• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1375-1382
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• 2015

This paper aims to introduce the numerical methods for solving the optimal control theory to model bufferbloat problem. Mathematical tools are useful to provide insight for system engineers and users to understand better about what we are facing right now while experiment in a large-scale testbed can encourage us to implement in realistic scenario. In this paper, we introduce a survey of the numerical methods for solving the optimal control problem. We propose the dynamic optimization sweeping algorithm for optimal control of the active queue management. Simulation results in network simulator ns2 demonstrate that our proposed algorithm can obtain the stability faster than the others while still maintain a short queue length (≈10 packets) and low delay experience for arriving packets (0.4 seconds).

• Bulletin of the Korean Mathematical Society
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• v.46 no.4
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• pp.673-689
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• 2009

We analyze $MAP_1,\;MAP_2$/G/1 finite queues with service scheduling function dependent upon queue lengths. The customers are classified into two types. The arrivals of customers are assumed to be the Markovian Arrival Processes (MAPs). The service order of customers in each buffer is determined by a service scheduling function dependent upon queue lengths. Methods of embedded Markov chain and supplementary variable give us information for queue length of two buffers. Finally, the performance measures such as loss probability and mean waiting time are derived. Some numerical examples also are given with applications in telecommunication networks.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.4
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• pp.295-304
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• 2014

We analyze theMMPP/G/1/K queue with a modified state-dependent service rate. The service time of customers upon service initiation is changed if the number of customers in the system reaches a threshold. Then, the changed service time is continued until the system becomes empty completely, and this process is repeated. We analyze this system using an embedded Markov chain and a supplementary variable method, and present the queue length distributions at a customer's departure epochs and then at an arbitrary time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.307-312
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• 2000

Asynchronous transfer mode(ATM) is flexible to support the various multimedia communication services such as data, voice, and image by applying asynchronous time-sharing and statistical multiplexing techniques to the existing data communication. ATM service is categorized to CBR, VBR, UBR, and ABR according to characteristics of the traffic and a required service qualities. Among them, ABR service guarantees a minimal bandwidth and can transmit cells at a maximum transmission rate within the available bandwidth. To minimize the cell losses in transmission and switching, a feedback information in ATM network is used to control the traffic. In this paper, predictive control algorithms are proposed for the feedback information. When the feedback information takes a long propagation delay to the backward nodes, ATM switch can experience a congestion situation from the queue length increases, and a high queue length fluctuations in time. The control algorithms proposed in this paper provides predictive control model using slop changes of the queue length function and previous data of the queue lengths. Simulation shows the effectiveness result of the proposed control algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.66-75
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• 2017

Priority disciplines are an important scheme for service systems to differentiate their services for different classes of customers. (N, n)-preemptive priority disciplines enable system engineers to fine-tune the performances of different classes of customers arriving to the system. Due to this virtue of controllability, (N, n)-preemptive priority queueing models can be applied to various types of systems in which the service performances of different classes of customers need to be adjusted for a complex objective. In this paper, we extend the existing (N, n)-preemptive resume and (N, n)-preemptive repeat-identical priority queueing models to the (N, n)-preemptive repeat-different priority queueing model. We derive the queue-length distributions in the M/G/1 queueing model with two classes of customers, under the (N, n)-preemptive repeat-different priority discipline. In order to derive the queue-length distributions, we employ an analysis of the effective service time of a low-priority customer, a delay cycle analysis, and a joint transformation method. We then derive the first and second moments of the queue lengths of high- and low-priority customers. We also present a numerical example for the first and second moments of the queue length of high- and low-priority customers. Through doing this, we show that, under the (N, n)-preemptive repeat-different priority discipline, the first and second moments of customers with high priority are bounded by some upper bounds, regardless of the service characteristics of customers with low priority. This property may help system engineers design such service systems that guarantee the mean and variance of delay for primary users under a certain bounds, when preempted services have to be restarted with another service time resampled from the same service time distribution.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.43-51
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• 2002

In this paper, we study the new packet dropping scheme using an active queue management algorithm. Active queue management mechanisms differ from the traditional drop tail mechanism in that in a drop tail queue packets are dropped when the buffer overflows, while in active queue management mechanisms, packets may be dropped early before congestion occurs, However, it still incurs high packet loss ratio when the buffer size is not large enough, By detecting congestion and notifying only a randomly selected fraction of connection, RED causes to the global synchronization and fairness problem. And also, it is the biggest problem that the network traffic characteristics need to be known in order to find the optimum average queue length, We propose a new efficient packet dropping method based on the active queue management for congestion control. The proposed scheme uses the per-flow rate and fair share rate estimates. To this end, we present the estimation algorithm to compute the flow arrival rate and the link fair rate, We shows the proposed method improves the network performance because the traffic generated can not cause rapid fluctuations in queue lengths which result in packet loss

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.23-32
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• 2017

In this paper, We suggest a unified approach for the analysis of discrete-time MAP/G/1 queueing system. Many researches on the D-MAP/G/1 queue have been used different approach to analyze system queue length and waiting time for the same system. Therefore, a unified framework for analyzing a system is necessary from a viewpoint of system design and management. We first derived steady-state workload distribution, and then waiting time and sojourn time are derived by the result of workload analysis. Finally, system queue length distribution is derived with generating function from the sojourn time distribution.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.63-76
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• 2024

In this study, we analyzed queue length and sojourn time of discrete-time BMAP/G/1 queues under the workload control. Group customers (packets) with correlations arrive at the system following a discrete-time Markovian arrival process. The server starts busy period when the total service time of the arrived customers exceeds a predetermined workload threshold D and serves customers until the system is empty. From the analysis of workload and waiting time, distributions of queue length at the departure epoch and arbitrary time epoch and system sojourn time are derived. We also derived the mean value as a performance measure. Through numerical examples, we confirmed that we can obtain results represented by complex forms of equations, and we verified the validity of the theoretical values by comparing them with simulation results. From the results, we can obtain key performance measures of complex systems that operate similarly in various industrial fields and to analyze various optimization problems.

• 전자공학회논문지 IE
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• v.43 no.3
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• pp.41-48
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• 2006

In this paper, we propose a new active queue management (AQM) scheme by utilizing the predictability of the Internet traffic. The proposed scheme predicts future traffic input rate by using the auto-regressive (AR) time series model and determines the future congestion level by comparing the predicted input rate with the service rate. If the congestion is expected, the packet drop probability is dynamically adjusted to avoid the anticipated congestion level. Unlike the previous AQM schemes which use the queue length variation as the congestion measure, the proposed scheme uses the variation of the traffic input rate as the congestion measure. By predicting the network congestion level, the proposed scheme can adapt more rapidly to the changing network condition and stabilize the average queue length and its variation even if the traffic input level varies widely. Through ns-2 simulation study in varying network environments, we compare the performance among RED, Adaptive RED (ARED), REM, Predicted AQM (PAQM) and the proposed scheme in terms of average queue length and packet drop rate, and show that the proposed scheme is more adaptive to the varying network conditions and has shorter response time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.13-22
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• 2003

It is recognized that one of the problems for the current 'Traffic Adaptive Control System in Seoul' is the performance at the oversaturated condition. Instead of 'Degree of Saturation' adopted in the current system, the methodology of balancing the queue length was developed and evaluated in this study. This method keeps the balance of queue lengths on the intersections and reduces the overall queue lengths. In addition a traffic signal control model was developed based on the method. This model can reduce not only the queue lengths but also the average delay of vehicles according to the macroscopic and microscopic evaluations.