• Journal of the Korean Mathematical Society
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• v.42 no.3
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• pp.517-527
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• 2005

This paper considers a discrete-time queueing system with variable service capacity. Using the supplementary variable method and the generating function technique, we compute the joint probability distribution of queue length and remaining service time at an arbitrary slot boundary, and also compute the distribution of the queue length at a departure time.

• Journal of the Korean Mathematical Society
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• v.32 no.2
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• pp.211-236
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• 1995

The purpose of this paper is to provide a transient diffusion approximation of queue size distribution for M/G/m/N system. The M/G/m/N system can be expressed as follows. The interarrival times of customers are exponential and the service times of customers have general distribution. The system can hold at most a total of N customers (including the customers in service) and any further arriving customers will be refused entry to the system and will depart immediately without service. The queueing system with finite capacity is more practical model than queueing system with infinite capacity. For example, in the design of a computer system one of the important problems is how much capacity is required for a buffer memory. It its capacity is too little, then overflow of customers (jobs) occurs frequently in heavy traffic and the performance of system deteriorates rapidly. On the other hand, if its capacity is too large, then most buffer memories remain unused.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.377-385
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• 1996

We present an approximate algorithmic approach for the m-server fork-join queueing system with infinite queue capacity. We analyze the system size and queue waiting time. We assume Poisson arrival process and independent exponential service times.

• Communications of the Korean Mathematical Society
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• v.14 no.3
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• pp.611-625
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• 1999

We consider ΜΑΡ/G/ 1 finite capacity queue with mul-tiple thresholds on buffer. The arrival of customers follows a Markov-ian arrival process(MAP). The service time of a customer depends on the queue length at service initiation of the customer. By using the embeded Markov chain method and the supplementary variable method, we obtain the queue length distribution ar departure epochs and at arbitrary epochs. This gives the loss probability and the mean waiting time by Little's law. We also give a simple numerical examples to apply the overload control in packetized networks.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.1
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• pp.41-52
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• 2016

When the queue length of congestion vehicles in tunnel fire is extended beyond tunnel length, the capacity of smoke control system needs to be increased in line with ventilation resistance. However, the vehicle queue length is not defined, so a rational equation is necessary in current fire prevention guideline. This study is intended to propose an equation to calculate the queue length considering the number of vehicles in queue in tunnel fire and evaluate the applicability by tunnel length as well. When it comes to normal tunnel, it is necessary to compare the vehicle queue length with tunnel length up to the length of 1,200 m in a bid to avoid applying the vehicle queue length excessively in case of fire. As a result of evaluation of applicability to model a tunnel, saving the number of jet fan for smoke control appeared to be effective. Besides, quantitative approach to explain the vehicle queue length through the relationship between the percentage of large vehicles and tunnel length was presented. Consequently, when the queue length of the congestion vehicles exceeds the tunnel length in determining the capacity of smoke control system in case of fire, the number of vehicles beyond the tunnel length needs to be excluded from estimating the ventilation resistance by vehicles.

• Management Science and Financial Engineering
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• v.9 no.2
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• pp.1-12
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• 2003

For a stationary queue with BMAP arrivals, Takine and Takahashi [8] present a relationship between the queue length distributions at a random epoch and at a departure epoch by using the rate conservation law of Miyazawa [6]. In this note, we derive the same relationship by using the elementary balance equation, ‘rate-in = rate-out’. Along the same lines, we additionally derive relationships between the queue length distributions at a random epoch and at an arrival epoch. All these relationships hold for a broad class of finite-as well as infinite-capacity queues with BMAP arrivals.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.152-160
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• 1996

This paper focuses on development and evaluation of a performance management algorithm for IEEE 802.4 token bus networks to serve large-scale integrated manufacturing systems. Such factory automation networks have to satisfy delay constraints imposed on time-critical messages while maintaining as much network capacity as possible for non-time-critical messages. This paper presents a network performance manager that adjusts queue capacity as well as timers by using a set of fuzzy rules and fuzzy inference mechanism. The efficacy of the performance management has been demonstrated by a series of simulation experiments.

• The Journal of Engineering Research
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• v.1 no.1
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• pp.31-40
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• 1997

We first describe an approximation method for fitting a k-state MMBP to the departure process of a D-BMAP/Geo/1/K queue. The fitting model is them used in a simple decomposition algorithm to analyze a tandem configuration of finite capacity queue with cell loss.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2254-2259
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• 2011

The introduction of Personal Rapid Transit (PRT) has been widely discussed in the Korean transportation research field. However, there is no robust criterion to derive the throughput of cars and passengers at PRT stations, which plays a primary role in determining the overall capacity of PRT systems. The present study provided a methodology to rigorously compute the capacity for simple-serial PRT stations with a single platform, considering three decisive factors, i.e., the demand level of incoming cars and outgoing passengers, the station structure, and the operation strategy. A micro-level simulator was developed for the analysis of station capacity. And, by using this, station capacities were presented for various combinations of the decisive factors. In particular, the relationship between capacity and station structure was investigated in detail. Station structure is represented by the numbers of platform berths, input queue berths, and output queue berths. Moreover, both waive rate and waiting time, which represent the level of passenger service, were taken into account when the station throughput was computed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.563-570
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• 2009

This study is aimed to analyze the overall effects of the additional delay caused by the vehicle in front of the queue, at the signal, to the total delay estimation. To estimate the average vehicle delay at the signalized intersection, as survey of the queue length at the intersection and traffic counts were conducted. As a result of this analysis, all of the three delay estimation methods turned out to be similar in that the estimation of the average delay for the test vehicle was less than 60 sec/vehicle. However, the average delay time for the vehicle in front of the queue only, was estimated at 60-70 sec/vehicle which is similar to the average delay of the test vehicle.