• Title/Summary/Keyword: M/G/1 queues

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M/G/1 Preemptive Priority Queues With Finite and Infinite Buffers (유한 및 무한 용량 대기열을 가지는 선점 우선순위 M/G/1 대기행렬)

  • Kim, Kilhwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.4
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    • pp.1-14
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    • 2020
  • Recently, M/G/1 priority queues with a finite buffer for high-priority customers and an infinite buffer for low-priority customers have applied to the analysis of communication systems with two heterogeneous traffics : delay-sensitive traffic and loss-sensitive traffic. However, these studies are limited to M/G/1 priority queues with finite and infinite buffers under a work-conserving priority discipline such as the nonpreemptive or preemptive resume priority discipline. In many situations, if a service is preempted, then the preempted service should be completely repeated when the server is available for it. This study extends the previous studies to M/G/1 priority queues with finite and infinite buffers under the preemptive repeat-different and preemptive repeat-identical priority disciplines. We derive the loss probability of high-priority customers and the waiting time distributions of high- and low-priority customers. In order to do this, we utilize the delay cycle analysis of finite-buffer M/G/1/K queues, which has been recently developed for the analysis of M/G/1 priority queues with finite and infinite buffers, and combine it with the analysis of the service time structure of a low-priority customer for the preemptive-repeat and preemptive-identical priority disciplines. We also present numerical examples to explore the impact of the size of the finite buffer and the arrival rates and service distributions of both classes on the system performance for various preemptive priority disciplines.

G/M/1 QUEUES WITH DELAYED VACATIONS

  • Han, Dong-Hwan;Choi, Doo-Il
    • 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.

RETRIAL QUEUES WITH A FINITE NUMBER OF SOURCES

  • Artalejo, J.R.
    • 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.

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A SIMPLE APPROACH TO THE WORKLOAD ANALYSIS OF M/G/1 VACATION QUEUES

  • Kim, Nam-Ki;Park, Yon-Il;Chae, Kyung-Chul
    • Journal of the Korean Statistical Society
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    • v.33 no.2
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    • pp.159-167
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    • 2004
  • We present a simple approach to finding the stationary workload of M/G/1 queues having generalized vacations and exhaustive service discipline. The approach is based on the level crossing technique. According to the approach, all that we need is the workload at the beginning of a busy period. An example system to which we apply the approach is the M/G/1 queue with both multiple vacations and D-policy.

Conditional sojourn time distributions in M/G/1 and G/M/1 queues under PMλ-service policy

  • Kim, Sunggon
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.443-451
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    • 2018
  • $P^M_{\lambda}$-service policy is a workload dependent hysteretic policy. The policy has two service states comprised of the ordinary stage and the fast stage. An ordinary service stage is initiated by the arrival of a customer in an idle state. When the workload of the server surpasses threshold ${\lambda}$, the ordinary service stage changes to the fast service state, and it continues until the system is empty. These service stages alternate in this manner. When the cost of changing service stages is high, the hysteretic policy is more efficient than the threshold policy, where a service stage changes immediately into the other service stage at either case of the workload's surpassing or crossing down a threshold. $P^M_{\lambda}$-service policy is a modification of $P^M_{\lambda}$-policy proposed to control finite dams, and also an extension of the well-known D-policy. The distributions of the stationary workload of $P^M_{\lambda}$-service policy and its variants are studied well. However, there is no known result on the sojourn time distribution. We prove that there is a relation between the sojourn time of a customer and the first up-crossing time of the workload process over the threshold ${\lambda}$ after the arrival of the customer. Using the relation and the duality of M/G/1 and G/M/1 queues, we obtain conditional sojourn time distributions in M/G/1 and G/M/1 queues under the policy.

A Note on the Decomposition Property for $M^{X}$/G/1 Queues with Generalized Vacations (일반휴가형 $M^{X}$/G/1 대기행렬의 분해속성에 대한 소고)

  • Chae, Kyung-Chul;Choi, Dae-Won;Lee, Ho-Woo
    • Journal of Korean Institute of Industrial Engineers
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    • v.28 no.3
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    • pp.247-255
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    • 2002
  • The objective of this paper is to clarify the decomposition property for $M^{X}$/G/1 queues with generalized vacations so that the decomposition property is better understood and becomes more applicable. As an example model, we use the $M^{X}$/G/1 queue with setup time. For this queue, we correct Choudhry's (2000) steady-state queue size PGF and derive the steady-state waiting time LST. We also present a meaningful interpretation for the decomposed steady-state waiting time LST.

Performance Estimation of AS/RS using M/G/1 Queueing Model with Two Queues (M/G/l 대기모델을 이용한 자동창고 시스템의 성능 평가)

  • Lee, Moon-Hwan;Lim, Si-Yeong;Hur, Sun;Lee, Young-Hae
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.10a
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    • pp.59-62
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    • 2000
  • Many of the previous researchers have been studied for the performance estimation of an AS/RS with a static model or computer simulation. Especially, they assumes that the storage/retrieval (S/R) machine performs either only single command (SC) or dual command (DC) and their requests are known in advance. However, the S/R machine performs a SC or a DC. or both or becomes idle according to the operating policy and the status of system at an arbitrary point of time. In this paper, we propose a stochastic model for the performance estimation of a unit-load AS/RS by using a M/G/1 queueing model with a single-server and two queues. Expected numbers of waiting storage and retrieval commands, and the waiting time in queues for the storage and retrieval commands are found

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A RECENT PROGRESS IN ALGORITHMIC ANALYSIS OF FIFO QUEUES WITH MARKOVIAN ARRIVAL STEAMS

  • Takine, Tetsuya
    • Journal of the Korean Mathematical Society
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    • v.38 no.4
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    • pp.807-842
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    • 2001
  • This paper summarizes recent development of analytical and algorithmical results for stationary FIFO queues with multiple Markovian arrival streams, where service time distributions are general and they may differ for different arrival streams. While this kind of queues naturally arises in considering queues with a superposition of independent phase-type arrivals, the conventional approach based on the queue length dynamics (i.e., M/G/1 pradigm) is not applicable to this kind of queues. On the contrary, the workload process has a Markovian property, so that it is analytically tractable. This paper first reviews the results for the stationary distributions of the amount of work-in-system, actual waiting time and sojourn time, all of which were obtained in the last six years by the author. Further this paper shows an alternative approach, recently developed by the author, to analyze the joint queue length distribution based on the waiting time distribution. An emphasis is placed on how to construct a numerically feasible recursion to compute the stationary queue length mass function.

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AN M/G/1 VACATION QUEUE UNDER THE $P_{\lambda}^M-SERVICE$ POLICY

  • Lee, Ji-Yeon
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.285-297
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    • 2007
  • We consider the $P_{\lambda}^M-service$ policy for an M/G/1 queueing system in which the workload is monitored randomly at discrete points in time. If the level of the workload exceeds a threshold ${\lambda}$ when it is monitored, then the service rate is increased from 1 to M instantaneously and is kept as M until the workload reaches zero. By using level-crossing arguments, we obtain explicit expressions for the stationary distribution of the workload in the system.

Estimation of the Expected Time in System of Trip-Based Material Handling Systems (트립에 기초한 물자취급 시스템에서 자재의 평균 체류시간에 대한 추정)

  • Cho, Myeon-Sig
    • Journal of Korean Institute of Industrial Engineers
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    • v.21 no.2
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    • pp.167-181
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    • 1995
  • We develop an analytical model to estimate the time a workpiece spends in both input and output queues in trip-based material handling systems. The waiting times in the input queues are approximated by M/G/1 queueing system and the waiting times in the output queues are estimated using the method discussed in Bozer, Cho, and Srinivasan [2]. The analytical results are tested via simulation experiment. The result indicates that the analytical model estimates the expected waiting times in both the input and output queues fairly accurately. Furthermore, we observe that a workpiece spends more time waiting for a processor than waiting for a device even if the processors and the devices are equally utilized. It is also noted that the expected waiting time in the output queue with fewer faster devices is shorter than that obtained with multiple slower devices.

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