• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.803-816
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• 1996

It is possible to prevent deadlock if the priority which is conventionally given to transactions is endowed to data items and the transactions with the highest priority among transactions accessing the data item is allowed to proceed. Based on this observation, we proposed a Data-Priority Based Locking Protocol(DPLP) and evaluated its performance against known locking protocols in Real Time Database Management System(RTDBMS). Transaction inter-arrival time(IAT) was varied to determine success ratio, average-lateness, confict ratio and restart ratio, In these simulations we verified that the proposed DPLP performs better than the other protocols.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.19-28
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• 2017

Moments of stationary intervals and those of the counting process can be used for moment fittings of the point processes. As for the Markovian arrival processes, the moments of stationary intervals are given as a polynomial function of parameters whereas the moments of the counting process involve exponential terms. Therefore, moment fittings are more complicated with the counting process than with stationary intervals. However, in queueing network analysis, cross-correlation between point processes can be modeled more conveniently with counting processes than with stationary intervals. A Laplace-Stieltjies transform of the stationary intervals of MAP (3)s is recently proposed in minimal number of parameters. We extend the results and present the Laplace transform of the counting process of MAP (3)s. We also show how moments of the counting process such as index of dispersions for counts, IDC, and limiting IDC can be used for moment fittings. Examples of exact MAP (3) moment fittings are also presented on the basis of moments of stationary intervals and those of the counting process.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.47-61
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• 1996

An ATM switch must deal with various kinds of input sources having different traffic characteristics and it must guarantee very small value of cel loss probability, about 10$^{8}$ -10$^{12}$ , to deal with loss-sensitive traffics. In order to estimate such a rate event probability with simulation procedure, a variance reduction technique is essential for obtaining an appropriate level of precision with reduced cost. In this paper, we propose a hybrid simulation technique to achieve reduction of variance of cell loss probability estimator, where hybrid means the combination of analytical method and simulation procedure. A discrete time queueing model with multiple input sources and a finite shared buffer is considered, where the arrival process at an input source and a finite shared buffer is considered, where the arrival process at an input source is governed by an Interrupted Bernoulli Process and the service rate is constant. We deal with heterogeneous input sources as well as homogeneous case. The performance of the proposed hybrid simulation estimator is compared with those of the raw simulation estimator and the importance sampling estimator in terms of variance reduction ratios.

• Korean Management Science Review
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• v.32 no.2
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• pp.69-78
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• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.131-142
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• 2016

We consider a multi-server queueing system without buffer and with two types of customers as a model of operation of a mobile network cell. Customers arrive at the system in the marked Markovian arrival flow. The service times of customers are exponentially distributed with parameters depending on the type of customer. A part of the available servers is reserved exclusively for service of first type customers. Customers who do not receive service upon arrival, can make repeated attempts. The system operation is influenced by random factors, leading to a change of the system parameters, including the total number of servers and the number of reserved servers. The behavior of the system is described by the multi-dimensional Markov chain. The generator of this Markov chain is constructed and the ergodicity condition is derived. Formulas for computation of the main performance measures of the system based on the stationary distribution of the Markov chain are derived. Numerical examples are presented.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.44-52
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• 2016

The departure flow management is the planning tool to optimize the schedule of the departure aircraft and allows them to join smoothly into the overhead traffic flow. To that end, the arrival time prediction to the merge point for the cruising aircraft is necessary to determined. This paper proposes a trajectory prediction model for the cruising aircraft based on the machine learning approach. The proposed method includes the trajectory vectored from the procedural route and is applied to the historical data to evaluate the prediction performances.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.17-20
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• 1998

The purpose of this paper is to develop a port simulation program for Inchon Port. The arrival and departure data from Inchon Port are analyzed, several probability density functions for the interval time and service time are estimated, and the berthing rules are constructed based on experts experiences. The port simulation program is written in visual basic considering the interarrival p.d.f., service rate p.d.f., berthing rules, and dual-dock system, and is used to analyze the effects of the changes in ship arrival rate and service rate upon the demurrage. It is expected that we can use the simulation results in order to prepare proper service level and to evaluate the appropriate investment strategy to be planned.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.639-647
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• 2020

In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1564-1571
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• 2022

Wireless sensor network(WSN) is being used in various fields such as reconnaissance, echelon scale identification, weather observation, etc. using small sensors in an environment without a network infrastructure environment. In addition, WSN uses limited battery power, so study on routing protocols to extend the lifetime of the network is important. PEGASIS, a hierarchical routing protocol, accounts for the majority of energy-efficient routing protocol studies and is well known as a representative protocol. In this study, based on PEGASIS, we propose a protocol that constructs multiple chains rather than one chain using the AoA of nodes. The proposed protocol has the advantage of reducing the transmission distance of nodes and eliminating unnecessary transmissions, thereby increasing energy efficiency compared to the existing protocols.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1133-1136
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• 2005

Markovian Service Process(MSP)는 기존의 Markovian Arrival Process(MAP)에서 사용하던 위상 개념을 고객의 서비스 과정에 대응시킨 모형이다. 이는 서버의 상태에 따라 달라질 수 있는 서비스 상태를 위상 변화에 대응시키는 모형이다. 본 논문에서는 대기행렬 모형의 중요한 성능 척도인 고객 수 분포에 관하여 임의시점, 고객 도착 직전 시점, 고객 이탈 직후 시점에서의 관계식을 유도한다.