• Title/Summary/Keyword: Multi-server Queue

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AN APPROXIMATION FOR THE QUEUE LENGTH DISTRIBUTION IN A MULTI-SERVER RETRIAL QUEUE

  • Kim, Jeongsim
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.1
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    • pp.95-102
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    • 2016
  • Multi-server queueing systems with retrials are widely used to model problems in a call center. We present an explicit formula for an approximation of the queue length distribution in a multi-server retrial queue, by using the Lerch transcendent. Accuracy of our approximation is shown in the numerical examples.

Stochastic Upper Bound for the Stationary Queue Lengths of GPS Servers

  • Kim, Sung-Gon
    • The Korean Journal of Applied Statistics
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    • v.22 no.3
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    • pp.541-551
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    • 2009
  • Generalized processor sharing(GPS) service policy is a scheduling algorithm to allocate the bandwidth of a queueing system with multi-class input traffic. In a queueing system with single-class traffic, the stationary queue length becomes larger stochastically when the bandwidth (i.e. the service rate) of the system decreases. For a given GPS server, we consider the similar problem to this. We define the monotonicity for the head of the line processor sharing(HLPS) servers in which the units in the heads of the queues are served simultaneously and the bandwidth allocated to each queue are determined by the numbers of units in the queues. GPS is a type of monotonic HLPS. We obtain the HLPS server whose queue length of a class stochastically bounds upper that of corresponding class in the given monotonic HLPS server for all classes. The queue lengths process of all classes in the obtained HLPS server has the stationary distribution of product form. When the given monotonic HLPS server is GPS server, we obtain the explicit form of the stationary queue lengths distribution of the bounding HLPS server. Numerical result shows how tight the stochastic bound is.

An Inference Method of a Multi-server Queue using Arrival and Departure Times (도착 및 이탈시점을 이용한 다중서버 대기행렬 추론)

  • Park, Jinsoo
    • Journal of the Korea Society for Simulation
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    • v.25 no.3
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    • pp.117-123
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    • 2016
  • This paper presents inference methods for inner operations of a multi-server queue when historical data are limited or system observation is restricted. In a queueing system analysis, autocorrelated arrival and service processes increase the complexity of modeling. Accordingly, numerous analysis methods have been developed. In this paper, we introduce an inference method for specific situations when external observations exhibit autocorrelated structure and and observations of internal operations are difficult. We release an assumption of the previous method and provide lemma and theorem to guarantee the correctness of our proposed inference method. Using only external observations, our proposed method deduces the internal operation of a multi-server queue via non-parametric approach even when the service times are autocorrelated. The main internal inference measures are waiting times and service times of respective customers. We provide some numerical results to verify that our method performs as intended.

ANALYSIS OF M/M/c RETRIAL QUEUE WITH THRESHOLDS, PH DISTRIBUTION OF RETRIAL TIMES AND UNRELIABLE SERVERS

  • CHAKRAVARTHY, SRINIVAS R.;OZKAR, SERIFE;SHRUTI, SHRUTI
    • Journal of applied mathematics & informatics
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    • v.39 no.1_2
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    • pp.173-196
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    • 2021
  • This paper treats a retrial queue with phase type retrial times and a threshold type-policy, where each server is subject to breakdowns and repairs. Upon a server failure, the customer whose service gets interrupted will be handed over to another available server, if any; otherwise, the customer may opt to join the retrial orbit or depart from the system according to a Bernoulli trial. We analyze such a multi-server retrial queue using the recently introduced threshold-based retrial times for orbiting customers. Applying the matrix-analytic method, we carry out the steady-state analysis and report a few illustrative numerical examples.

QUEUE LENGTH DISTRIBUTION IN A QUEUE WITH RELATIVE PRIORITIES

  • Kim, Jeong-Sim
    • Bulletin of the Korean Mathematical Society
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    • v.46 no.1
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    • pp.107-116
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    • 2009
  • We consider a single server multi-class queueing model with Poisson arrivals and relative priorities. For this queue, we derive a system of equations for the transform of the queue length distribution. Using this system of equations we find the moments of the queue length distribution as a solution of linear equations.

Simulation for Efficient Employment of JLBS (JLBS의 효율적인 운용을 위한 시뮬레이션)

  • 남동진;한영신;이칠기
    • Proceedings of the Korea Society for Simulation Conference
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    • 2002.05a
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    • pp.183-187
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    • 2002
  • JLBS는 multi-server multi-queue 방식을 채택하고 있으며, 각 tool별로 할당된 license 수에 비례하여 system을 할당한다. 그러나 이러한 방식의 문제점은 특정 tool에만 job이 집중될 경우 비효율적이다. 즉 특정 system은 모두 사용되고 있고, queue에는 많은 job이 대기하고, 여타 tool에 해당하는 queue에는 대기하는 job이 없어서 system이 그냥 놀고 있는 현상이 발생한다. 본 논문에서는 이러한 단점을 극복하기 위해 각 tool에 license수에 비례하여 할당되었던 system을 모든 tool들이 system을 공유할 수 있도록 하는 방법을 제안했다. 대신 system의 숫자는 줄이고, license의 숫자는 더 할당하는 방법으로, 기존의 방법보다 더 효율적으로 나타났다.

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A Study on the Service Rates of M/M/s Multi-server Demanding Queues (Multi-server Demanding M/M/s 대기행렬의 Service Rate 변화곡선에 관한 연구)

  • Kim, Seong-Sik;Jang, Jin-Ik
    • Journal of Korean Institute of Industrial Engineers
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    • v.6 no.1
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    • pp.1-7
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    • 1980
  • An exact solution technique for M/M/s multi-server demanding queue is introduced, and a general form of the curves representing service rates of the system is presented. As the number of customers in the system increases, the service rate is shown to increase initially, then decrease, and finally converge to a certain value. It is also shown that this phenomenon persists regardless of the numbers of servers and customer types.

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M/M/2 system with two customer classes and exclusive server (전용서버가 있는 이계층고객 M/M/2 대기모형)

  • Jung, Jae-Ho;Hur, Sun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.25 no.5
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    • pp.31-38
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    • 2002
  • In this paper, we model a two-server queueing system with priority, to which we put a restriction on the number of servers for each customer class. customers are divided into two different classes. Class 1 customers have non-preemptive priority over class 2 customers. They are served by both servers when available but class 2 customers are served only by a designated server. We use a method of generating function depending on the state of servers. We find the generating function of the number of customers in queue, server utilization, mean queue length and mean waiting time for each class of customers.

On the Discrete-Time Version of the Distributional Little's Law (이산시간 대기행렬시스템에 대한 분포적 Little의 법칙의 활용)

  • Kim, Nam-Ki;Chae, Kyung-Chul
    • Journal of Korean Institute of Industrial Engineers
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    • v.27 no.4
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    • pp.374-378
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    • 2001
  • We present a discrete-time version of the distributional Little's law, of which the continuous-time version is well known. Then we extend it to the queue in which two or more customers may depart at the same time. As a demonstration, we apply this law to various discrete-time queues such as the standard Geom/G/1 queue, the Geom/G/1 queue with vacations, the multi-server Geom/D/c queue, and the bulk-service Geom/$G^b$/1 queue. As a result, we obtain the probability generating functions of the numbers in system/queue and the waiting times in system/queue for those queues.

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D-MAP 도착과정을 갖는 이산시간 대기행렬모형에서의 분포적 Little의 법칙과 D-MAP/D/c 모형에의 응용

  • Kim Nam-Gi
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1101-1103
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    • 2006
  • For a broad class of discrete-time FIFO queueing systems with D-MAP (discrete-time Markovian arrival process) arrivals, we present a distributional Little's law that relates the distribution of the stationary number of customers in system (queue) with that of the stationary number of slots a customer spends in system (queue). Taking the multi-server D-MAP/D/c queue for example, we illustrate how to utilize this relation to get the desired distribution of the number of customers.

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