• Journal of Communications and Networks
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• v.6 no.1
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• pp.78-87
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• 2004

This paper presents deterministic, worst-case analysis of a queueing system whose multiple homogeneous input streams are regulated by the associated leaky buckets and the queueing system that has a single stream regulated by the jumping-window. Queueing delay averaged over all items is used for performance measure, and the worst-case input traffic and the worst-case performance are identified for both queueing systems. For the former queueing system, the analysis explores different phase relations among leaky-bucket token generations. This paper observes how the phase differences among the leaky buckets affect the worst-case queueing performance. Then, this paper relates the worst-case performance of the former queueing system with that of the latter (the single stream case, as in the aggregate streams from many users, whose item arrivals are regulated by one jumping-window). It is shown that the worst-case performance of the latter is identical to that of the former in which all leaky buckets have the same phase and have particular leaky bucket parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1240-1243
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• 2016

In this paper, we analyze the queueing performance of cumulative distribution function (CDF)-based opportunistic scheduling over Nakagami-m Markov fading channels. We derive the formula for the average queueing delay and the queue length distribution by constructing a two-dimensional Markov chain. Using our formula, we investigate the queueing performance for various fading parameters.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.143-149
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• 2008

There have been some approximation analysis methods for a GI/G/1 queueing system. As one of them, an approximation technique for the steady-state probability in the GI/G/1 queueing system based on the iteration numerical calculation has been proposed. As another one, an approximation formula of the average queue length in the GI/G/1 queueing system by using the diffusion approximation or the heuristics extended diffusion approximation has been developed. In this article, an approximation technique in order to analyze the GI/G/1 queueing system is considered and then the formulae of both the steady-state probability and the average queue length in the GI/G/1 queueing system are proposed. Through some numerical examples by the proposed technique, the existing approximation methods, and the Monte Carlo simulation, the effectiveness of the proposed approximation technique is verified.

• 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.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.405-414
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• 2004

This paper considers overload control in telecommunication networks. Markov-modulated Bernoulli process ( MMBP ) has been extensively used to model bursty traffics with time-correlation. Thus, we investigate the transient behavior of the queueing system MMBP/D/l/K queue with two thresholds. The model is analyzed recursively by using the generating function method. We obtain the transient queue length distribution and waiting time distribution at an arbitrary time. The transient behavior of the queueing system helps observing the temporary system behavior.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.111-122
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• 1999

In this paper, we consider a queueing network model. where the population constraint within each subnetwork is controlled by a semaphore queue. The total number of customers that may be present in the subnetwork can not exceed a given value. Each node has a constant service time and the arrival process to the queueing network is an arbitrary distribution. A major characteristics of this model is that the lower layer flow is halted by the state of higher layer. We present some properties that the inter-change of nodes does not make any difference to customer's waiting time in the queueing network under a certain condition. The queueing network can be transformed into a simplified queueing network. A dramatic simplification of the queueing network is shown. It is interesting to see how the simplification developed for sliding window flow control, can be applied to multi-layered queueing network.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.349-357
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• 2002

In this paper, we analyze queueing behaviors and investigate the possibilities of reducing and controlling shortages and oversupplies in the bidirectional queueing system which forms a negative queue by demand and a positive queue by supply. Interarrival times of units in the bidirectional queueing system investigated are exponetially distributed. Instant pairing off implies that queue can be either positive or negative, but not both at the same time. The results include a proof that sum of queue lengths is minimized if rates of demand and supply in each system are equal and optimum solutions for rates of supply which minimize the sum of queue lengths when rates of demand and sum of rates of supply are given. In addition, the relationship between the ordinary queueing system and the bidirectional queueing system is investigated.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.428-434
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• 2014

Dry docks are used to repair warships or Merchant ships based on their life cycles. There are the certain number of dry docks in the ROK Navy, However, the ROK Navy force structure has been changing a lot since the Korean War. The focus of this study is to analyze the queueing problem regarding present dry docks capacities and to forecast the appropriate number of dry docks based on future naval ship structure. The study proposes to obtain an efficient dry dock size using queueing problem and simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.288-291
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• 2002

We characterize multipath fading channel dynamics at the packet level and analyze the corresponding data queueing performance in various environments. We identify the similarity between wire-line queueing analysis and wireless network per-formance analysis. The second order channel statistics, i.e. channel power spectrum, is fecund to play an important role in the modeling of multipath fading channels. However, it is identified that the first order statistics, i.e. channel CDF also has significant impact on queueing performance. We use a special Markov chain, so-called CMPP, throughout this paper.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.285-295
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• 2001

We consider a queueing system under overload control to support bursty traffic. The queueing system under overload control is modelled by MMBP/D1/K queue with two thresholds on buffer. Arrival of customer is assumed to be a Markov-modulated Bernoulli process (MMBP) by considering burstiness of traffic. Analysis is done in discrete-time case. Using the generating function method, we obtain the stationary queue length distribution. Finally, the loss probability and the waiting time distribution of a customer are given.