• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.465-466
• /
• 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.

• IE interfaces
• /
• v.23 no.4
• /
• pp.349-356
• /
• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.6
• /
• pp.722-728
• /
• 2003

In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.1291-1293
• /
• 2007

Due to dense deployment and innumerable amount of traffic flow in wireless sensor networks (WSNs), congestion becomes more common phenomenon from simple periodic traffic to unpredictable bursts of messages triggered by external events. Even for simple network topology and periodic traffic, congestion is a likely event due to dynamically time varying wireless channel condition and contention caused due to interference by concurrent transmissions. In this paper, we have proposed three mechanisms: upstream source count and buffer based rate control and snoop based MAC level ACK scheme to avoid congestion. The simulation results show that our proposed mechanism achieves around 80% delivery ratio even under bursty traffic condition

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.4
• /
• pp.381-388
• /
• 2018

This study proposes marine traffic volume estimation method considering ship speed, a factor excluded from the existing method. Ten days of GICOMS marine traffic data from Pyeongtaek and Dangjin ports was applied to this study. As a result, converted traffic volume with the proposed estimation method showed an increase of 4.41 (${\pm}0.99$) times or decrease of 0.59 (${\pm}0.04$) at most, compared with the existing estimation method. Average marine traffic congestion for each time applying the proposed estimation method showed an increase of 1.43 (${\pm}0.10$) compared with the existing estimation method. The maximum marine traffic congestion for each time was 1.62 (${\pm}0.34$) times higher compared with the existing estimation method. Marine traffic peak time, defined as the highest point of marine traffic congestion, was evaluated to be different from that of the existing method because of distribution of vessel speed. In conclusion, considering ship speed is necessary when estimating marine traffic volume to produce a practical estimate of marine traffic capacity.

• Proceedings of the IEEK Conference
• /
• 2000.11a
• /
• pp.21-24
• /
• 2000

End-to-end congestion control mechanism have been critical to the robustness and stability of the Internet. Most of today's Internet traffic is TCP, and we expect this to remain so in the future. TCP/IP is the intermediate transport layer candidate for today's applications. TCP uses an adaptive window-based flow control. The congestion avoidance and control algorithms deployed by TCP aims at using the available network bandwidth. This paper compares different congestion control policies, and proposes the new design mechanism for future public networks

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1998.10a
• /
• pp.323-329
• /
• 1998

In Pusan port, the studies, which analysis container cargo volumes by using forecasting methods and research about container logistics system, etc., have been continuously performed. But, in Pusan port, this study on an evaluation of traffic congestion has been scarcely performed until now. Especially, when changing and extending a berth, and constructing a new port, it is very important to examine this field. And it should be considered. Thus, this paper aims to analysis the effect of ship traffic condition in 2011, to evaluate marine traffic congestion, according to changing ship traffic volumes in Pusan port. To analysis it, we used simulation method and examined the results

• Journal of Korean Port Research
• /
• v.12 no.2
• /
• pp.177-194
• /
• 1998

In Pusan port, the studies which analyze container cargo volumes by using forecasting methods and research about container logistics system, etc., have been continuously carried out. But, in Pusan port, the study on an evaluation of traffic congestion has been scarcely performed until now. Especially, when changing and extending a berth, or constructing a new port, it is very important to examine this field. And it should be considered. Thus, this paper aims to analyze the effect of ship traffic condition in the year 2011, to evaluate marine traffic congestion according to changing ship traffic volumes in Pusan port. To analyze it, we examined the results by simulation method.

• International Journal of Highway Engineering
• /
• v.11 no.1
• /
• pp.25-36
• /
• 2009

Everyday congestion length (distance) and duration (time) data are collected and recorded in Expressway Traffic Information Center. These records are based on the information that the operators watch CCTV and decide traffic condition in order to present information about congestion on VMS. Using VMS message has some merits like that it doesn't need a great lot of cost to construct hardware such like FTMS because operators can check traffic condition by watching CCTV only. Of cause in the aspect of accuracy, using VMS message has the limitation that it is based on subject decision compared with FTMS. However, it can be said that the value of using VMS message is very large. The object of this study is to use the VMS information record (log file) usefully to provide information of traffic condition on expressway for users (drivers) without keeping the VMS information record in dead storage. To do so, in this research, congestion calculation method able to understand traffic congestion condition on expressway was developed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.3
• /
• pp.762-777
• /
• 2014

With the increasing usage of cloud applications such as MapReduce and social networking, the amount of data traffic in data center networks continues to grow. Moreover, these appli-cations follow the incast traffic pattern, where a large burst of traffic sent by a number of senders, accumulates simultaneously at the shallow-buffered data center switches. This causes severe packet losses. The currently deployed TCP is custom-tailored for the wide-area Internet. This causes cloud applications to suffer long completion times towing to the packet losses, and hence, results in a poor quality of service. An Explicit Congestion Notification (ECN)-based approach is an attractive solution that conservatively adjusts to the network congestion in advance. This legacy approach, however, lacks scalability in terms of the number of flows. In this paper, we reveal the primary cause of the scalability issue through analysis, and propose a new congestion-control algorithm called FaST. FaST employs a novel, virtual congestion window to conduct fine-grained congestion control that results in improved scalability. Fur-thermore, FaST is easy to deploy since it requires only a few software modifications at the server-side. Through ns-3 simulations, we show that FaST improves the scalability of data center networks compared with the existing approaches.