• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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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.

• Journal of KIISE:Information Networking
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• v.31 no.1
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• pp.70-80
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• 2004

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). But, RED configuration has been a problem since its first proposal. This problem is that proposed configuration is only good for the particular traffic conditions studied, but may have detrimental effects if used in other conditions. 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 unstable for tile various traffic conditions. The inherent problem with these queue management algorithms is that they all use static parameter setting. In this paper, in order to solve this problem, a new active queue management algorithm called SQM(Stabilized Queue Management) is proposed. This paper shows that it is easy to parameterize SQM algorithm to perform well under different congestion scenarios. This algorithm can effectively reduce packet loss while maintaining high link utilizations and is good for the various traffic conditions.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.133-146
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• 2004

Recently, many active queue management (AQM) algorithms have been proposed to address the performance degradation. of end-to-end congestion control under tail-drop (TD) queue management at Internet routers. However, these AQM algorithms show performance improvement only for limited network environments, and are insensitive to dynamically changing network situations. In this paper, we propose an adaptive queue management algorithm, called PID-controller, that uses proportional-integral-derivative (PID) feedback control to remedy these weak-Dalles of existing AQM proposals. The PID-controller is able to detect and control congestion adaptively and proactively to dynamically changing network environments using incipient as well as current congestion indications. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as Random Early Detection (RED) [3] and Proportional-Integral (PI) controller [9] in terms of queue length dynamics, packet loss rates, and link utilization.

• 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

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1104-1110
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• 2006

In this paper we present a simple approach to the joint queue length distribution in the nonpreemptive priority M/G/1 queue. Without using the supplementary variable technique, we derive the joint probability generating function of the stationary queue length at arbitrary time.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.1
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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.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.275-281
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• 2003

Random Early Detection (RED) [1] is an active queue management scheme which has been deployed extensively to reduce packet loss during congestion. Although RED can improve loss rates, its performance depends severely on the tuning of its operating parameters. The idea of adaptively varying RED parameters to suit the network conditions has been investigated in [2], where the maximum packet dropping probability $max_p$ has been varied. This paper focuses on adaptively varying the queue weight $\omega_q$ in conjunction with $max_p$ to improve the performance. We propose two algorithms viz., $\omega_q$-thresh and $\omega_q$-ewma to adaptively vary $\omega_q$. The performance is measured in terms of the packet loss percentage, link utilization and stability of the instantaneous queue length. We demonstrate that varying $\omega_q$ and $max_p$ together results in an overall improvement in loss percentage and queue stability, while maintaining the same link utilization. We also show that $max_p$ has a greater influence on loss percentage and queue stability as compared to $\omega_q$, and that varying $\omega_q$ has a positive influence on link utilization.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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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.

• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.89-98
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• 2004

AQM (Active Queue Management) techniques such as RED (Random Early Detection) which be proposed to solve the congestion of internet perform congestion control effectively for TCP data. However, in the situation where TCP and UDP share the bottleneck link, they can not solve the problems of the unfairness and long queueing delay. In this paper, we proposed an simple queue management algorithm, called PSRED (Protocol Sensitive RED), that improves fairness and decreases queueing delay. PSRED algorithm improves fairness and decreases average queue length by distinguishes each type of flow in using protocol field of packets and applies different drop functions to them respectively.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.437-447
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• 2003

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) algorithm. However, RED algorithm simple but does not protect traffic from high-bandwidth flows, which include not only flows that fail to use end-to-end congestion control such as UDP flow, but also short round-trip time TCP flows. In this paper, in order to solve this problem, we propose a simple fairness queue management scheme, called AFQM(Approximate Fair Queue Management) algorithm, that discriminate against the flows which submit more packets/sec than is allowed by their fair share. By doing this, the scheme aims to approximate the fair queueing policy Since it is a small overhead and easy to implement, AFQM algorithm controls unresponsive or misbehaving flows with a minimum overhead.