• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1345-1362
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• 2019

Most active queue management algorithms manage network congestion based on the size of the queue but ignore the network environment which makes queue size change. It seriously affects the response speed of the algorithm. In this paper, a new AQM algorithm named CT-AQM (Change Trend-Adaptive Queue Management) is proposed. CT-AQM predicts the change trend of queue size in the soon future based on the change rate of queue size and the network environment, and optimizes its dropping function. Simulation results indicate that CT-AQM scheme has a significant improvement in loss-rate and throughput.

• 한국경영과학회지
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• 제22권2호
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• pp.1-12
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• 1997

We consider an M/M/2 queue with two servers placed in series. System performance measures that we present in closed expressions are the first and the second moments for the system size, the queue walting time and the sojourn time. We also present an algorithm for computing the queue waiting time distribution function based on the randomization method. As an application, we analyze the double tollbooth system and compare its performance with the conventional single tollbooth system's.

• 전기학회논문지
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• 제58권5호
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• pp.891-897
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• 2009

This paper presents a novel load management technique that can lower the peak demand caused by package airconditioner loads in large apartment complex. An intelligent hierarchical load management system composed of a Central Intelligent Management System(CIMS) and multiple Local Intelligent Management Systems(LIMS) is proposed to implement the proposed technique. Once the required amount of the power reduction is set, CIMS issues tokens, which can be used by each LIMS as a right to turn on the airconditioner. CIMS creates and maintains a queue for fair and proper allocation of the tokens among the LIMS requesting tokens. By adjusting the number tokens and queue management policies, desired power reduction can be achieved smoothly. The Markov Birth and Death process and the Balance Equations utilizing the Diffusion Model are employed for evaluation of queue performances during transient periods until the static balances among the states are achieved. The proposed technique is tested using a summer load data of a large apartment complex and give promising results demonstrating the usability in load management while minimizing the customer inconveniences.

• 한국경영과학회지
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• 제33권1호
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• pp.107-115
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• 2008

We consider the discrete-time GI/G/1/K queue under the early arrival system. Using a modified supplementary variable technique(SVT), we obtain the distribution of the steady-state queue length. Unlike the conventional SVT, the modified SVT yields transform-free results in such a form that a simple two-moment approximation scheme can be easily established.

• 한국경영과학회지
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• 제18권3호
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• pp.51-63
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• 1993

We consider a cyclid server system under N-policy. This system consists of multiple queues served in a cyclic order by a single server. In this paper, we consider the following control policy. Every time server polls one queue, the server inspects the state of the queue. If the total number of units is found to have reached or exceeded a pre-specified value, the server begins to serve the queue until it is empty. As soon as the queue becomes empty, the server polls next queue. An approximate analysis of this system is presented. Sever vacation model is used as an analytical tool. However, server vacation periods are considered to be dependent on the service times of respective queues. The results obtained from the approximate analysis are ompared with simulation results.

• Management Science and Financial Engineering
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• 제15권2호
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• pp.1-21
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• 2009

We consider an $M^x/G/1$ queueing system with a random setup time under Bernoulli vacation schedule, where the service of the first unit at the completion of each busy period or a vacation period is preceded by a random setup time, on completion of which service starts. However, after each service completion, the server may take a vacation with probability p or remain in the system to provide next service, if any, with probability (1-p). This generalizes both the $M^x/G/1$ queueing system with a random setup time as well as the Bernoulli vacation model. We carryout an extensive analysis for the queue size distributions at various epochs. Further, attempts have been made to unify the results of related batch arrival vacation models.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1101-1103
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• 2006

For a broad class of discrete-time FIFO queueing systems with D-MAP (discrete-time Markovian arrival process) arrivals, we present a distributional Little's law that relates the distribution of the stationary number of customers in system (queue) with that of the stationary number of slots a customer spends in system (queue). Taking the multi-server D-MAP/D/c queue for example, we illustrate how to utilize this relation to get the desired distribution of the number of customers.

• 대한산업공학회지
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• 제28권3호
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• pp.319-330
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• 2002

We consider BMAP/G/1 queueing system with N-policy and multiple vacations. We derive the vector generating functions of the queue length in a factorized form and interpret the factorization. We also derive the mean queue length.

• Journal of the Korean Statistical Society
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• 제34권1호
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• pp.39-47
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• 2005

We adopt the P/sub λ, T//sup M/ policy of dam to introduce a service policy with alternating service rates for a Poisson arrival queue, in which the service rate alternates depending on the number of customers in the system. The stationary distribution of the number of customers in the system is derived and, after operating costs being assigned to the system, the optimization of the policy is studied.

• 한국경영과학회지
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• 제16권2호
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• pp.36-48
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• 1991

In this study, an efficient algorithm is developed to compute steady state probabilities for the following M$_{x}$G/1 server vacation system under control-operating poligy: At the end of a busy period, the server takes a sequence of vacations, each for a random amount of time. At the end of each vacation, he inspects the length of the queue. If the queue length at this time is equal to or greater than a prespecified threshold value r, he begins to serve the queue until it is empty.y.