• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.115-118
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• 2000

In order to control the flow of traffics in ATM networks and optimize the usage of network resources, an efficient control mechanism is necessary to cope with congestion and prevent the degradation of network performance caused by congestion. To effectively control traffic in UNI(User Network Interface) stage, we proposed algorithm of integrated model using on-line teaming neural network for CAC(Call Admission Control) and UPC(Usage Parameter Control). Simulation results will show that the proposed adaptive algorithm uses of network resources efficiently and satisfies QoS for the various kinds of traffics.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.629-637
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• 2000

Unbalance between user requirements and insufficient network resources makes a congestion. In the future since the communication networks will have very heavy traffic congestion will be more serious. The ATM networks was recommended to support the B-ISDN service for the future multimedia communication. In thie sense of congestion avoidance and recovery the ABR service category in ATM networks allows the feedback flow control mechanism to dynamically allocate the idle bandwidth of the network to users fairly and to control the network congestion rapidly In this paper we introduce a congestion control scheme using systematical approach to confirm robust stability with respect to unknown round trip delay for the network which has both unicast and multicast connections.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1520-1524
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• 2000

TCP congestion control algorithm prevents network congestion through the control of outgoing traffic size. The network, therefore, should monitor the incoming traffic size of a TCP to determine whether or not a TCP follows standard congestion control algorithms. Some TCP friendly test algorithms are proposed, But, these algorithms cannot be used in real environments because a router in a network does not know the RTT of a TCP flow. In this study, we propose a new RTT determination algorithm that can be used in a router. Our proposed algorithms is validated through the simulation studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.2
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• pp.264-270
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• 2006

In this paper we verified that the window based TCP performance of throughput can be improved by the traffic connection efficiency. and have studied the performance of traffic congestion control that is controlling transmission rate. In wireless network, the bidirectional node is run by estimating the usage rate of link of error control idle and the throughput is shown by transmitting segments. The throughput rate shows almost no delay due to the bidirectional traffic connection efficiency up to the allowable point as increasing the transport rate by the critical value, depending on the size of end-to-end node queue of the increase of transport rate. This paper reports the performance improvement as the number of feedback connection traffic congestion control increases because of the increase of the number of asynchronous transport TCP connections.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.316-323
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• 1995

This paper presents an image processing technique to get traffic information such as vehicle volume, velocity, and occupancy for measuring the traffic congestion rate. To obtain these information, two horizontal lines are previously set on the screen. A moving vehicle is detected using the gray level difference on each line, and also template matching method at night. Threshold values are determined by sampling pavement grey level, and updated dynamically to cope with the change of ambient light conditions. These technique is successfully used to calculate vehicle volume, occupancy, and velocity. This study can be applied to traffic signal control system for minimizing traffic congestion in urban areas.

• Journal of Korea Multimedia Society
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• v.11 no.8
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• pp.1051-1058
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• 2008

The advancement of technology for image processing and communications makes it possible for current traffic signal controllers and vehicle detection technology to make both emergency vehicle preemption and transit priority strategies as a part of integrated system. Present]y traffic signal control in crosswalk is controlled by fixed signals. The signal control keeps regular signals traffic even with no traffic, when there is traffic, should wait until the signal is given. Waiting time causes the risk of traffic accidents and traffic congestion in accordance with signal violation. To help reduce the risk of accidents and congestion, this paper explains traffic signal control system for the adaptive priority order so that signal may be preferentially given in accordance with the situation of site through the object detect images.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.23-30
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• 2022

Recently, traffic congestion and environmental pollution have occurred due to population concentration and vehicle increase in large cities. Various studies are being conducted to solve these problems. Most of the traffic congestion in cities is caused by traffic signals at intersections. This paper proposes a dynamic traffic light control (DTLC) scheme to support safe vehicle operation and smooth traffic flow using real-time traffic information based on VANET. DTLC receives instantaneous speed and directional information of each vehicle through road side units (RSUs) to obtain the density and average speed of vehicles for each direction. RSUs deliver this information to traffic light controllers (TLCs), which utilize it to dynamically control traffic lights at intersections. To demonstrate the validity of DTLC, simulations were performed on average driving speed and average waiting time using the ns-2 simulator. Simulation results show that DTLC can provide smooth traffic flow by increasing average driving speed at dense intersections and reducing average waiting time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4A
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• pp.241-249
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• 2005

ATM based MPLS(Multiprotocol Label Switching) is discussed for its provisioning QOS commitment capabilities, Traffic engineering and smooth migration for BcN in Korea. At this time, due to the comprehensive nature of ATM protocol, ATM has been adapted as the backbone system for carrying Internet traffic[1,2,3,4]. This paper presents preventive congestion control mechanisms for detecting HTR(Hard-To-Reach) LSP(Label Switched Path) in ATM based MPLS systems. In particular, we have introduced a HTR LSP detection method using network signaling information in an ATM layer. MPLS related studies can cover LSP failures in a physical layer fault, it can not impact network congestion status. Here we will present the research results for introducing HTR LSP detection methods and control mechanisms and this mechanism can be implementing as SOC for high speed processing a packet header. We concluded that it showed faster congestion avoidance abilities with a more reduced system load and maximized the efficiency of network resources by restricting ineffective machine attempts.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2779-2789
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• 1999

In this paper, we propose a new neural Buffered Leaky Bucket algorithm for preventing the degradation of network performance caused by congestion and dealing with the traffic congestion in ATM networks. We networks. We justify the validity of the suggested method through performance comparison in aspects of cell loss rate and mean transfer delay under a variety of traffic conditions requiring the different QoS(Quality of Service). also, the cell scheduling algorithms such as DWRR and DWEDF used for multiplexing the incoming traffics are induced to get the delay time of the traffics fairly. The network congestion information from cell scheduler is used to control the predicted traffic loss rate of Neural Leaky Bucket, and token generation rate is changed by the predicted values. The prediction of traffic loss rate by neural networks can effectively reduce the cell loss rate and the cell transfer delay of next incoming cells and be applied to other traffic control systems. Computer simulation results performed for traffic prediction show that QoSs of the various kinds of traffics are increased.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.375-378
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• 2011

Measurement of network traffic have shown that the self-similarity is a ubiquitous phenomenon spanning across diverse network environments. In previous work, we have explored the feasibility of exploiting the long-range correlation structure in a self-similar traffic for the congestion control. We have advanced the framework of the multiple time scale congestion control and showed its effectiveness at enhancing performance for the rate-based feedback control.