• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.107-118
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• 2007

A single-server queueing model with infinite buffer and batch arrival of customers is considered. In contrast to the standard batch arrival when a whole batch arrives into the system at one epoch, we assume that the customers of an accepted batch arrive one-by one in exponentially distributed times. Service time is exponentially distributed. Flow of batches is the stationary Poisson arrival process. Batch size distribution is geometric. The number of batches, which can be admitted into the system simultaneously, is subject of control. Analysis of the joint distribution of the number batches and customers in the system and sojourn time distribution is implemented by means of the matrix technique and method of catastrophes. Effect of control on the main performance measures of the system is demonstrated numerically.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.9-13
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• 2003

We consider a two-phase queueing system with Bernoulli feedback. Customers arrive at the system according to a Poison process and receive batch service in the first phase followed by individual services in the second phase. Each customer who completes the individual service returns to the tail of the second phase service queue with probability 1 -$\sigma$. This type of queueing problem cad be easily found in computer and telecommunication systems. By deriving a relationship between the generating functions for system size at various embedded epochs, we obtain the system size distribution. The exhaustive and gated cases for the batch service are considered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.263-267
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.289-295
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics. Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• Journal of applied mathematics & informatics
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• v.38 no.3_4
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• pp.351-373
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• 2020

There is an extensive literature on retrial queueing models. While a majority of the literature on retrial queueing models focuses on the retrial times to be exponentially distributed (so as to keep the state space to be of a reasonable size), a few papers deal with nonexponential retrial times but with some additional restrictions such as constant retrial rate, only the customer at the head of the retrial queue will attempt to capture a free server, 2-state phase type distribution, and finite retrial orbit. Generally, the retrial queueing models are analyzed as level-dependent queues and hence one has to use some type of a truncation method in performing the analysis of the model. In this paper we study a retrial queueing model with threshold-type policy for orbiting customers in the context of nonexponential retrial times. Using matrix-analytic methods we analyze the model and compare with the classical retrial queueing model through a few illustrative numerical examples. We also compare numerically our threshold retrial queueing model with a previously published retrial queueing model that uses a truncation method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.435-444
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• 1995

We propose a new approach to the calculation of the exact cells loss probability in a shared buffer ATM multiplexer, which is loaded with homogeneous discrete-time ON-OFF sources. Renewal cycles are identified in regard to the state of input sources and the buffer state on each renewal circle is modelled as a K(shared buffer size)-state Markov chain. We also analyze the behavior of queue build-up at the shared buffer whose distribution together with the steady-state probabilities of the Markov chain leads to the exact cell loss probability. Our approach to obtaining the exact cell loss probability seems to be more efficient than most of other existing ones since our underlying Markov chain has less number of states.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.19-32
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• 2018

This study focuses on an M/M/1 queue with an attached continuous-type inventory. The customers arrive into the system according to the Poisson process, and are served in their arrival order; i.e., first-come-first-served. The service times are assumed to be independent and identically distributed exponential random variable. At a service completion epoch, the customer consumes a random amount of inventory. The inventory is controlled by the traditional (s, S)-inventory policy with a generally distributed lead time. A customer that arrives during a stock-out period assumed to be lost. For the number of customers and the inventory size, we derive a product-form stationary joint probability distribution and provide some numerical examples. Besides, an operational strategy for the inventory that minimizes the long-term cost will also be discussed.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.27.2-27.2
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• 2015

Strategic plan of Subaru science and operation will be introduced. Currently, Subaru has wide variety of instruments, conducts only classical observations, with less than 5 nights allocation for each proposal. Near future, Subaru will emphasize on surveys, introduce queue mode observations, reduce the number of instruments, and concentrate on large size programs. Large surveys are called Subaru Strategic Programs (SSPs). HSC-SSP is on-going (300 nights for 5 years), PFS-SSP will start at around 2020 (360 nights for 5 years), and IRD-SSP from 2016 (TBD). HSC science includes 1) cosmology with gravitational lensing, 2) lensing studies of galaxies and clusters, 3) photometric redshifts, 4) the Solar system, 5) the Milky Way and the Local Group, 6) AGN/quasars, 7) transients, 8) galaxies at low/high redshifts, and 9) clusters of galaxies. PFS science includes 1) cosmology, 2) galaxy & AGN, and 3) galactic archaeology. Subaru is planning the third pillar instrument, so called ULTIMATE-Subaru, which is the GLAO optical-NIR wide field camera & multi-IFU spectrograph for finding galaxies at ultra high redshift (z>10). Finally the strategy from Subaru to TMT will be presented. Subaru will conduct four major SSPs (HSC, PFS, IRD, ULTIMATE-Subaru) in coming decade to provide targets to TMT. HSC performs wide field surveys to reveal the distribution of dark matter in the Universe. IRD surveys Earth-like young planets to discover ~20 Earth-like habitable planets. PFS studies the expanding Universe to provide a few million emission line galaxies to TMT.

• The KIPS Transactions:PartA
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• v.8A no.2
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• pp.133-146
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• 2001

In a dynamic load distribution policies, each node gathers the current system sates information before making a decision on load balancing. Load balancing policies based on this strategy can suffer from processor thrashing. In this paper, we propose a new algorithm which attempts to decrease the frequency of the processor thrashing, the algorithm is based on the integration of three components. The first, the algorithm of which determine the size of jobs be transferred. The second, negotiation protocol with obtains a mutual agreement between a sender and a receiver on the transferring job size. And the third, a symmetrically-initiated location policy. The algorithm proposed in this paper used Siman IV as simulation tool to prove the improvement of performance. I analyzed the result of simulation, and compared with related works. The mean response time shows that there are no difference with existing policy, but appear a outstanding improvement in high load. The thrashing coefficient that shows the average response time, CPU overhead and the thrashing ratio at both the receiving and sending node has been used in the analysis. A significant improvement in the average response time and the CPU overhead ratio was detected using our algorithm when an overhead occurred in the system over other algorithm. The thrashing coefficient differed in the sending node and the receiving node of the system. Using our algorithm, the thrashing coefficient at the sending node showed more improvement when there was an overhead in the system, proving to be more useful. Therefore, it can be concluded that the thrashing ratio can be reduce by properly setting the maximum and minimum value of the system’s threshold queue.