• Title/Summary/Keyword: Traffic Flows

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Study on the Measurement-Based Packet Loss Rates Assuring for End-to-End Delay-Constrained Traffic Flow (지연 제한 트래픽 흐름에 대한 측정 기반 패킷 손실률 보장에 관한 연구)

  • Kim, Taejoon
    • Journal of Korea Multimedia Society
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    • v.20 no.7
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    • pp.1030-1037
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    • 2017
  • Traffic flows of real-time multimedia services such as Internet phone and IPTV are bounded on the end-to-end delay. Packets violating their delay limits will be dropped at a router because of not useful anymore. Service providers promise the quality of their providing services in terms of SLA(Service Level Agreement), and they, especially, have to guarantee the packet loss rates listed in the SLA. This paper is about a method to guarantee the required packet loss rate of each traffic flow keeping the high network resource utilization as well. In details, it assures the required loss rate by adjusting adaptively the timestamps of packets of the flow according to the difference between the required and measured loss rates in the lossy Weighted Fair Queuing(WFQ) scheduler. The proposed method is expected to be highly applicable because of assuring the packet loss rates regardless of the fluctuations of offered traffic load in terms of quality of services and statistical characteristics.

Prediction Model with a Logistic Regression of Sequencing Two Arrival Flows (합류하는 두 항공기간 도착순서 결정에 대한 로지스틱회귀 예측 모형)

  • Jung, Soyeon;Lee, Keumjin
    • 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.

Implementation of outgoing packet processor for ATM based MPLS LER System

  • Park, Wan-Ki;Kwak, Dong-Yong;Kim, Dae-Yong
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1851-1854
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    • 2002
  • The Internet with conventional routing scheme cannot meet user demands driven from drastic growth in the Internet user and various service and traffic type. MPLS(Multi Protocol Label Switching) was introduced to the Internet fur solution to resolve this problem. MPLS is a paradigm to integrate higher layer’s software routing functions including layer-3 routing with layer-2 switching. But, the exponential growth of Internet traffic brings out of label space. One scalable solution to cope with this problem is to introduce flow merge technique, i. e. a group of flows is forwarded using the same label. Specially, IETF(Internet Engineering Task Force) recommends that ATM based MPLS system may include VC merge function, so it is scalable to increase of internet traffic. We implemented the MPLS LER system that includes the look-up and forwarding function in incoming path and VC merging function and limited traffic management function in outgoing path. This paper describes the implementation of the LER’s outgoing parts.

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A Study on Traffic Control Blocks for QOS Services in the $MP\lambdaS$ Networks ($MP\lambdaS$ 네트워크의 QOS 서비스를 위한 트래픽 제어 블록에 관한 연구)

  • Gi-Ho Joo
    • The Journal of Engineering Research
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    • v.6 no.2
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    • pp.131-140
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    • 2004
  • With a rapid development of DWDM and photonic switching, $MP{\lambda}S$ network can realize DiffServ like QOS services using optical wavelength mapping to the traffic flows. In this study, we describe the service connection architecture for providing QOS service between $MP{\lambda}S$ network and network users. We also describe a methodology, which is similar to DiffServ mechanism, to build traffic conditioning blocks that can be used to provide the negotiated QOS services using traffic control components defined by IETF

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Origin and destination matrix estimation using Toll Collecting System and AADT data (관측 TCS data 및 AADT 교통량을 이용한 기종점 교통량 보정에 관한 연구)

  • 이승재;장현호;김종형;변상철;이헌주;최도혁
    • Journal of Korean Society of Transportation
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    • v.19 no.5
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    • pp.49-59
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    • 2001
  • In the transportation planning process, origin and destination(O-D) trip matrix is one of the most important elements. There have been developments and applications of the methodology to adjust old matrices using link traffic counts. Commonly, the accuracy of an adjusted O-D matrix depends very much on the reliability of the input data such as the numbers and locations of traffic counting points in the road network. In the real application of the methodology, decisions on the numbers and locations of traffic counting points are one of the difficult problems, because usually as networks become bigger, the numbers of traffic counting points are required more. Therefore, this paper investigates these issues as an experiment using a nationwide network in Korea. We have compared and contrasted the set of link flows assigned by the old and the adjusted O-D matrices with the set of observed link flows. It has been analyzed by increasing the number of the traffic counting points on the experimental road network. As a result of these analyses, we can see an optimal set of the number of counting links through statistical analysis, which are approximately ten percentages of the total link numbers. In addition, the results show that the discrepancies between the old and the adjusted matrices in terms of the trip length frequency distributions and the assigned and the counted link flows are minimized using the optimal set of the counted links.

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A Statistical Fitness Test of Newell's 3-detector Simplification Method for Unexpected Incident Detection in the Expressway Traffic Flow (고속도로 돌발상황 검지를 위한 삼연속검지기 단순화 해법의 통계적 적합성 검정)

  • OH, Chang-Seok;RHO, Jeong Hyun;PARK, Young Wook
    • Journal of Korean Society of Transportation
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    • v.34 no.2
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    • pp.146-157
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    • 2016
  • The objective of this study is to actualize a statistical model of the 3-detector simplification model, which was proposed to detect outbreak situations by Daganzo in 1997 and to verify the statistical appropriacy thereof. This study presents the calculation process of the 3-detector simplification model and realizes the process using a statistics program. Firstly, the model was applied using data on detector of the main highways on which there is no entrances or exits. Moreover, in order to statistically verify the 3-detector simplification model, accumulative traffics for 30 seconds period, which reflects the dynamic changes of traffics due to shock wave, were estimated for outbreak traffics and steady flow, and the error of acquired data was statistically compared with that of the actual accumulative traffics. As a result, the error ratio between steady and incident cumulative flows has reached its maximum after 2-3 hours from an accident. Moreover, the incident traffic flows by accidents and the stade flows are heterogeneous in terms of their dispersion and means.

The Study on Development of Intergrated Ship's Traffic Flow Simulation Model based on Collision Avoidance Function (피항판단평가함수를 고려한 선박교통흐름 통합프로그램의 구축에 관한 연구)

  • Seong, Yu-Chang
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.16 no.1
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    • pp.101-106
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    • 2010
  • Marine transportation system plays an important role in maintaining and promoting economic activities among countries. The accurate understanding of marine traffic flows are necessary for the further advancement of marine transportation system. While many existing researches on marine traffic have been conducted mainly on the basis of statistical analysis using traffic data, ship's traffic flow simulation model was developed in this study. A collision avoidance algorithm was conducted with categorizing of traffic factors such as ship's length and speed. The developed model was also verified by a simulation process.

The analysis of two-lane highway traffic flows in case of the neighborhood electric vehicle involved (2차로도로에서 저속전기자동차 혼입에 따른 교통류 특성분석)

  • Jang, Keun-Woo;Jung, Sung-Hwa;Cho, Ju-Myung;Jung, Phil-Hyun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.10 no.5
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    • pp.124-134
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    • 2011
  • To make popular the NEV(Neighborhood Electric Vehicles) uses, it must be considered the supply of infrastructure and the political decision for NEV. However, the guidelines of infrastructure for NEV are not prepared. The guidelines of infrastructure for NEV should be performed in many research and case. The purpose of this study is to reveal the influence of NEV on the two-lane highway traffic flows by TWOPAS simulation model. The main items to check the influence are Average Travel speed, Percent Time Spent Following and Total Delay. The scenario were setup by traffic volume. And the NEV percentages are changed from 1% ~ 30%. The scenario 1 which traffic volume are 650veh/h and the scenario 4 which traffic volume are 2,600veh/h are less influenced by NEV, compare to scenario 2, scenario 3. Because the scenario 1 is more free to make passing other cars and Scenario 4 is fully saturated with existing traffic volumes. The urban two-lane highway which has much traffic volume and the rural two-lane highway which has little traffic volume has affinity for NEV than the other two-lane highway.

Traffic Classification Using Machine Learning Algorithms in Practical Network Monitoring Environments (실제 네트워크 모니터링 환경에서의 ML 알고리즘을 이용한 트래픽 분류)

  • Jung, Kwang-Bon;Choi, Mi-Jung;Kim, Myung-Sup;Won, Young-J.;Hong, James W.
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.8B
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    • pp.707-718
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    • 2008
  • The methodology of classifying traffics is changing from payload based or port based to machine learning based in order to overcome the dynamic changes of application's characteristics. However, current state of traffic classification using machine learning (ML) algorithms is ongoing under the offline environment. Specifically, most of the current works provide results of traffic classification using cross validation as a test method. Also, they show classification results based on traffic flows. However, these traffic classification results are not useful for practical environments of the network traffic monitoring. This paper compares the classification results using cross validation with those of using split validation as the test method. Also, this paper compares the classification results based on flow to those based on bytes. We classify network traffics by using various feature sets and machine learning algorithms such as J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, and NaiveBayes. In this paper, we find the best feature sets and the best ML algorithm for classifying traffics using the split validation.

Real-time Classification of Internet Application Traffic using a Hierarchical Multi-class SVM

  • Yu, Jae-Hak;Lee, Han-Sung;Im, Young-Hee;Kim, Myung-Sup;Park, Dai-Hee
    • 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.