• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.99-107
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• 2016

PURPOSES : This study was initiated to estimate expressway traffic congestion costs by using Vehicle Detection System (VDS) data. METHODS : The overall methodology for estimating expressway traffic congestion costs is based on the methodology used in a study conducted by a study team from the Korea Transport Institute (KOTI). However, this study uses VDS data, including conzone speeds and volumes, instead of the volume delay function for estimating travel times. RESULTS : The expressway traffic congestion costs estimated in this study are generally lower than those observed in KOTI's method. The expressway lines that ranked highest for traffic congestion costs are the Seoul Ring Expressway, Gyeongbu Expressway, and the Youngdong Expressway. Those lines account for 64.54% of the entire expressway traffic congestion costs. In addition, this study estimates the daily traffic congestion costs. The traffic congestion cost on Saturdays is the highest. CONCLUSIONS : This study can be thought of as a new trial to estimate expressway traffic congestion costs by using actual traffic data collected from an entire expressway system in order to overcome the limitations of associated studies. In the future, the methodology for estimating traffic congestion cost is expected to be improved by utilizing associated big-data gathered from other ITS facilities and car navigation systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.1-11
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• 2014

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4342-4366
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• 2016

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

• Annual Conference of KIPS
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• 2009.11a
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• pp.465-466
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• 2009

This paper investigates congestion detection and control strategies for multi-path traffic (CDCM) diss emination in lifetime-constrained wireless sensor networks. CDCM jointly exploits packet arrival rate, succ essful packet delivery rate and current buffer status of a node to measure the congestion level. Our objec tive is to develop adaptive traffic rate update policies that can increase the reliability and the network lif etime. Our simulation results show that the proposed CDCM scheme provides with good performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1A
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• pp.16-24
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• 2010

High Speed Uplink Packet Access(HSUPA) is a WCDMA Release 6 technology which corresponds to High Speed Downlink Packet Access(HSDPA). Node B Supports fast scheduling, Hybrid ARQ(HARQ), short Transmission Time Interval(TTI) for high rate uplink packet data. It is very important to detect Iub congestion to improve end user's Quality of Service(QoS). This paper proposes Node B Congestion Detection(BCD) mechanism and suggests to use the hybrid of Transport Network Layer(TNL) congestion detection and BCD. It is shown that HSUPA user throughput performance can be improved by the proposed method even with small Iub bandwidth.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.343-350
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• 2010

Wireless Sensor Network is an event-driven system that a large number of micro sensor nodes are collected, giving and Wing information. Congestion can take place easily since a great number of sensor nodes are sensing data and transferring them to sink nodes when an event occurs, comparing to the existing wired network. Current internet transport protocol is TCP/UDP, however, this is not proper for wireless sensor network event-driven ESRT, STCP and CODA are being studied for reliable data transport in the wireless sensor network. Congestion are being detected local buffer and channel loading with these techniques. Broadcasting is mainly used and can avoid congestion when one happens. The way that combining local buffer and channel loading information and detecting congestion is being studied in this paper. When congestion occurs, buffering state is divided into three in order to lessen the broadcasting sending the message on congestion control to the node having frequent channel loading. Thus they have advantage of decreasing network's loading.

• 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.