• 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 the Korea Society of Computer and Information
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• v.16 no.1
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• pp.133-142
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• 2011

When TCP operates in multi-hop wireless networks, it suffers from severe performance degradation due to the different characteristics of wireless networks and wired networks. This is because TCP reacts to wireless packet losses by unnecessarily decreasing its sending rate assuming the losses as congestion losses. Although several loss differentiation algorithms (LDAs) have been proposed to avoid such performance degradation, their detection accuracies are not high as much as we expect. In addition the schemes have a tendency to sacrifice the detection accuracy of congestion losses while they improve the detection accuracy of wireless losses. In this paper, we suggest a new sender-based loss differentiation scheme which enhances the detection accuracy of wireless losses while minimizing the sacrifice of the detection accuracy of congestion losses. Our scheme estimates the rate of queue usage which is highly correlated with the congestion in the network path between a TCP sender and a receiver, and it distinguishes congestion losses from wireless losses by comparing the estimated queue usage with a certain threshold. In the extensive experiments based on a network simulator, QualNet, we measure and compare each detection accuracy of wireless losses and congestion losses, and evaluate the performance enhancement in each scheme. The results show that our scheme has the highest accuracy among the LDAs and it improves the most highly TCP performance in multi-hop wireless networks.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.39-44
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• 2003

The network performance gets down during congestion periods to solve the problem effectively. A RED(Random Earl Detection) algorithm of the queue management algorithm is proposed and IETF recommends it as a queue management. A RED algorithm controls a congestion aspect dynamically. In analyzing parameters when static value of parameter is set in the gateway cannot be handled the status of current network traffic properly We propose the Effective RED algorithm to solve with the weakness of RED In this algorithm the maximum drop probability decides to accept or drop the interning packets, is adjusted dynamically on the current queue state for controlling the congestion phase effectively in the gateway. This algorithm is confirmed by computer simulation using the NS(Network Simulator)-2.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.186-192
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• 2007

The virus throttling technique[5,6] is the one of well-known worm early technique. Virus throttling reduce the worm propagration by delaying connection packets artificially. However the worm detection time is not sufficiently fast as expected when the worm generated worm packets at a low rate. This is because the virus throttling technique use only delay queue length. In this paper we use the trend of weighted average delay queue length (TW AQL). By using TW AQL, the worm detection time is not only shorten at a low rate Internet worm, but also the false alarm does not largely increase. By experiment, we also proved our proposed algorithm had better performance.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.45-56
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• 2010

This paper reports a new mechanism for congestion controls. The proposed congestion detection algorithm can be provided with delay and unnecessary energy consumption. Conventional congestion control methods decide congestion by queue occupancy or mean packet arrival rate of MAC layer only, however, our method can perform precise detection by considering queue occupancy and mean packet arrival rate. In addition, the congestion avoiding method according to congestion degree and scheduling method using priority for real time packets are proposed. Finally, simulation results show that proposed congestion detection and control methods outperforms conventional scheduling schemes for wireless sensor network.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.181-183
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• 2002

현재의 인터넷 라우터는 Drop tail 방식으로 큐 안의 패킷을 관리한다. 따라서 네트워크 트래픽의 지수적인 증가로 인해 발생하는 혼잡 상황을 명시적으로 해결 한 수 없다. 이 문제를 해결하기 위해 IETF (Internet Engineering Task Force)에서는 RED(Random Early Detection)알고리즘과 같은 능동적인 큐 관리 알고리즘(AQM: Active Queue Algorithm)을 제시하였다. 하지만 RED 알고리즘은 네트워크 환경에 따른 매개 변수의 설정의 어려움을 가지고 있어 잘못된 매개변수 설정으로 인하여 네트워크 성능을 저하시키는 문제를 발생시키며 전체 망에 불안정한 혼잡제어를 야기 시킨다. 본 논문에서는 기존의 AQM를 개선한 SOQuM(Stabilized Operation of Queue Management) 알고리즘을 제안하였다. 제안한 알고리즘의 성능을 검증하기 위해 기존의 방법과 시뮬레이션을 이용하여 비교하였다.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.285-291
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• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.63-70
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• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1332-1335
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• 2008

In order to various service types of real time and non-real time traffic with varying requirements are transmitted over the IEEE 802.16 standard is expected to provide quality of service(QoS) researchers have explored to provide a queue management scheme with differentiated loss guarantees for the future Internet. The sides of a packet drop rate, an each class to differential drop probability on achieving a low delay and high traffic intensity. Improved a queue management scheme to be enhanced to offer a drop probability is desired necessarily. This paper considers multiple random early detection with differential drop probability which is a slightly modified version of the Multiple-RED(Random Early Detection) model, to get the performance of the best suited, we analyzes its main control parameters (max_th, min_th, max_p) for achieving the proportional loss differentiation (PLD) model, and gives their setting guidance from the analytic approach. we propose Dynamic-multiple queue management scheme based on differential drop probability, called Dynamic-VQSDDP(Variable Queue State Differential Drop Probability)T, is proposed to overcome M-RED's shortcoming as well as supports static max_p parameter setting values for relative and each class proportional loss differentiation. M-RED is static according to the situation of the network traffic, Network environment is very dynamic situation. Therefore max_p parameter values needs to modify too to the constantly and dynamic. The verification of the guidance is shown with figuring out loss probability using a proposed algorithm under dynamic offered load and is also selection problem of optimal values of parameters for high traffic intensity and show that Dynamic-VQSDDP has the better performance in terms of packet drop rate. We also demonstrated using an ns-2 network simulation.