalized vacations. Specific types of generalized vacations we consider are N -policy and a combination of N-policy and exponential multiple vacations. Discussions about how to find trial solutions are given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.575-596
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• 2009

Facing limited network resources such as bandwidth and processing capability, the Internet will have congestion from time to time. In this paper, we propose a scheme to maximize the total utility offered by the network to the end user during congested times. We believe the only way to achieve our goal is to make the scheme application-aware, that is, to take advantage of the characteristics of the application. To make our scheme scalable, it is designed to be class-based. Traffic from applications with similar characteristics is classified into the same class. We adopted the RED queue management mechanism to adaptively control the traffic belonging to the same class. To achieve the optimal utility, the traffic belonging to different classes should be controlled differently. By adjusting link bandwidth assignments of different classes, the scheme can achieve the goal and adapt to the changes of dynamical incoming traffic. We use the control theoretical approach to analyze our scheme. In this paper, we focus on optimizing the control on two types of traffic flows: TCP and Simple UDP (SUDP, modeling audio or video applications based on UDP). We derive the differential equations to model the dynamics of SUDP traffic flows and drive stability conditions for the system with both SUDP and TCP traffic flows. In our study, we also find analytical results on the TCP traffic stable point are not accurate, so we derived new formulas on the TCP traffic stable point. We verified the proposed scheme with extensive NS2 simulations.

• 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.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.300-307
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• 2008

Power management (PM) depends on the power state transition and system workload. The system model is composed of corresponding stochastic models of the power state and system queue. In this paper, stochastic models which can handle various PM techniques are developed. SRN (Stochastic Reward Nets), an extended Petri-Net, has facilities that represent system queue and various modelling functions. The SRN is employed for developing PM models. An adaptive timeout PM model is also introduced and the power consumption and performance of this model are compared with other existing PM techniques models such as greedy and N-Policy techniques.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.37-43
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• 2016

This note discusses the inter-loss time ofan M/G/1/1 queuing system. The inter-loss time is defined as the time duration between two consecutive losses of arriving customers. In this study, we present the explicit Laplace transform of the inter-loss time distribution of an M/G/1/1 queuing system.

• 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 Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.134-141
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• 2005

Due to the complexity and stochastic nature of automated warehousing system, items are usually queued up at I/O point. We introduce a storage/retrieval policy : dual-command. We present quick approximations to queueing phenomena under these policies. It is assumed that the storage and retrieval arrival pattern follow the same poisson process. We also assumed that storage queue and retrieval queue being operated separately. The approximation attempts are performed under the proposed storage/retrieval policies after we derive S/R machine travel time distributions.