• ETRI Journal
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• v.33 no.2
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• pp.219-229
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• 2011

In this paper, we propose a transformation scheme used to analyze online gaming traffic properties and develop a traffic model. We analyze the packet size and the inter departure time distributions of a popular first-person shooter game (Left 4 Dead) and a massively multiplayer online role-playing game (World of Warcraft) in order to compare them to the existing scheme. Recent online gaming traffic is erratically distributed, so it is very difficult to analyze. Therefore, our research focuses on a transformation scheme to obtain new smooth patterns from a messy dataset. It extracts relatively heavy-weighted density data and then transforms them into a corresponding dataset domain to obtain a simplified graph. We compare the analytical model histogram, the chi-square statistic, and the quantile-quantile plot of the proposed scheme to an existing scheme. The results show that the proposed scheme demonstrates a good fit in all parts. The chi-square statistic of our scheme for the Left 4 Dead packet size distribution is less than one ninth of the existing one when dealing with erratic traffic.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.9-13
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• 2016

With the introduction of the data-oriented plan for LTE service, one may concerned with the background of the ISP's policy in charging for LTE services. In this work we investigate the latest usage patterns of voice and data applications for customers over the current mobile network, via which we investigate why mobile operators introduced data-oriented plans. To be specific, we collected the real-field data for the volume of voice and data traffic from the LTE network before the data-oriented plans were introduced. From the collected data we compute the absolute volume as well as the proportion of voice and data applications. From these observations we infer mobile operators' reasoning behind the decision to introduce data-oriented plans with unlimited voice calls over the mobile network.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.859-864
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• 2001

An effective live load model for analyzing probable maximum live load effects such as moment and shear in transverse direction was developed. The main procedure of this live load model is composed of four parts, i.e., firstly, determination of the appropriate influence lines in longitudinal direction, secondly, application of the characteristics of vehicles and traffic patterns in longitudinal direction, thirdly, determination of the appropriate influence lines in transverse direction, and fourthly, application of the characteristics of vehicles and traffic patterns in transverse direction. Through this procedure, the probabilistic distributions of maximum probable load effects are deduced in the form of probability density function (PDF) and/or cumulative density function(CDF). This live load model is able to consider local or global deterioration of bridges in the structural analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.3
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• pp.135-149
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• 2008

Traditional attack detection schemes based on packets or flows have very high computational complexity. And, network based anomaly detection schemes can reduce the complexity, but they have a limitation to figure out the pattern of the distributed global scale network attack. In this paper, we propose an efficient and fast method for detecting distributed global-scale network attack symptoms in high-speed backbone networks. The proposed method is implemented at the aggregate traffic level. So, our proposed scheme has much lower computational complexity, and is implemented in very high-speed backbone networks. In addition, the proposed method can detect attack patterns, such as attacks in which the target is a certain host or the backbone infrastructure itself, via collaboration of edge routers on the backbone network. The effectiveness of the proposed method are demonstrated via simulation.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.40-52
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• 2011

This paper develops a traffic condition decision algorithm to improve the reliability of traffic information on urban streets. This research is reestablished the criteria of qualitative traffic condition categorization and proposed a new qualitative traffic condition decision types and decision measures. The developed algorithm can be classified into 9 types for qualitative traffic condition in consideration of historical time series of speed changes and traffic patterns. The performance of the algorithm is verified through individual matching analysis using the radar detector data in Ansan city. The results of this paper is expected to help promotion of the traffic information processing system, real-time traffic flow monitoring and management, use of historical traffic information, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.17-32
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• 1996

In this paper, a model for two-layered video traffic is proposed. The performance analysis of the proposed model and the effects of two-layer coding scehemes in ATM networks are also studied. ATM-based networks give the possibility to support image codingat variable bit rate(VBR). Two layer coding is one of the very promising methods among many proposed methods to compensate the cell loss, the major drawback in ATM networks. From the experimental data of the 2-layer coded video traffics, it is observed that traffic patterns of base layer and enhanced layer are highly correlate to each other, when constant image quality is kept. With this observation, coded two layered video traffic can be modeled as 2-dimensional Markov chain. The model well fit the real experimental data. The model was used for the analysis of the performance of statistical multiplexer with priorites in ATM networks.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.59-62
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• 2001

This paper discusses a data mining technique for time series analysis of traffic data, which provides useful knowledge for network configuration management. Commonly, a network designer must employ a combination of heuristic algorithms and analysis in an interactive manner until satisfactory solutions are obtained. The problem of heuristic algorithms is that it is difficult to deal with large networks and simplification or assumptions have to be made to make them solvable. Various data mining techniques are studied to gain valuable knowledge in large and complex telecommunication networks. In this paper, we propose a traffic pattern association technique among network nodes, which produces association rules of traffic fluctuation patterns among network nodes. Discovered rules can be utilized for improving network topologies and dynamic routing performance.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.42-48
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• 2015

This paper has its purpose on constructing a prediction model of the arrival sequencing strategy which reflects the actual sequencing patterns of air traffic controllers. As the first step, we analyzed a pair-wise sequencing of two aircraft entering TMA from different entering points. Based on the historical trajectory data, several traffic factors such as time, speed and traffic density were examined for the model. With statistically significant factors, we constructed a prediction model of arrival sequencing through a binary logistic regression analysis. With the estimated coefficients, the performance of the model was conducted through a cross validation.

• Journal of the Ergonomics Society of Korea
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• v.26 no.2
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• pp.89-102
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• 2007

Generally, it is well known that driving in tunnel imposes large burden to driver because of spatial constraint, limited visual field and so on. And such a burden of driver result in high accident occurrence. In this reason, studies dealing with features of driving and traffic flow in tunnel have been performed. However, information about characteristics of drivers and traffic in a very long tunnel is not accumulated yet. The purpose of this study is to identify the relations between tunnel length and burden of driver, driving patterns, traffic flow characteristics using the tunnel simulator that realizing various tunnel situations. For this, the tunnel simulation program was developed along 11km-length section. And biological data of 10 subjects gained from driving condition in simulation program was analyzed and compared with the result of real driving condition.