• The Journal of the Acoustical Society of Korea
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• v.16 no.3E
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• pp.7-13
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• 1997

This paper addresses traffic prediction issues on MPEG. A new adaptive traffic prediction scheme is proposed using MPEG picture characteristic that picture traffic depends on the coding mode of that picture, that is, I, P, and B mode. Our prediction scheme, which is based n picture decomposition (PD) and the cross-correlation of the different types of pictures, has better performance in predicting bursty MPEG traffic than that of the first-order autoregressive (AR) prediction scheme. Our simulation results show that the performance is further improved about 15% by utilizing the cross-correlations between pictures.

• ETRI Journal
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• v.30 no.2
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• pp.290-300
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• 2008

We apply IEEE 802.3 frame burst mode (FBM) to the Ethernet passive optical network (EPON) downstream link and compare its performance with non-frame burst mode for various traffic patterns. Although in light traffic loads (p<0.5) the efficiency of the FBM mechanism is not significant, it does feature high throughput, small jitter, low queue occupancy, and short queuing delay in optical line terminals under various traffic loads with various numbers of optical network units (ONUs). The FBM performance always approaches that of full-duplex mode, especially under heavy traffic loads (p>0.5). Moreover, an increase in number of ONUs will decrease the burst performance. Our work shows that FBM scheme is very useful for EPON transmission and has low design complexity.

• The KIPS Transactions:PartC
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• v.10C no.2
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• pp.217-232
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• 2003

QoS routing can improve network performance while providing support for QoS guarantees. These benefits, however, comes with additional routing costs such as more complex and frequent route computation and the protocol overheads to exchange dynamic network state information. Moreover, little has been done to mininize the impact of the QoS traffic to the best effort traffic or to enhance the routine Performance of the best effort traffic when QoS routing is deployed. In this paper, it is proposed that a sewer based routing mechanism, which supports the QoS routing without incurring the QoS routing protocol overhead for the network state update exchanges and enhances the performance of the best effort traffic without affecting the performance of QoS routing. Simulation results show that the proposed scheme enhances the routing performance for the QoS traffic while reducing the routing protocol overhead. The routing performance of the best traffic is also improved with virtually no impact to the routine performance of the QoS traffic. The proposed scheme is shown to be especially effective when the ratio of QoS traffic is high, that is, when the impact of the QoS traffic to the performance of best effort traffic is significant.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.307-313
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• 2011

In this paper, we compare performance of three models. The Holt-Winters, FARIMA and ARGARCH models, are used in predicting internet traffic data for analysis of traffic characteristics. We first introduce the time series models and apply them to real traffic data to forecast. Finally, we examine which model is the most suitable for explaining the long memory, the characteristics of the traffic material, and compare the respective prediction performance of the models.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.2
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• pp.139-155
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• 2003

The aim of this study is to identify the data traffic capacity of 3G mobile communication networks, especially of cdma2000-1X networks. Three-layered ON/OFF traffic model is used to describe the dynamics of data traffics and the process of data transmission such as packet scheduling. We construct a simulator fully incorporating packet handling process of cdma2000-lX data network as well as three-layered ON/OFF traffic model describing the behavior of source data traffics. To get influence of traffic parameters on performance measures, the extensive simulations were performed for several data sets which are obtained from real trace data or previous studies. The experimental results show that the engineered throughput satisfying QoS criteria is approximately 25% of total capacity. Finally, some proposals to improve the system capacity are followed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1B
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• pp.17-24
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• 2008

The effect of the variable packet size on the LRD characteristic of the MMPP traffic model is investigated. When we generate packet traffic for the performance evaluation of IP packet network, MMPP model can be used to generate packet interarrival time. And a random length of packet size from a certain distribution can be assigned to each packet. However, there is a possibility that the variable packet size might change the LRD characteristic of the original MMPP model. In this study, we investigate this possibility. For this purpose the 'refined traffic' is defined, where packet arrival time is generated according to the MMPP model and a random packet length from a specific distribution is assigned to each generated packet. Hurst parameter of the refined traffic is estimated and compared with the original Hurst parameter, which is the input parameter of the MMPP model. We also investigate the effect of the packet size distribution on the queueing performance of the MMPP traffic model and the relationship between the Hurst parameter and queueing performance.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.225-232
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• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.5
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• pp.378-383
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• 2005

Traffic engineering is a technology that guarantees quality of service that users want and maximize inflection degree of network resources at the same time as evenly distributing traffic to whole network. To improve performance of network at traffic and resources level, traffic engineering aims at utilizing network resource efficiently and effectively and must be satisfied performance requirement concerned with traffic. In this paper, two models to embody traffic engineering are analyzed and finally functional structure of IP/WDM traffic engineering is explained.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1244-1253
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• 2018

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.84-92
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• 2006

To defeat abnormal traffic driven by DoS (Denial-of-Service) or DDoS (Distributed DoS), there has been a variety of researches or studies in a few decades. In this paper, we present the results of theoretical performance analysis between attack prevention schemes and attack mitigation schemes. The former is a scheme that prevents abnormal incoming traffic from forwarding into a specific network based on filtering rules, and the latter is a scheme that makes some perimeter or intermediate routers, which exist on the traffic forwarding path, prevent abnormal traffic based on their own abnormal traffic information, or that mitigates abnormal traffic by using quality-of-service mechanisms at the gateway of the target network. The aspects of theoretical performance analysis are defined as the transit rates of either normal traffic or false-positive traffic after an attack detection routine processes its job, and we also present the concrete network bandwidth rates to control incoming traffic.