• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.809-817
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• 1998

In this paper we consider a polling system where the token is passed according to a general service order table. We derive an exact and explicit formula to compute the mean waiting time for a message when the arrivals of messages are modeled by batch Poisson processes.

• Journal of the Korean Statistical Society
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• v.26 no.3
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• pp.355-363
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• 1997

In queueing theory, polling systems have been widely studied as a way of serving several stations in cyclic order. In this paper we consider Markov-modulated Poisson process which is useful for approximating a superposition of heterogeneous arrivals. We derive the mean waiting time of each station in a polling system where the arrival process is modeled by a Markov-modulated Poisson process.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.2
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• pp.103-113
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• 2013

We analyze the queueing model for leaky bucket (LB) scheme with dynamic arrivals and token rates. In other words, in our LB scheme the arrivals and token rates are changed according to the buffer occupancy. In telecommunication networks, the LB scheme has been used as a policing function to prevent congestion. By considering bursty and correlated properties of input traffic, the arrivals are assumed to follow a Markov-modulated Poisson process (MMPP). We derive the distribution of system state, and obtain the loss probability and the mean waiting time. The analysis is done by using the embedded Markov chain and supplementary variable method. We also present some numerical examples to show the effect of our proposed model.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.455-464
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• 2005

In this paper, we analyze a queueing system with overload control by arrival rates. This paper is motivated by overload control to prevent congestion in telecommunication networks. The arrivals occur dependent upon queue length. In other words, if the queue length increases, the arrivals may be reduced. By considering the burstiness of traffics in telecommunication networks, we assume the arrival to be a Markov-modulated Poisson process. The analysis by the embedded Markov chain method gives to us the performance measures such as loss and delay. The effect of performance measures on system parameters also is given throughout the numerical examples.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1989.10a
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• pp.6-6
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• 1989

• Korean Management Science Review
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• v.32 no.2
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• pp.69-78
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• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.601-616
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• 2021

Retrial queueing models have been studied extensively in the literature. These have many practical applications, especially in service sectors. However, retrial queueing models have their own limitations. Typically, analyzing such models involve level-dependent quasi-birth-and-death processes, and hence some form of a truncation or an approximate method or simulation approach is needed to study in steady-state. Secondly, in general, the customers are not served on a first-come-first-served basis. The latter is the case when a new arrival may find a free server while prior arrivals are waiting in the retrial orbit due to the servers being busy during their arrivals. In this paper, we take a different approach to the study of multi-server retrial queues in which the signals are generated in such a way to provide a reasonably fair treatment to all the customers seeking service. Further, this approach makes the study to be level-independent quasi-birth-and-death process. This approach is different from any considered in the literature. Using matrix-analytic methods we analyze MAP/M/c-type retrial queueing models along with Poisson signals in steady-state. Illustrative numerical examples including a comparison with previously published retrial queues are presented and they show marked improvements in providing a quality of service to the customers.

• Journal of Communications and Networks
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• v.17 no.3
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• pp.265-266
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• 2015

In a recent paper [1], the authors investigated the maximum stable throughput region of a network composed of a rechargeable primary user and a secondary user plugged to a reliable power supply. The authors studied the cases of an infinite and a finite energy queue at the primary transmitter. However, the results of the finite case are incorrect. We show that under the proposed energy queue model (a decoupled M/D/1 queueing system with Bernoulli arrivals and the consumption of one energy packet per time slot), the energy queue capacity does not affect the stability region of the network.

• Bulletin of the Korean Mathematical Society
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• v.43 no.3
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• pp.657-669
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• 2006

In this paper, we analyze a leaky bucket (LB) scheme with queue length dependent arrival rates. In other words, if the queue length exceeds an appropriate threshold value on buffer, the arrivals need to be controlled. In ATM networks, if the congestion occurs, the input traffics must be controlled (reduced) for congestion resolution. By the bursty and correlated properties of traffics, the arrivals are assumed to follow a Markov-modulated Poisson process (MMPP). We derive the loss probability and the waiting time distribution for arbitrary cell. The analysis is done by using the embedded Markov chain and supplementary variable method. We also present some numerical examples to show the effects of our proposed LB scheme.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.503-525
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• 1998

In the theory of retrial queues it is usually assumed that the flow of primary customers is Poisson. This means that the number of independent sources, or potential customers, is infinite and each of them generates primary arrivals very seldom. We consider now retrial queueing systems with a homogeneous population, that is, we assume that a finite number K of identical sources generates the so called quasi-random input. We present a survey of the main results and mathematical tools for finite source retrial queues, concentrating on M/G/1//K and M/M/c//K systems with repeated attempts.