• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.99-109
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• 2007

There have been few studies on the impacts of independent recurrent and non-recurrent congestion on freeway networks. The main reason is due partly to the lack of traffic data collected during those periods of recurrent and non-recurrent congestion and partly to the difficulty of using the simulation tools effectively. This study has suggested a methodology to analyze the independent impacts of the recurrent and non-recurrent congestion on target freeway segments. The proposed methodology is based on an elaborately calibrated simulation analysis, using real traffic data obtained during the recurrent and non-recurrent congestion periods. This paper has also summarized the evaluation results from the field tests of two ITS technologies, which were developed to provide drivers with real-time traffic information under traffic congestion. As a result, their accuracy may not be guaranteed during the transition periods such as the non-recurrent congestion. In summary, this study has been focused on the importance of non-recurrent congestion compared to recurrent congestion, and the proposed methodology is expected to provide a basic foundation for prioritizing limited government investments for improving freeway network performance degraded by recurrent or non-recurrent congestion.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.31-41
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• 2014

This paper proposes a virtual mobile ad-hoc network (VMANET) model that automatically divides heterogeneous mobile devices of a MANET into a number of network groups depending on the communication capacity(data rate) of different network operational models such as IEEE 802.11g, IEEE 802.11b, and Frequency Hopping. In addition, it supports a distinct routing protocol for each network group of VMANETs, resulting in running multiple routing protocols concurrently on different groups of VMANETs. To reduce the network congestion and improve the network load balance, a default MANET gateway is configured in each VMANET and these gateways are responsible for integrating the MANET and IP networks. Experiment results show that the proposed model outperforms the conventional IMANET by significantly increasing throughput and reducing network congestion and network delay.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.18-24
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• 2013

Network coding has been extensively studied to increase the network throughput by exploiting the broadcast and overhearing capabilities. In this paper, we formulate a network utility maximization problem to improve the network utility in multichannel, multiradio and multisession wireless multihop network with intrasession network coding. To find the solution of this problem, we propose a congestion control, distributed rate control, and heuristic resource allocation algorithm. We find the network utility and evaluate the performance in multichannel, multiradio and multisession environment by using MATLAB. Finally, the results show that the proposed schemes can achieve throughput improvement by performing the network utility optimization in wireless multihop network.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.4
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• pp.19-35
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• 2007

This study is for detecting the Braess Paradox by stable dynamics in general transportation networks. Stable dynamics, suggested by Nesterov and de Palma[18], is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with user equilibrium model based on link latency function in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on the congestion. Therefore it is expected to be an useful analysis tool for transportation planners. The phenomenon that increasing capacity of a network, for example creating new links, may decrease its performance is called Braess Paradox. It has been studied intensively under user equilibrium model with link latency function since Braess[5] demonstrated a paradoxical example. However it is an open problem to detect the Braess Paradox under stable dynamics. In this study, we suggest a method to detect the Paradox in general networks under stable dynamics. In our model, we decide whether Braess Paradox will occur in a given network. We also find Braess links or Braess crosses if a network permits the paradox. We also show an example how to apply it in a network.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2196-2207
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• 2017

This paper presents a two-stage market auction model in a pool-based electricity market, which explicitly takes into account the system network security. The security network-constrained market auction model considers the use of corrective control to yield economically efficient actions in the post-contingency state, while ensuring a certain security level. Under this framework, the proposed model shows not only for quantifying the correlation between secure system operation and efficient market operation, but also for providing transparent information on the pricing system security for market participants. The two-stage market auction procedure is formulated using Benders decomposition (BD). In the first stage, the market participants bid in the market for maximizing their profit, and the independent system operator (ISO) clears the market based on social welfare maximization. System network constraints incorporating post-contingency control actions are described in the second stage of the market auction procedure. The market solutions, along with the BD, yield nodal spot prices (NSPs) and nodal congestion prices (NCPs) as byproducts of the proposed two-stage market auction model. Two benchmark systems are used to test and demonstrate the effectiveness of the proposed model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.6
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• pp.109-116
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• 2007

The lack of load-balancing functionality in most existing ad hoc routing protocols often causes congestion resulting in bad performance and short lifetime of participating nodes. We present an auxiliary scheme for reactive routing protocols to discover an unloaded route, thereby decreasing possibility of congestion. The scheme allows an intermediate node to determine whether to be a relaying node for a newly constructed route autonomously based on the occupancy of its queue. Thus the scheme does not require network-wide load information. Simulation results show that the proposed scheme distributes traffic load well.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.19-31
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• 2016

A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.10 s.352
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• pp.8-17
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• 2006

Recently, the high-speed Internet users increase rapidly and broadband networks have been widely deployed. However, the current TCP congestion control algorithm was designed for relatively narrowband network environments, and thus its performance is inefficient for traffic transport in broadband networks. To remedy this problem, the TCP having an enhanced congestion control algorithm is required for broadband networks. In this paper, we propose an improved TCP congestion control that can sufficiently utilize the large available bandwidth in broadband networks. The proposed algorithm predicts the available bandwidth by using ACK information and RTT variation, and prevents large packet losses by adjusting congestion window size appropriately. Also, it can rapidly utilize the large available bandwidth by enhancing the legacy TCP algorithm in congestion avoidance phase. In order to evaluate the performance of the proposed algorithm, we use the ns-2 simulator. The simulation results show that the proposed algorithm improves not only the utilization of the available bandwidth but also RTT fairness and the fairness between contending TCP flows better than the HSTCP in high bandwidth delay product network environment.