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

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.103-118
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• 2014

Over the last couple of years, traditional VANET (Vehicular Ad Hoc NETwork) evolved into VANET-based clouds. From the VANET standpoint, applications became richer by virtue of the boom in automotive telematics and infotainment technologies. Nevertheless, the research community and industries are concerned about the under-utilization of rich computation, communication, and storage resources in middle and high-end vehicles. This phenomenon became the driving force for the birth of VANET-based clouds. In this paper, we envision a novel application layer of VANET-based clouds based on the cooperation of the moving cars on the road, called CaaS (Cooperation as a Service). CaaS is divided into TIaaS (Traffic Information as a Service), WaaS (Warning as a Service), and IfaaS (Infotainment as a Service). Note, however, that this work focuses only on TIaaS and WaaS. TIaaS provides vehicular nodes, more precisely subscribers, with the fine-grained traffic information constructed by CDM (Cloud Decision Module) as a result of the cooperation of the vehicles on the roads in the form of mobility vectors. On the other hand, WaaS provides subscribers with potential warning messages in case of hazard situations on the road. Communication between the cloud infrastructure and the vehicles is done through GTs (Gateway Terminals), whereas GTs are physically realized through RSUs (Road-Side Units) and vehicles with 4G Internet access. These GTs forward the coarse-grained cooperation from vehicles to cloud and fine-grained traffic information and warnings from cloud to vehicles (subscribers) in a secure, privacy-aware fashion. In our proposed scheme, privacy is conditionally preserved wherein the location and the identity of the cooperators are preserved by leveraging the modified location-based encryption and, in case of any dispute, the node is subject to revocation. To the best of our knowledge, our proposed scheme is the first effort to offshore the extended traffic view construction function and warning messages dissemination function to the cloud.

• Journal of Environmental Science International
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• v.32 no.1
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• pp.37-46
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• 2023

This study investigated the effect of May 31, 2022 Miryang wildfire on fine particle concentrations in Busan and Gimhae, which are neighboring urban areas. In addition, fine particle characteristics and air pollution concentrations were investigated in Miryang, where haze occurred. The Miryang city wildfire that occurred on May 31, 2022, at 0925 LST, was driven by strong north winds and increased fine particle concentrations in Dongsangdong and Jangyoodong, Gimhae City, which are approximately 35 km to the southeast and south, respectively, of the wildfire occurrence site. Furthermore, the fine particle concentration in Myeongjidong, which is approximately 50 km south-southeast of the wildfire site, exhibited a temporary increase at 1400 LST owing to the effects of wildfire smoke. On the morning of June 1, the day after the fire, the Miryang area had very bad visibility because of the smoke from the fire. Therefore the PM₁₀ and PM_2.5 concentrations in Naeildong, 3 km south of the wildfire site, were 276 ㎍/㎥ and 222 ㎍/㎥, respectively, at 1200 LST. In addition, the gases O₃, CO, and SO₂ showed high concentrations at the time of haze generation. This study provides insights into policy making in response to the rapid increase in fine dust when wildfire occurs near cities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.859-876
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• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.151-160
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• 2010

For the realization of future intelligent transportation systems, fine-grained lane-by-lane traffic monitoring and control functionalities are among the most important technology barriers to overcome. To satisfy the accuracy requirement for traffic monitoring, a GNSS receiver network is designed. The designed receiver network consists of three different types of entities; reference server, broadcaster, and client. For deployment flexibility, all the entities utilize the international message standard RTCM SC-104 version 3.0. For fine-grained traffic monitoring, the client is designed to utilize position-domain carrier-smoothed-code filters to provide accurate vehicle coordinates in spite of frequent addages and outages of visible satellites. An experiment result is presented to evaluate the positioning accuracy of the proposed method.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.111-118
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• 2009

Factors causing traffic accidents are various and traffic law violations can be among them. The efforts to increase traffic law obedience rates of drivers are common in many other countries to reduce traffic accidents, and one of generally applied methods is to increase the amounts of violation fines. Expensive levels of traffic law violation fines could have drivers choose "obey the law" in their decision-making stages since they are economically better-off by following the law. In this sense, this study has developed an economic model to verify whether the current levels of the traffic violation fines of Korea are effective for drivers to choose "obey-the-law" decisions. Speed violations and traffic signal violations have been selected for the case study to verify the relationships between "expected probabilities of being-caught" and "levels of violations fines".

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.5
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• pp.523-528
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• 1996

Aerosol Particles were collected in a heaby traffic region in pusan. Samples were collected in two size fractions with a two-stage sampler during the day and the night. Elemental concentrations of these aerosol particles were determined by a PIXE(Proton Induced X-ray Emission) analysis method. The results suggest that the elements originating mainly from natural sources such as Si, Ca, Fe, Cl, and K are dominent in the coarse fraction, but the elements such as S, Pb, Br, and Zn are dominent in the fine fraction. Br/Pb ratio are evaluated in both coarse and fine size fraction, and which are mainly emitted automobile sources. The study further also discussed other Br/Pb ratio related works described elsewhere. Sulfur in the fine fraction was continuously increased during the sampling period without time variation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.623-631
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• 2011

In this study, a new method which can detect incidents in interrupted traffic flow was suggested. The applied method of detecting the incident is the Latin Square Analysis Method by using traffic traits. In the Latin Square Analysis, unlike other previously tried methods, the traffic situation was analyzed, this time considering the changes in traffic traits for each lane and for each time period. The data used in this study were the data observed in the actual field with fine weather. The traffic volumes, the vehicle speed and the occupancy rate were collected on the interrupted flow road. The data were collected in normal and incident situations. The incidents occurred on the second lane, the time of persistent incidents was set to 10 minutes. The Latin Square Analyses were performed using the collected data with the traffic volume, with the vehicle speed or with the occupancy rate. As a result in this study, in case of detecting the traffic situations with Latin Square Analysis, it will be more successful to apply traffic volume to detect the traffic situations than to apply other factors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.12-26
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• 2014

This Study deals with effect of low visibility condition at nighttime on traffic accident. Roads for experiment of this study are Gyeongbu expressway, Seohaean expressway, Yeongdong expressway and Seoul beltway in Gyeonggi province. For this study, I subdivided basic straight section of them into 58 short section. And I analyzed effect of low visibility condition by darkness at nighttime on traffic accident by using 410 traffic accidents between January 1, 2009 and June 30, 2012 on those sections. The Quasi-experimental and negative binomial regression were applied to analyze effect of low visibility condition at nighttime on traffic accident. In this study, I only analyzed visibility difference of daytime and nighttime on traffic accident except other effective variables on traffic accidents. As a result, I have found that it is for low visibility condition at nighttime to have effect on traffic accidents at such specific conditions as Los A speed is maintained in basic straight section of expressway in fine weather. And I tried to do various analysis on types and causes of traffic accidents using the result of analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.921-928
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• 2011

The increase of Internet users and services has caused the upsurge of data traffic over the network. Nowadays, variety of Internet applications has emerged which generates complicated and diverse data traffic. For the efficient management of Internet traffic, many traffic classification methods have been proposed. But most of the methods focused on the application-level classification, not the function-level classification or state changes of applications. The functional classification of application traffic makes possible the in-detail understanding of application behavior as well as the fine-grained control of applications traffic. In this paper we proposed automata based functional classification method of IM application traffic. We verified the feasibility of the proposed method with function-level control experiment of IM application traffic.