• Journal of Korean Institute of Industrial Engineers
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• v.42 no.5
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• pp.304-313
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• 2016

This work suggests a new analysis approach for a discrete-time GI/G/1 queue with multiple vacations. The method used is called a modified supplementary variable technique and our result is an exact transform-free expression for the steady state queue length distribution. Utilizing this result, we propose a simple two-moment approximation for the queue length distribution. From this, approximations for the mean queue length and the probabilities of the number of customers in the system are also obtained. To evaluate the approximations, we conduct numerical experiments which show that our approximations are remarkably simple yet provide fairly good performance, especially for a Bernoulli arrival process.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.36-43
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• 2002

We analyze bulk service $M/G^{b}/1$ queues using the arrival time approach of Chae et al. (2001). As a result, the decomposition property of the M/G/1 queue with generalized vacations is extended to the $M/G^{b}/1$ queue in which the batch size is exactly a constant b. We also demonstrate that the arrival time approach is useful for relating the time-average queue length PGF to that of the departure time, both for the $M/G^{b}/1$queue in which the batch size is as big as possible but up to the maximum of constant b. The case that the batch size is a random variable is also briefly mentioned.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.80-91
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• 2010

Due to the convergence of broadcasting and communications, IPTV services are spotlighted as the that next-generation multimedia services. IPTV services should have functionality such as unlimited channel capacity, extension of media, QoS awareness and are required increasing traffic and quality control technology to adapt the attributes of IPTV service. Consequently, flow based quality control techniques are needed. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED(Random Early Detection) and modified RED algorithms have proposed. However, these algorithms have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the Flow based AQM(Active Queue Management) algorithm for the multimedia services that request various QoS requirements. The proposed algorithm can converge the packet loss ratio to the target packet loss ratio of required QoS requirements. And we present a performance evaluation by the simulations using the ns-2.

• 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).

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.1-18
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• 2006

We consider an $M^x/G/1$ queueing system with Bernoulli vacation schedule under multiple vacation policy. where after each vacation completion or service completion the server takes sequence of vacations until a batch of new customer arrive. This generalizes both $M^x/G/1$ queueing system with multiple vacation as well as M/G/1 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.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.437-446
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• 2002

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF (Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED (Random Early Detection). While active queue management in routers and gateways can potentially reduce packet loss rates in the Internet, this paper has demonstrated the inherent weakness of current techniques and shows that they are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they all use static parameter setting. So, in case where these parameters do not match the requirement of the network load, the performance of these algorithms can approach that of a traditional Drop-tail. In this paper, in order to solve this problem, a new active queue management algorithm called ARED (Active RED) is proposed. ARED computes the parameter based on our heuristic method. This algorithm can effectively reduce packet loss while maintaining high link utilizations.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1099-1104
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• 2020

In order to provide various types of application services based on the Internet, it is ideal to guarantee the quality of service(QoS) for each flow. However, realizing these ideas is not an easy task.. It is effective to classify multiple flows having the same or similar service quality requirements into same group, and to provide service quality for each group. The queue management mechanism in the router plays a very important role in order to efficiently transmit data and to support differentiated quality of service for each service. In order to efficiently support various multimedia services, an intelligent and adaptive queue management mechanism is required. This paper proposes an intelligent queue management mechanism based on deep reinforcement learning that decides whether to deliver packets for each group based on the traffic information of each flow group flowing in for a certain period of time and the current network state information.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3097-3107
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• 1999

Recently many studies have been done on the Random Early Detection(RED) algorithm as an active queue management and congestion avoidance scheme in the Internet. In this paper we first overview the characteristics of RED and the modified RED algorithms in order to understand the current status of these studies. Then we analyze the RED dynamics by investigating how RED parameters affect router queue behavior. We show the cases when RED fails since it cannot react to queue state changes aggressively due to the deterministic use of its parameters. Based on the RED parameter analysis, we propose a self-adaptive algorithm to cope with this RED weakness. In this algorithm we make two parameters be adjusted themselves depending on the queue states. One parameter is the maximum probability to drop or mark the packet at the congestion state. This parameter can be adjusted to react the long burst of traffic, consequently reducing the congestion disaster. The other parameter is the queue weight which is also adjusted aggressively in order for the average queue size to catch up with the current queue size when the queue moves from the congestion state to the stable state.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9B
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• pp.823-833
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• 2003

To satisfy the requirements of the real-time Internet services, queue management and scheduling schemes should be enhanced to accommodate the delay and jitter characteristic of them. Although the existing queue management schemes can address the congestion problems of TCP flows, they have some problems in supporting real-time services. That is, they show performance degradation when burst traffics are continuously going into the system after the queue is occupied at a predefined threshold level. In addition, under the congestion state, they show large jitter, which is not a desirable phenomenon for real-time transmissions. To resolve these problems, we propose a SDRED (State Dependent Random Early Detection) and dynamic scheduling scheme that can improve delay and jitter performances by adjusting RED parameters such as ma $x_{th}$ and $w_{q}$ according to the queue status. The SDRED is designed to adapt to the current traffic situation by adjusting the max,$_{th}$ and $w_{q}$ to four different levels. From the simulation results, we show that the SDRED decreases packet delays in a queue and has more stable jitter characteristics than the existing RED, BLUE, ARED and DSRED schemes.mes.mes.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.177-183
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• 2007

Active queue management (AQM) refers to a family of packet dropping mechanisms for router queues that has been proposed to support end-to-end congestion control mechanisms in the Internet. The proposed AQM algorithm by the IETF is Random Early Detection (RED). The RED algorithm allows network operators simultaneously to achieve high throughput and low average delay. However. the resulting average queue length is quite sensitive to the level of congestion. In this paper, we propose the Refined Adaptive RED(RARED), as a solution for reducing the sensitivity to parameters that affect RED performance. Based on simulations, we observe that the RARED scheme improves overall performance of the network. In particular, the RARED scheme reduces packet drop rate and improves goodput.