• Korean Management Science Review
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• v.26 no.1
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• pp.161-169
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• 2009

A traffic analysis on the Internet has an advantage for obtaining the characteristics of transferred packets. There were many studies to understand the characteristics of the Internet traffic with mathematical statistical approach. The approach of this study is different from previous studies. We first introduced a virtual network concept to present the Internet as a simplified mathematical model. It also represents each traffic flowing on the Internet as a parallel Gaussian channel on the virtual network. We suggest the optimal capacity of each parallel Gaussian channel using some related studies on the Gaussian channel model.

• Ocean Systems Engineering
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• v.12 no.3
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• pp.267-284
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• 2022

A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.10
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• pp.40-47
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• 1996

A method for computing effectiv ebandwidth of aggregated varable bit rate (VBR) moving picture experts group (MPEG) video traffic is proposed. To compute statistical characteristics of aggregated MPEG traffic, first we split input MPEG traffic into I, B, and P frame traffics and aggregate respective I, B, and P frame traffics according to the frame type. Second statisticsal characteristics of the aggregated MPEG traffic are obtained using those of aggregated I, B, and P frame traffics. The effective bandwidth of the aggregated I frame traffic is computed by using the gaussian bound. Using the modified equivalent capacity, we obtain the effective bandwidths of aggregated B and P frame traffics and then compute the effective bandwidth of the combined B and P frame traffic. Finally the effective bandwidth of the aggregated MPEG traffic is computed by adding the gaussian bound of the aggregated I frame traffic and modifed equivalent capacity of combined B and P frame traffic. Computer simulation shows that the proposed method estimates effective bandwidth of the aggregated MPEG traffic well.

• Journal of KIISE:Information Networking
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• v.29 no.5
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• pp.553-561
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• 2002

We present a novel service discipline, called linear service discipline, to serve multiple QoS queues sharing a resource and analyze its properties. The linear server makes the output traffic and the queueing dynamics of individual queues as a linear function of its input traffic. In particular, if input traffic is Gaussian, the distributions of queue length and output traffic are also Gaussian with their mean and variance being a function of input mean and input power spectrum (equivalently, autocorrelation function of input). Important QoS measures including buffer overflow probability and queueing delay distribution are also expressed as a function of input mean and input power spectrum. This study explores a new direction for network-wide traffic management based on linear system theories by letting us view the queueing process at each node as a linear filter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.667-680
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• 2008

In this work, we present the results of our empirical study on 802.11 wireless LAN network traffic. We collect the packet trace from existing campus wireless LAN infra-structure. We analyzed four different data sets: aggregate traffic, upstream traffic, downstream traffic, tcp only packet trace from aggregate traffic. We analyze the time series aspect of underlying traffic (byte count process and packet count process), marginal distribution of time series, and packet size distribution. We found that in all four data sets there exist long-range dependent property in byte count and packet count process. Inter-arrival distribution is well fitted with Pareto distribution. Upstream traffic, i.e. from the user to Internet, exhibits significant difference in its packet size distribution from the rests. Average packet size of upstream traffic is 151.7 byte while average packet size of the rest of the data sets are all greater than 260 bytes. Packets with full data payloads constitutes 3% and 10% in upstream traffic and the downstream traffic, respectively. Despite the significant difference in packet size distribution, all four data sets have similar Hurst values. The Hurst alone does not properly explain the stochastic characteristics of the underlying traffic. We model the underlying traffic using fractional-ARIMA (FARIMA) and fractional Gaussian Noise (FGN). While the fractional Gaussian Noise based method is computationally more efficient, FARIMA exhibits superior performance in accurately modeling the underlying traffic.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.169-183
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• 2010

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.52-61
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• 2006

For the detection of moving objects, background subtraction methods are widely used. An adaptive Gaussian mixture model combined with probabilistic learning is one of the most popular methods for the real-time update of the complex and dynamic background. However, probabilistic learning approach does not work well in high traffic regions. In this paper, we Propose a reliable learning method of complex and dynamic backgrounds in high traffic regions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.12A
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• pp.1828-1835
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• 2000

In this paper, we analyzed the other-cell interference characteristics for various non-uniform traffic distributions and their effects on the capacity of multi-cell CDMA system. We consider three different traffic distributions, i.e., linear, exponential and Gaussian traffic distribution with distribution parameters. Changing the distribution parameter, we can obtain the center-focused distributions or uniform distributions for each model. From the results of other-cell interference calculation we can see that the other-cell interference decreases, as the user concentrates on the base station. Also using frequency reuse efficiency indicating the capacity reduction of a multi-cell system when compared to a single cell system, we evaluate the effect of traffic distribution on the reverse link CDMA capacity. For linear case, the capacity of multi-cell system is reduced to 0.637∼0.867 times that of single cell system. On the other hand, for both exponential and Gaussian cases, the capacity under a multi-cell environment is equal to 70∼100% of that under a single cell. Therefore, we conclude that the average capacity of multi-cell CDMA system are increased when users are likely to be at near the cell base station due to reduced total other-cell interference and decreased when users exist at near the cell edge regardless of traffic distribution models.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.173-183
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• 2015

At present, it is simple to the electronic commerce credit scoring model, as a brush credit phenomenon in E-commerce has emerged. This phenomenon affects the judgment of consumers and hinders the rapid development of E-commerce. In this paper, that E-commerce credit evaluation model that uses a Gaussian density function is put forward by density test and the analysis for the anomalies of E-commerce credit rating, it can be fond out the abnormal point in credit scoring, these points were calculated by nonlinear credit scoring algorithm, thus it can effectively improve the current E-commerce credit score, and enhance the accuracy of E-commerce credit score.