• Title/Summary/Keyword: Discrete-time Markov Chain

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DISCRETE-TIME BULK-SERVICE QUEUE WITH MARKOVIAN SERVICE INTERRUPTION AND PROBABILISTIC BULK SIZE

  • Lee, Yu-Tae
    • Journal of applied mathematics & informatics
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    • v.28 no.1_2
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    • pp.275-282
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    • 2010
  • This paper analyzes a discrete-time bulk-service queue with probabilistic bulk size, where the service process is interrupted by a Markov chain. We study the joint probability generating function of system occupancy and the state of the Markov chain. We derive several performance measures of interest, including average system occupancy and delay distribution.

Analysis of Real-time Error for Remote Estimation Based on Binary Markov Chain Model (이진 마르코프 연쇄 모형 기반 실시간 원격 추정값의 오차 분석)

  • Lee, Yutae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.317-320
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    • 2022
  • This paper studies real-time error in the context of monitoring a symmetric binary information source over a delay system. To obtain the average real-time error, the delay system is modeled and analyzed as a discrete time Markov chain with a finite state space. Numerical analysis is performed on various system parameters such as state transition probabilities of information source, transmission times, and transmission frequencies. Given state transition probabilities and transmission times, we investigate the relationship between the transmission frequency and the average real-time error. The results can be used to investigate the relationship between real-time errors and age of information.

Analysis of Real-time Error for Geo/D/1/1 Model (Geo/D/1/1 모형에서의 실시간 원격 추정값의 오차 분석)

  • Yutae, Lee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.27 no.1
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    • pp.135-138
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    • 2023
  • In this paper, we study real-time error in the context of monitoring a binary information source through a delay system. To derive the average real-time error, we model the delay system as a discrete time Geo/D/1/1 queueing model. Using a discrete time three-dimensional Markov chain with finite state space, we analyze the queueing model. We also perform some numerical analysis on various system parameters: state transition probabilities of binary information source; transmission times; and transmission frequencies. When the state changes of the information source are positively correlated and negatively correlated, we investigate the relationship between transmission time and transmission frequency.

MARKOVIAN EARLY ARRIVAL DISCRETE TIME JACKSON NETWORKS

  • Aboul-Hassan A.;Rabia S.I.
    • Journal of the Korean Statistical Society
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    • v.35 no.3
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    • pp.281-303
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    • 2006
  • In an earlier work, we investigated the problem of using linear programming to bound performance measures in a discrete time Jackson network. There it was assumed that the system evolution is controlled by the early arrival scheme. This assumption implies that the system can't be modelled by a Markov chain. This problem was resolved and performance bounds were calculated. In the present work, we use a modification of the early arrival scheme (without corrupting it) in order to make the system evolves as a Markov chain. This modification enables us to obtain explicit expressions for certain moments that could not be calculated explicitly in the pure early arrival scheme setting. Moreover, this feature implies a reduction in the linear program size as well as the computation time. In addition, we obtained tighter bounds than those appeared before due to the new setting.

Numerical Iteration for Stationary Probabilities of Markov Chains

  • Na, Seongryong
    • Communications for Statistical Applications and Methods
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    • v.21 no.6
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    • pp.513-520
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    • 2014
  • We study numerical methods to obtain the stationary probabilities of continuous-time Markov chains whose embedded chains are periodic. The power method is applied to the balance equations of the periodic embedded Markov chains. The power method can have the convergence speed of exponential rate that is ambiguous in its application to original continuous-time Markov chains since the embedded chains are discrete-time processes. An illustrative example is presented to investigate the numerical iteration of this paper. A numerical study shows that a rapid and stable solution for stationary probabilities can be achieved regardless of periodicity and initial conditions.

A Novel Spectrum Access Strategy with ${\alpha}$-Retry Policy in Cognitive Radio Networks: A Queueing-Based Analysis

  • Zhao, Yuan;Jin, Shunfu;Yue, Wuyi
    • Journal of Communications and Networks
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    • v.16 no.2
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    • pp.193-201
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    • 2014
  • In cognitive radio networks, the packet transmissions of the secondary users (SUs) can be interrupted randomly by the primary users (PUs). That is to say, the PU packets have preemptive priority over the SU packets. In order to enhance the quality of service (QoS) for the SUs, we propose a spectrum access strategy with an ${\alpha}$-Retry policy. A buffer is deployed for the SU packets. An interrupted SU packet will return to the buffer with probability ${\alpha}$ for later retrial, or leave the system with probability (1-${\alpha}$). For mathematical analysis, we build a preemptive priority queue and model the spectrum access strategy with an ${\alpha}$-Retry policy as a two-dimensional discrete-time Markov chain (DTMC).We give the transition probability matrix of the Markov chain and obtain the steady-state distribution. Accordingly, we derive the formulas for the blocked rate, the forced dropping rate, the throughput and the average delay of the SU packets. With numerical results, we show the influence of the retrial probability for the strategy proposed in this paper on different performance measures. Finally, based on the trade-off between different performance measures, we construct a cost function and optimize the retrial probabilities with respect to different system parameters by employing an iterative algorithm.

Priority MAC based on Multi-parameters for IEEE 802.15.7 VLC in Non-saturation Environments

  • Huynh, Vu Van;Le, Le Nam-Tuan;Jang, Yeong-Min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.3C
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    • pp.224-232
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    • 2012
  • Priority MAC is an important issue in every communication system when we consider differentiated service applications. In this paper, we propose a mechanism to support priority MAC based on multi-parameters for IEEE 802.15.7 visible light communication (VLC). By using three parameters such as number of backoff times (NB), backoff exponent (BE) and contention window (CW), we provide priority for multi-level differentiated service applications. We consider beacon-enabled VLC personal area network (VPAN) mode with slotted version for random access algorithm in this paper. Based on a discrete-time Markov chain, we analyze the performance of proposed mechanism under non-saturation environments. By building a Markov chain model for multi-parameters, this paper presents the throughput and transmission delay time for VLC system. Numerical results show that we can apply three parameters to control the priority for VLC MAC protocol.

DISCRETE-TIME BUFFER SYSTEMS WITH SESSION-BASED ARRIVALS AND MARKOVIAN OUTPUT INTERRUPTIONS

  • Kim, Jeongsim
    • Journal of applied mathematics & informatics
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    • v.33 no.1_2
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    • pp.185-191
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    • 2015
  • This paper considers a discrete-time buffer system with session-based arrivals, an infinite storage capacity and one unreliable output line. There are multiple different types of sessions and the output line is governed by a finite state Markov chain. Based on a generating functions approach, we obtain an exact expression for the mean buffer content.

Parallel Gaussian Processes for Gait and Phase Analysis (보행 방향 및 상태 분석을 위한 병렬 가우스 과정)

  • Sin, Bong-Kee
    • Journal of KIISE
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    • v.42 no.6
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    • pp.748-754
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    • 2015
  • This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.