• Title/Summary/Keyword: Traffic Rate Analysis

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On-line Prediction Algorithm for Non-stationary VBR Traffic (Non-stationary VBR 트래픽을 위한 동적 데이타 크기 예측 알고리즘)

  • Kang, Sung-Joo;Won, You-Jip;Seong, Byeong-Chan
    • Journal of KIISE:Information Networking
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    • v.34 no.3
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    • pp.156-167
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    • 2007
  • In this paper, we develop the model based prediction algorithm for Variable-Bit-Rate(VBR) video traffic with regular Group of Picture(GOP) pattern. We use multiplicative ARIMA process called GOP ARIMA (ARIMA for Group Of Pictures) as a base stochastic model. Kalman Filter based prediction algorithm consists of two process: GOP ARIMA modeling and prediction. In performance study, we produce three video traces (news, drama, sports) and we compare the accuracy of three different prediction schemes: Kalman Filter based prediction, linear prediction, and double exponential smoothing. The proposed prediction algorithm yields superior prediction accuracy than the other two. We also show that confidence interval analysis can effectively detect scene changes of the sample video sequence. The Kalman filter based prediction algorithm proposed in this work makes significant contributions to various aspects of network traffic engineering and resource allocation.

The Effect of the Buffer Size in QoS for Multimedia and bursty Traffic: When an Upgrade Becomes a Downgrade

  • Sequeira, Luis;Fernandez-Navajas, Julian;Saldana, Jose
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3159-3176
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    • 2014
  • This work presents an analysis of the buffer features of an access router, especially the size, the impact on delay and the packet loss rate. In particular, we study how these features can affect the Quality of Service (QoS) of multimedia applications when generating traffic bursts in local networks. First, we show how in a typical SME (Small and Medium Enterprise) network in which several multimedia flows (VoIP, videoconferencing and video surveillance) share access, the upgrade of the bandwidth of the internal network may cause the appearance of a significant amount of packet loss caused by buffer overflow. Secondly, the study shows that the bursty nature of the traffic in some applications traffic (video surveillance) may impair their QoS and that of other services (VoIP and videoconferencing), especially when a certain number of bursts overlap. Various tests have been developed with the aim of characterizing the problems that may appear when network capacity is increased in these scenarios. In some cases, especially when applications generating bursty traffic are present, increasing the network speed may lead to a deterioration in the quality. It has been found that the cause of this quality degradation is buffer overflow, which depends on the bandwidth relationship between the access and the internal networks. Besides, it has been necessary to describe the packet loss distribution by means of a histogram since, although most of the communications present good QoS results, a few of them have worse outcomes. Finally, in order to complete the study we present the MOS results for VoIP calculated from the delay and packet loss rate.

Traffic Performance Analysis using Asymmetry Wireless Link Network in Transmission Rate Controlled Channels (전송률 제어 채널에서 비대칭 무선 링크 네트워크를 이용한 트래픽 성능 분석)

  • Jeong, You-Sun;Youn, Young-Ji;Shin, Bo-Kyoung;Kim, Hye-Min;Park, Dong-Suk;Ra, Sang-Dong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.8
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    • pp.1434-1440
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    • 2008
  • Performance of TCP/IP is studied on the wireless network using flow control and congestion control mechanism based on transmission rate. We discuss the elimination or the reduction of various phenomena of burst by flow controlling on transmission rate and verify that there are TCP ACK compression promblems on the queue by burst reaction while executing transmission rate controlled channels. Analyzing periodic burst reaction on the queue of source IP, the maximum value of queue is expected, which represents the applible expectation of throughput reduce and shows the improvement of performance by the reduce of throughput due to hi-directional traffic.

Effect of Noise Reduction by Installation of a Point to Point Speed Camera (실측자료를 통한 구간단속카메라의 소음저감효과 분석)

  • Son, Jin Hee;Chun, Hyung-Joon;Choung, Tae Ryaug;Park, Young Min;Kim, Deuk Sung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.27 no.1
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    • pp.57-64
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    • 2017
  • This study was reviewed the noise reduction effects with installation of 'point to point speed camera' for controlling the speed of the car. The multiple regression analysis was performed to know how the relationship between the noise level and these parameters, such as measured traffic volume and rate of heavy vehicle and weighted average speed was changed with and without the 'point to point speed camera'. In the analysis results shows that the less traffic volume, the more noise reduction effect has been increased and the more traffic volume, the more noise reduction effect has been reduced. And noise reduction effects by the 'point to point speed camera' was different from each measured point. The cause of the difference was determined that inadequate 'point to point speed camera' position to see the effect of noise reduction. It is determined to require a more study to improve the noise reduction effects of the 'point to point speed camera' such as the camera position adjustment.

Estimation of Unprotected Left-Turn Saturation Flows (비보호 좌회전 포화유률 추정)

  • 김경환
    • Proceedings of the KOR-KST Conference
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    • 1998.10a
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    • pp.236-244
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    • 1998
  • When the capacity and traffic operation at signalized intersections are analyzed in Korea, the unprotected left-turn saturation flow rate, which is an important parameter for the analysis, is estimated form the USHCM model. thus, exact analysis of the left-turn is not possible because of the difference of traffic environments between two contries. In order to improve this problem, it is undertaken in this study to develop techniques for the estimation of unprotected left-turn saturation flows based on Korean drivers' data. As study intersections, signalized or unsignalized intersections on the 6, 4 and 2 lane streets are selected. the data for the saturation flow measurement and gap-acceptance behavior analysis are inputed in a notebook computer on the sites. The critical acceptance gaps of the 6, 4, and 2 lane streets are analyzed to be 6.0 secs, 4.6 secs, and 4.3 secs respectively. the average minimum headway of the left-turn vehicle was observed to be 2.6 secs. As the model to estimate unportected left-turn saturation flows, the drew model is recommended for 6 and 4 lane streets, and a graph is suggested for the 2-lane street. As the values of the parameters of the Drew model, the 2.6 secs of this study is recommended for the average minimum headway of the left-turn. But, the critical acceptance gap varies according to the approach speed of opposing traffic and driver population, it requires field survey to measure the gap of an intersection; however, the values of the gaps studied in this study may be used for the general intersections in urban area in Korean.

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The Design and Implementation of Anomaly Traffic Analysis System using Data Mining

  • Lee, Se-Yul;Cho, Sang-Yeop;Kim, Yong-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.4
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    • pp.316-321
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    • 2008
  • Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

Comparative Study on Internet Pricing : Flat-rate vs. Usage-based (초고속인터넷 요금제 유형에 대한 비교 검토 : 정액제, 종량제)

  • Song, Jae-Do
    • Korean Management Science Review
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    • v.26 no.1
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    • pp.21-35
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    • 2009
  • There is a controversy on Internet pricing, flat-rate vs. usage-based. This study gives a comparative analysis between flat-rate and two-part tariff which is realistic alternative of usage-based pricing. In a basic economic model, two-part tariff based on ISP's cost structure satisfies allocative efficiency and relatively expand the number of subscribers. But the characteristics of Internet service like consumers' uncertainty on cost, measurement cost of traffic and network externality induce increase of cost or decrease of marginal utility. The analysis shows that small impact of these can make flat-rate more efficient.

The Study on Cognition Difference of Environmental Sounds due to Subject' Classes (환경음에 대한 계층별 인식 차이에 관한 조사 연구)

  • Shin, Hoon;Baek, Geon-Jong;Song, Min-Jeong;Jang, Gil-Soo
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.1187-1190
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    • 2007
  • This study aims to induce acoustic environmental characteristics which could be used for soundscape design by carrying out factor analysis on sound source image and cognition analysis on subjects' responses on selective questions due to class differences. The results of this study are as follows ; Satisfaction rate differences on exterior acoustic environment due to sensitivity and residence year were revealed. After factor analysis of living sound sources' image, it is known that natural sound, traditional sound, socials traffic sound, rural sound, religious sound and the others are main factors. Social traffic sound is the most one that should be eliminated and traditional sound is selected as a most Korean-like sound. Natural sound is evaluated as the most one that should be preserved and the most retrospectively one.

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The Effectiveness of WBI(Web-Based Instruction) on the Knowledge and Attitude of Traffic Safety among Middle School Students (웹기반 교육이 중학생의 교통안전 지식과 태도에 미치는 효과 연구)

  • 장시원;이명선
    • Korean Journal of Health Education and Promotion
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    • v.21 no.3
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    • pp.101-116
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    • 2004
  • Korea has the highest traffic accident occurrence rate in the world. It means that we are forced to face a tremendous amount of economic loses and great cost of life. Even though this phenomenon consistently has arose as a public issue every year and many researchers have emphasized the importance of safety education as the fundamental solution, we are still trying to make a long-lasting and effective traffic safety education programs for children and adolescents. The purpose of this study was to test the effectiveness of web-based learning for traffic safety in Korea middle school. For this purpose, the instructive model was constructed based on the ASSURE model and a special web-site of education was developed on behalf of practical use of multi-media learning materials for the traffic safety. The research subject was represented by 259 students from second grade in 2 middle schools located in Seoul Korea. The traffic safety education program using web-site was preceded to the 136 students as a case group for 45 minutes total 3 times. Other 126 students are control group those who did not get with this program. The survey was conducted before and after the education. The results of this study were as follow: 1. The knowledge analysis from the comparison between before and after of the lesson showed case group and control group scored average at 11.25 points and 10.97 points. However, after they attended programs, case group scored 13.57 points and control group scored 10.85 points. The difference from the result of the case group was statistically significant(p<0.001). 2. The attitude analysis from the comparison between before and after of the lesson showed case group and control group scored averages at 29.59 points and 28.21 points. However, after they attended program, case group scored 37.23 points and control group scored 32.71 points. The difference from the result of the case group was statistically significant(p<0.05). 3. Regarding the domain analysis by means of web-based traffic safety education, only the case group had a statistically significant score in the case of knowledge 'safe utilization of bicycle' and 'The Characteristic of Automobile and Safer Mode of Walking for Pedestrian'(p<0.01, p< 0.001), and in the case of attitude 'safe walking and crossing' 'The Characteristic of Automobile and Safer Mode of Walking for Pedestrian'(p<0.01, p<0.001). 4. Web based instruction for traffic safety was effective in terms of improving students' knowledge and attitude for traffic safety.

Application of Deep Learning Method for Real-Time Traffic Analysis using UAV (UAV를 활용한 실시간 교통량 분석을 위한 딥러닝 기법의 적용)

  • Park, Honglyun;Byun, Sunghoon;Lee, Hansung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.4
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    • pp.353-361
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    • 2020
  • Due to the rapid urbanization, various traffic problems such as traffic jams during commute and regular traffic jams are occurring. In order to solve these traffic problems, it is necessary to quickly and accurately estimate and analyze traffic volume. ITS (Intelligent Transportation System) is a system that performs optimal traffic management by utilizing the latest ICT (Information and Communications Technology) technologies, and research has been conducted to analyze fast and accurate traffic volume through various techniques. In this study, we proposed a deep learning-based vehicle detection method using UAV (Unmanned Aerial Vehicle) video for real-time traffic analysis with high accuracy. The UAV was used to photograph orthogonal videos necessary for training and verification at intersections where various vehicles pass and trained vehicles by classifying them into sedan, truck, and bus. The experiment on UAV dataset was carried out using YOLOv3 (You Only Look Once V3), a deep learning-based object detection technique, and the experiments achieved the overall object detection rate of 90.21%, precision of 95.10% and the recall of 85.79%.