• 제목/요약/키워드: Markov Arrival Process

검색결과 41건 처리시간 0.025초

Performance Evaluation of the WiMAX Network Based on Combining the 2D Markov Chain and MMPP Traffic Model

  • Saha, Tonmoy;Shufean, Md. Abu;Alam, Mahbubul;Islam, Md. Imdadul
    • Journal of Information Processing Systems
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    • 제7권4호
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    • pp.653-678
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    • 2011
  • WiMAX is intended for fourth generation wireless mobile communications where a group of users are provided with a connection and a fixed length queue. In present literature traffic of such network is analyzed based on the generator matrix of the Markov Arrival Process (MAP). In this paper a simple analytical technique of the two dimensional Markov chain is used to obtain the trajectory of the congestion of the network as a function of a traffic parameter. Finally, a two state phase dependent arrival process is considered to evaluate probability states. The entire analysis is kept independent of modulation and coding schemes.

Waiting Times in Polling Systems with Markov-Modulated Poisson Process Arrival

  • Kim, D. W.;W. Ryu;K. P. Jun;Park, B. U.;H. D. Bae
    • Journal of the Korean Statistical Society
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    • 제26권3호
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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.

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Application of GTH-like algorithm to Markov modulated Brownian motion with jumps

  • Hong, Sung-Chul;Ahn, Soohan
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.477-491
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    • 2021
  • The Markov modulated Brownian motion is a substantial generalization of the classical Brownian Motion. On the other hand, the Markovian arrival process (MAP) is a point process whose family is dense for any stochastic point process and is used to approximate complex stochastic counting processes. In this paper, we consider a superposition of the Markov modulated Brownian motion (MMBM) and the Markovian arrival process of jumps which are distributed as the bilateral ph-type distribution, the class of which is also dense in the space of distribution functions defined on the whole real line. In the model, we assume that the inter-arrival times of the MAP depend on the underlying Markov process of the MMBM. One of the subjects of this paper is introducing how to obtain the first passage probabilities of the superposed process using a stochastic doubling algorithm designed for getting the minimal solution of a nonsymmetric algebraic Riccatti equation. The other is to provide eigenvalue and eigenvector results on the superposed process to make it possible to apply the GTH-like algorithm, which improves the accuracy of the doubling algorithm.

MAP/G/1/K QUEUE WITH MULTIPLE THRESHOLDS ON BUFFER

  • Choi, Doo-Il
    • 대한수학회논문집
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    • 제14권3호
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    • pp.611-625
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    • 1999
  • We consider ΜΑΡ/G/ 1 finite capacity queue with mul-tiple thresholds on buffer. The arrival of customers follows a Markov-ian arrival process(MAP). The service time of a customer depends on the queue length at service initiation of the customer. By using the embeded Markov chain method and the supplementary variable method, we obtain the queue length distribution ar departure epochs and at arbitrary epochs. This gives the loss probability and the mean waiting time by Little's law. We also give a simple numerical examples to apply the overload control in packetized networks.

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MMAP 이산시간 큐잉 시스템의 속산 시뮬레이션 (An Efficient Simulation of Discrete Time Queueing Systems with Markov-modulated Arrival Processes)

  • 국광호;강성열
    • 한국시뮬레이션학회논문지
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    • 제13권3호
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    • pp.1-10
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    • 2004
  • The cell loss probability required in the ATM network is in the range of 10$^{-9}$ ∼10$^{-12}$ . If Monte Carlo simulation is used to analyze the performance of the ATM node, an enormous amount of computer time is required. To obtain large speed-up factors, importance sampling may be used. Since the Markov-modulated processes have been used to model various high-speed network traffic sources, we consider discrete time single server queueing systems with Markov-modulated arrival processes which can be used to model an ATM node. We apply importance sampling based on the Large Deviation Theory for the performance evaluation of, MMBP/D/1/K, ∑MMBP/D/1/K, and two stage tandem queueing networks with Markov-modulated arrival processes and deterministic service times. The simulation results show that the buffer overflow probabilities obtained by the importance sampling are very close to those obtained by the Monte Carlo simulation and the computer time can be reduced drastically.

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ANALYSIS OF A QUEUEING SYSTEM WITH OVERLOAD CONTROL BY ARRIVAL RATES

  • CHOI DOO IL
    • Journal of applied mathematics & informatics
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    • 제18권1_2호
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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.

다수의 이질적 IBP/D/1큐잉 모형의 분석을 위한 근사 알고리즘 (An Approximate algorithm for the analysis of the n heterogeneous IBP/D/l queuing model)

  • 홍석원
    • 한국정보통신학회논문지
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    • 제4권3호
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    • pp.549-555
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    • 2000
  • 본 논문에서는 n개의 버스트 입력 트래픽을 처리하는 이산 시간 큐잉 모형을 분석하기 위한 근사 계산 알고리즘을 제안한다. 입력되는 각각의 버스트 트래픽은 IBP(Interrupted Bernoulli Process)로 모형화된다. 이 알고리즘은 n 개의 입력 프로세스를 하나의 상태 변수로 표시하여 n 개의 입력 프로세스로 표현된 마코프 체인(Markov Chain)의 확률 전이 상태를 단순화한다. 이렇게 단순화된 하나의 상태 변수를 이용하여 큐잉모형의 상태 전이를 표현하고 이를 완전 수치 계산에 의해 해를 구한다. 이러한 절차를 통해 구한 큐 길이, 대기 시간 분포를 시뮬레이션에 의해 구한 값과 비교하여 알고리즘의 타당성을 검증한다.

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Performance Analysis of an ATM Multiplexer with Multiple QoS VBR Traffic

  • Kim, Young-Jin;Kim, Jang-Kyung
    • ETRI Journal
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    • 제19권1호
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    • pp.13-25
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    • 1997
  • In this paper, we propose a new queuing model, MMDP/MMDP/1/K, for an asynchronous transfer mode(ATM) multiplexer with multiple quality of service(QoS) variable bit rate (VBR) traffic in broadband-integrated services digital network (B-ISDN). We use the Markov Modulated Deterministic Process(MMDP) to approximate the actual arrival process and another MMDP for service process Using queuing analysis, we derive a formula for the cell loss probability of the ATM multiplexer in terms of the limiting probabilities of a Markov chain. The cell loss probability can be used for connection admission control in ATM multiplexer and the calculation of equivalent bandwidth for arrival traffic, The major advantages of this approach are simplicity in analysis, accuracy of analysis by comparison of simulation, and numerical stability.

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통신 서비스 가용도의 추계적 모델 (Stochastic Model for Telecommunication Service Availability)

  • 함영만;이강원
    • 한국통신학회논문지
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    • 제37권1B호
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    • pp.50-58
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    • 2012
  • 본 연구의 주된 목적은 사용자 관점에서 본 통신 시스템 서비스 가용도의 이론적 모델 개발이다. 이를 위하여 호(Call) 도착은 non-homogeneous 포아손 과정의 가정, 그리고 시스템 상태는 CTMC 모델의 가정을 토대로 서비스 가용도의 추계적 모델을 개발하였다. 제시한 모델은 시간에 따라 변하는 호 도착률을 포함하여 사용자 관점에서 본 서비스 신뢰도 모형의 사용자 모델을 효율적으로 나타냈다. 아울러 시스템 자원의 고장 없이도 사용자가 서비스를 받지 못하는 시스템 상태인 운영 고장 상태를 모델에 포함하여 제공자 입장이 아니라 사용자 관점에서 모델을 구축하였다.

마코비안 도착과정을 이용한 축구경기 득점결과의 예측 (Predicting the Score of a Soccer Match by Use of a Markovian Arrival Process)

  • 김남기;박현민
    • 산업공학
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    • 제24권4호
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    • pp.323-329
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    • 2011
  • We develop a stochastic model to predict the score of a soccer match. We describe the scoring process of the soccer match as a markovian arrival process (MAP). To do this, we define a two-state underlying Markov chain, in which the two states represent the offense and defense states of the two teams to play. Then, we derive the probability vector generating function of the final scores. Numerically inverting this generating function, we obtain the desired probability distribution of the scores. Sample numerical examples are given at the end to demonstrate how to utilize this result to predict the final score of the match.