• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.125-133
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• 2008

In this paper, we propose active queue management mechanism (Active-WRED) to guarantee quality of the high priority service class in multi-class traffic service environment. In congestion situation, this mechanism increases drop probability of low priority traffic and reduces the drop probability of the high priority traffic, therefore it can improve the quality of the high priority service. In order to analyze the performance of our mechanism we introduce the stochastic analysis of a discrete-time queueing systems for the performance evaluation of the Active Queue Management (AQM) based congestion control mechanism called Weighted Random Early Detection (WRED) using a two-state Markov-Modulated Bernoulli arrival process (MMBP-2) as the traffic source. A two-dimensional discrete-time Harkov chain is introduced to model the Active-WRED mechanism for two traffic classes (Guaranteed Service and Best Effort Service) where each dimension corresponds to a traffic class with its own parameters.

• IE interfaces
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• v.11 no.3
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• pp.89-101
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• 1998

The randomness of the input variables in simulation experiments produce output responses which are also realizations of random variables. The random responses make necessary the use of statistical inferences to adequately describe the stochastic nature of the output. The analysis of the simulation output of non-terminating simulations is frequently complicated by the autocorrelation of the output data and the effect of the initial conditions that produces biased estimates. The regenerative method has been developed to deal with some of the problems created by the random nature of the simulation experiments. It provides a simple solution to some tactical problems and can produce valid statistical results. However, not all processes can he modeled using the regenerative method. Other processes modeled as regenerative may not return to a given demarcating state frequently enough to allow for adequate statistical analysis. This paper shows how the state transformation concept was successfully used in a queueing model and a job shop model. Although the first example can be analyzed using the regenerative method. it has the problem of too few recurrences under certain conditions. The second model has the problem of no recurrences. In both cases, the state transformation increase the frequency of the demarcating state. It was shown that time state transformations are regenerative and produce more cycles than the best typical discrete demarcating state in a given run length.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.33-40
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• 2017

In this Paper, Analyse the Steady State Behavior of TCP and TFRC with Packet Error when both TCP and TFRC Flows Co-exist in the Network. First, Model the Network with TCP and TFRC Connections as a Discrete Time System. Second, Calculate Average Round Trip Time of the Packet Between Source and Destination on Packet Loss Environment. Then Derive the Steady State Performance i.e. Throughput of TCP and TFRC, and Average Buffer Size of RED Router Based on the Analytic Network Model. The Throughput of TCP and TFRC Connection Decrease Rapidly with the Growth of Sending Window Size and Their Transmission Rate but Their Declines become Smoothly when the Number of Sending Window Arrives on Threshold Value. The Average Queue Length of RED Router Increases Slowly on Low Transmission Rate but Increases Rapidly on High Transmission Rate.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.589-595
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• 2017

We present an estimation model for optimal channel capacity required to data traffic transmission. The optimal channel capacity should be calculated in order to satisfy the permitted transmission delay of each wireless data services. Considering the discrete-time operation of digital communication systems and batch arrival of packet-switched traffic for various wireless services, $Geo^x$/G/1 non-preemptive priority queueing model is analyzed. Based on the heuristic interpretation of the mean waiting time, the mean waiting times of various data packets which have the service priority. Using the mean waiting times of service classes, we propose the procedure of determining the optimal channel capacity to satisfy the quality of service requirement of the mean delay of wireless services. We look forward to applying our results to improvement in wireless data services and economic operation of the network facilities.