• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.973-980
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• 2005

In this paper, we analyze previous flow control algorithm for serving ABR traffic, and then propose the algorithm which calculate fair transmission rate and control efficiently ABR traffic using VS/VD switch which has an effect on PNNI environment with long delay. For getting the transmission rate, the proposed algorithm use FMMRA as ER scheme which calculate exactly the fair share. And, in large delay state, we can obtain fair cell sharing by calculating transmission rates which obtained by transmitted queue length information of VD to VS for serve and drain cell in queue Through the computer simulation, we evaluate the performance of proposed algorithm. According to the results, the proposed algorithm shows good performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2499-2522
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• 2017

Multi-hop networks are a low-setup-cost solution for enlarging an area of network coverage through multi-hop routing. Carrier sense multiple access with collision avoidance (CSMA/CA) is frequently used in multi-hop networks. Multi-hop networks face multiple problems, such as a rise in contention for the medium, and packet loss under heavy-load, saturated conditions, which consumes more bandwidth due to re-transmissions. The number of re-transmissions carried out in a multi-hop network plays a major role in the achievable quality of service (QoS). This paper presents a statistical, analytical model for the end-to-end delay of contention-based medium access control (MAC) strategies. These strategies schedule a packet before performing the back-off contention for both differentiated heterogeneous data and homogeneous data under saturation conditions. The analytical model is an application of Markov chain theory and queuing theory. The M/M/1 model is used to derive access queue waiting times, and an absorbing Markov chain is used to determine the expected number of re-transmissions in a multi-hop scenario. This is then used to calculate the expected end-to-end delay. The prediction by the proposed model is compared to the simulation results, and shows close correlation for the different test cases with different arrival rates.

• 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.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.29-40
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• 1997

Two asymptotic analyses of the queue length distribution at a statistical multiplexor supporting heterogeneous exponential on-off sources are considered. The first analysis is performed by approximating the cell generation rates as a multi-dimensional Ornstein-Uhlenbeck process and then applying the Benes queueing formula. In the second analysis, w state with a system of linear equations derived from the exact expressions of the dominant eigenvalue of the matrix governing the queue length distribution. Assuming that there are a large number of sources, we obtain asymptotic approximations to the dominant eigenvalue. Based on the analyses, we define a traffic descriptor to include the mean and the variance of the cell generation rate and a burstiness measure. A simple expression for the quality of service (QoS) in cell loss rate is derived in terms of the traffic descriptor parameters and the multiplexor parameters (output link capacity and buffer size). The result is then used to quantify the factors determining the required capacity of a call taking the statistical multiplexing gain into consideration. As an application of the analyses, we can use the required capacity calculation for simple yet effective connection admission control(CAC) algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1413-1421
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• 2000

In this paper, we analyze previous flow control algorithm for serving ABR traffic, and then propose the algorithm which calculate fair transmission rate and control efficiently ABR traffic using VS/VD switch which has an effect on WAN environment with long delay. For getting the transmission rate, the proposed algorithm use FMMAR as ER scheme which calculate exactly the fair share. And, in large delay state. we can obtain fair cell sharing by calculating transmission rates which obtained by transmitted queue length information of VD to VS for serve and drain cell in queue Through the computer simulation, we evaluate the performance of proposed algorithm. According to the results, the proposed algorithm shows good performance.

• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.31-39
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• 1999

A new approximation method for finding the steady-state probabilities of the number of customers present in queueing systems with Poisson arrivals and two servers with different deterministic service times with infinite waiting room capacity is developed. The major assumption made for the approximation is that the residual service times of the servers have mutually independent uniform distributions with densities equal to the reciprocals of the respective service times. The method reflects the heterogeneity of the servers only through the ratio of their service times, irrespective of the actual magnitudes and difference. The transition probability matrix is established and the steady-state probabilities are found for a variety of traffic intensities and ratios of the two service times; also the mean number of customers present in the system and in the queue, and server utilizations are found and tabulated. The method was validated by simulation and turned out to be very sharp.

• Journal of the Korean Operations Research and Management Science Society
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• v.11 no.1
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• pp.7-11
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• 1986

Throughout this paper we analyze the system at output point t of two stage cyclic queueing model. Our main result characterize the stochastic process (X$^{o}$ , T$^{o}$ ), the system at output point, as a Markov renewal process. The subsequent lemma exhibits the semi-Markov kernel of (X$^{o}$ , T$^{o}$ ) with state dependent feedback, the possibility of a reducible state space arises. A simple necessary and sufficient condition for the irreducibility of (X$^{o}$ , T$^{o}$ was determinded. This irreducibility implied that (X$^{o}$ , T$^{o}$ ) was aperiodic.

• Journal of IKEEE
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• v.22 no.2
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• pp.402-407
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• 2018

Link selection strategy has been an important technical issues of relay network. In this paper, we introduce a link selection scheme in the bidirectional, buffer-aided relay network. Three kinds of information such as the states of the queue at the relay buffer, the qualities of the links, and the states of the queues at the user buffer are considered. Throughput and delay performance is evaluated under three cases with different available information.

• 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.