• Title/Summary/Keyword: Discrete-time Batch Markovian Arrival Process(D-BMAP)

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Waiting Time Analysis of Discrete-Time BMAP/G/1 Queue Under D-policy (D-정책을 갖는 이산시간 BMAP/G/1 대기행렬의 대기시간 분석)

  • Lee, Se Won
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.1
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    • pp.53-63
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    • 2018
  • In this paper, we analyze the waiting time of a queueing system with D-BMAP (discrete-time batch Markovian arrival process) and D-policy. Customer group or packets arrives at the system according to discrete-time Markovian arrival process, and an idle single server becomes busy when the total service time of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state waiting time distribution is derived in the form of a generating function. Mean waiting time is derived as a performance measure. Simulation is also performed for the purpose of verification and validation. Two simple numerical examples are shown.

Workload Analysis of Discrete-Time BMAP/G/1 queue under D-policy (D-정책과 집단도착을 갖는 이산시간 MAP/G/1 대기행렬시스템의 일량 분석)

  • Lee, Se Won
    • Journal of Korea Society of Industrial Information Systems
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    • v.21 no.6
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    • pp.1-12
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    • 2016
  • In this paper, we consider a general discrete-time queueing system with D-BMAP(discrete-time batch Markovian arrival process) and D-policy. An idle single server becomes busy when the total service times of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state workload distribution is derived in the form of generating function. Mean workload is derived as a performance measure. Simulation is also performed for the purpose of verification and a simple numerical example is shown.

Queue Lengths and Sojourn Time Analysis of Discrete-time BMAP/G/1 Queue under the Workload Control (일량제어정책을 갖는 이산시간 BMAP/G/1 대기행렬의 고객수와 체재시간 분석)

  • Se Won Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.1
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    • pp.63-76
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    • 2024
  • In this study, we analyzed queue length and sojourn time of discrete-time BMAP/G/1 queues under the workload control. Group customers (packets) with correlations arrive at the system following a discrete-time Markovian arrival process. The server starts busy period when the total service time of the arrived customers exceeds a predetermined workload threshold D and serves customers until the system is empty. From the analysis of workload and waiting time, distributions of queue length at the departure epoch and arbitrary time epoch and system sojourn time are derived. We also derived the mean value as a performance measure. Through numerical examples, we confirmed that we can obtain results represented by complex forms of equations, and we verified the validity of the theoretical values by comparing them with simulation results. From the results, we can obtain key performance measures of complex systems that operate similarly in various industrial fields and to analyze various optimization problems.

POWER TAIL ASYMPTOTIC RESULTS OF A DISCRETE TIME QUEUE WITH LONG RANGE DEPENDENT INPUT

  • Hwang, Gang-Uk;Sohraby, Khosrow
    • Journal of the Korean Mathematical Society
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    • v.40 no.1
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    • pp.87-107
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    • 2003
  • In this paper, we consider a discrete time queueing system fed by a superposition of an ON and OFF source with heavy tail ON periods and geometric OFF periods and a D-BMAP (Discrete Batch Markovian Arrival Process). We study the tail behavior of the queue length distribution and both infinite and finite buffer systems are considered. In the infinite buffer case, we show that the asymptotic tail behavior of the queue length of the system is equivalent to that of the same queueing system with the D-BMAP being replaced by a batch renewal process. In the finite buffer case (of buffer size K), we derive upper and lower bounds of the asymptotic behavior of the loss probability as $K\;\longrightarrow\;\infty$.