• Title/Summary/Keyword: Markov Chain Model

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Assessment of the ENSO Impact on Frequency and Spatial Distribution of Rainfall in South Korea (ENSO가 우리나라 강우의 확률빈도와 공간분포에 미치는 영향)

  • Kim, Soo Jun;Kim, Byung Sik;Kim, Hung Soo
    • Journal of Wetlands Research
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    • v.10 no.2
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    • pp.143-153
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    • 2008
  • The purpose of this paper is to evaluate impacts of ENSO on frequency and spatial distribution of rainfall in South Korea. In this paper, First, rainfall data in 60 climate stations were categorized into Warm(El Nino), Cold(La Nina), Normal episodes based on the Cold & Warm Episodes by Season, then 100 years of daily rainfall data were generated for each episodic events(El Nino, La Nina, Normal) using Markov Chain model. Finally, Estimating frequency based flood and comparison for each episodes were conducted. From the results, it shows that there are significant changes in the rainfall frequency and the spatial distribution of rainfall among Warm(EL Nino), Cold(La Nina) and Normal episodes.

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Markov Chain Model-Based Trainee Behavior Pattern Analysis for Assessment of Information Security Exercise Courses (정보보안 훈련 시스템의 성취도 평가를 위한 마코브 체인 모델 기반의 학습자 행위 패턴 분석)

  • Lee, Taek;Kim, Do-Hoon;Lee, Myong-Rak;In, Hoh Peter
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.12
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    • pp.1264-1268
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    • 2010
  • In this paper, we propose a behavior pattern analysis method for users tasking on hands-on security exercise missions. By analysing and evaluating the observed user behavior data, the proposed method discovers some significant patterns able to contribute mission successes or fails. A Markov chain modeling approach and algorithm is used to automate the whole analysis process. How to apply and understand our proposed method is briefly shown through a case study, "network service configurations for secure web service operation".

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

  • 홍석원
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.3
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    • pp.549-555
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    • 2000
  • We propose an approximate algorithm to analyze the queuing system with n bursty and heterogeneous arrival processes. Each input process is modeled by Interrupted Bernoulli Process(IBP). We approximate N arrival processes by a single state variable and subsequently simplify the transition probability matrix of the Markov chain associated with these N arrival processes. Using this single state variable of arrival processes, we describe the state of the queuing system and analyze the system numerically with the reduced transition probability matrix. We compute the queue length distribution, the delay distribution, and the loss probability. Comparisons with simulation data show that the approximation algorithm has a good accuracy.

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Reliability Analysis Under Input Variable and Metamodel Uncertainty Using Simulation Method Based on Bayesian Approach (베이지안 접근법을 이용한 입력변수 및 근사모델 불확실성 하에 서의 신뢰성 분석)

  • An, Da-Wn;Won, Jun-Ho;Kim, Eun-Jeong;Choi, Joo-Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.10
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    • pp.1163-1170
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    • 2009
  • Reliability analysis is of great importance in the advanced product design, which is to evaluate reliability due to the associated uncertainties. There are three types of uncertainties: the first is the aleatory uncertainty which is related with inherent physical randomness that is completely described by a suitable probability model. The second is the epistemic uncertainty, which results from the lack of knowledge due to the insufficient data. These two uncertainties are encountered in the input variables such as dimensional tolerances, material properties and loading conditions. The third is the metamodel uncertainty which arises from the approximation of the response function. In this study, an integrated method for the reliability analysis is proposed that can address all these uncertainties in a single Bayesian framework. Markov Chain Monte Carlo (MCMC) method is employed to facilitate the simulation of the posterior distribution. Mathematical and engineering examples are used to demonstrate the proposed method.

Performance Analysis of Directional CSMA/CA for IEEE 802.15.3c under Saturation Environments

  • Kim, Mee-Joung;Kim, Yong-Sang;Lee, Woo-Yong
    • ETRI Journal
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    • v.34 no.1
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    • pp.24-34
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    • 2012
  • In this paper, the directional carrier sense multiple access/collision avoidance (CSMA/CA) protocol in the immediate acknowledgement mode for IEEE 802.15.3c is analyzed under saturation environments. For the analysis, a sensing region and an exclusive region with a directional antenna are computed probabilistically and a Markov chain model in which the features of IEEE 802.15.3c and the effects of using directional antennas are incorporated is analyzed. An algorithm to find the maximal number of concurrently transmittable frames is proposed. The system throughput and the average transmission delay are obtained in closed forms. The numerical results show the impact of directional antennas on the CSMA/CA media access control (MAC) protocol. For instance, the throughput with a small beamwidth of antenna is more than ten times larger than that for an omnidirectional antenna. The overall analysis is verified by a simulation. The obtained results will be helpful in developing an MAC protocol for enhancing the performance of mmWave wireless personal area networks.

Medium Access Control Protocol for Ad Hoc Networks Using Dynamic Contention Window (동적 경쟁윈도우를 이용한 Ad Hoc 망에서의 Medium Access Control 프로토콜)

  • Ahn, Hong-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.35-42
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    • 2008
  • Since Bianchi's 2-D Markov Chain Model considers collision problem only in ideal channel condition, it does not reflect real channel impaired by fading, interference, and noise. Distributed Coordination Function(DCF) doubles its contention window(CW) when transmission fails regardless of collision or transmission error. Increase of CW caused by transmission error degrade throughput and increase the delay. In this paper, we present quantitative analysis of the impact of the parameters such as contention window size(CW), transmission probability for a given time slot(${\Im}$), transmission failure probability($p_f$), on the system performance and provide a method how to decrease the initial CW to achieve equivalent performance.

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A Multi-Priority Service Differentiated and Adaptive Backoff Mechanism over IEEE 802.11 DCF for Wireless Mobile Networks

  • Zheng, Bo;Zhang, Hengyang;Zhuo, Kun;Wu, Huaxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.7
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    • pp.3446-3464
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    • 2017
  • Backoff mechanism serves as one of the key technologies in the MAC-layer of wireless mobile networks. The traditional Binary Exponential Backoff (BEB) mechanism in IEEE 802.11 Distributed Coordination Function (DCF) and other existing backoff mechanisms poses several performance issues. For instance, the Contention Window (CW) oscillations occur frequently; a low delay QoS guarantee cannot be provided for real-time transmission, and services with different priorities are not differentiated. For these problems, we present a novel Multi-Priority service differentiated and Adaptive Backoff (MPAB) algorithm over IEEE 802.11 DCF for wireless mobile networks in this paper. In this algorithm, the backoff stage is chosen adaptively according to the channel status and traffic priority, and the forwarding and receding transition probability between the adjacent backoff stages for different priority traffic can be controlled and adjusted for demands at any time. We further employ the 2-dimensional Markov chain model to analyze the algorithm, and derive the analytical expressions of the saturation throughput and average medium access delay. Both the accuracy of the expressions and the algorithm performance are verified through simulations. The results show that the performance of the MPAB algorithm can offer a higher throughput and lower delay than the BEB algorithm.

Self-Networking and Replaceable Structure for Ubiquitous Multimedia Contents (유비쿼터스 멀티미디어 컨텐츠의 자기 네트워킹과 대체 구조에 대한 연구)

  • Jeong, Gu-Min;Park, Kyung-Joon;Ka, Chung-Hee;Ahn, Hyun-Sik;Moon, Chan-Woo
    • Journal of the Institute of Convergence Signal Processing
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    • v.8 no.4
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    • pp.244-248
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    • 2007
  • In this paper, we propose a novel self-networking and replaceable structure method for the ubiquitous multimedia. As the contents in the ubiquitous multimedia should be realistic and continuously updated in the real-time manner, an efficient scheme of a self-networking and replaceable structure is necessary. In the proposed method, the contents itself connects to the server or corresponding devices and updates itself autonomously. Also, we can reduce the total amount of data transmission comparing to the cases where the whole contents should be downloaded. A Markov chain model is introduced for the proposed structure in order to perform the throughput analysis. The whole mechanism is implemented in the wireless handset and also, various applications of the scheme are discussed.

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Delay characteristics of speech packets in virtual cellular network(VCN) (가상 셀룰라 망(VCN)에서의 음성 패킷 지연 특성)

  • 정명순;김화종
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.23 no.9A
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    • pp.2305-2312
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    • 1998
  • This paper analyzed the delay characteristics of speech packets in virtual cellular network(VCN). The probability distribution of packet delay is obtained using the markov chain model when periodic speech packets are transmitted by slotted-ALOHA protocol. The effects of probility of capture and retransmission policy on the performance were also analyzed. At first, the probability cumulative function of packet delay is calculated from the probability of capture as a function of location of mobile terminal. In order to investigate the effects of backoff delay, we defined a parameter NPr, where N is the period (frame size) of the speech packets and Pr is the retransmission probability for each speech packet. We also obtained the 1% outage delay for various frame size N.

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Prediction of extreme rainfall with a generalized extreme value distribution (일반화 극단 분포를 이용한 강우량 예측)

  • Sung, Yong Kyu;Sohn, Joong K.
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.857-865
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    • 2013
  • Extreme rainfall causes heavy losses in human life and properties. Hence many works have been done to predict extreme rainfall by using extreme value distributions. In this study, we use a generalized extreme value distribution to derive the posterior predictive density with hierarchical Bayesian approach based on the data of Seoul area from 1973 to 2010. It becomes clear that the probability of the extreme rainfall is increasing for last 20 years in Seoul area and the model proposed works relatively well for both point prediction and predictive interval approach.