• Title/Summary/Keyword: Short Traffic

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Microcell Sectorization for Channel Management in a PCS Network by Tabu Search (광마이크로셀 이동통신망에서의 채널관리를 위한 동적 섹터결정)

  • Lee, Cha-Young;Yoon, Jung-Hoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.26 no.2
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    • pp.155-164
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    • 2000
  • Recently Fiber-optic Micro-cellular Wireless Network is considered to solve frequent handoffs and local traffic unbalance in microcellular systems. In this system, central station which is connected to several microcells by optical fiber manages the channels. We propose an efficient sectorization algorithm which dynamically clusters the microcells to minimize the blocked and handoff calls and to balance the traffic loads in each cell. The problem is formulated as an integer linear programming. The objective is to minimize the blocked and handoff calls. To solve this real time sectorization problem the Tabu Search is considered. In the tabu search intensification by Swap and Delete-then-Add (DTA) moves is implemented by short-term memory embodied by two tabu lists. Diversification is considered to investigate proper microcells to change their sectors. Computational results show that the proposed algorithm is highly effective. The solution is almost near the optimal solution and the computation time of the search is considerably reduced compared to the optimal procedure.

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A Study on the Railway Traffic Conflict Resolution Problem using GA (유전자 알고리즘을 이용한 열차경합 해소문제에 관한 연구)

  • Oh, Seog-Moon;Kim, Young-Hoon;Kim, Sung-Ho;Kim, Dong-Hee;Hong, Soon-Heum
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2736-2739
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    • 2002
  • This paper is a study on the railway traffic conflict resolution(RTCR) using genetic algorithm(GA). Using GA, many complicated problems can be expressed in the easy way, and good solutions can be found in a reasonably short time. Due to the above merits, we focus to GA first of all. We express the sample RTCR problem and algorithm of Korean railroad using GA. From the Mark Ho's[2,3] results, we introduce a chromosome scheme in addition.

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A Simulation Study on ITS/DSRC Communication Networks for Metropolitan Seoul area. (지능형 교통 시스템을 위한 수도권 지역에 대한 DSRC 통신망 시뮬레이션 연구)

  • 이희상;김윤배;박진수;이성룡;최경일
    • Journal of the Korea Society for Simulation
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    • v.9 no.2
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    • pp.103-118
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    • 2000
  • ITS(Intelligent Transportation System) is an advanced system which can effectively handle the current transportation problems. DSRC(Dedicated Short Range Communication) is considered as a promising technology since it has the capability of two-way communication and can serves to implement various ITS services. In this paper, we study DSRC based ITS telecommunication traffic analysis and suggest an architecture and network design of telecommunication network for DSRC services. We also perform a simulation study to validate the proposed network architecture and design for Metropolitan Seoul Area with various network alternatives. In this simulation, we use actual traffic data and road characteristics from Seoul area and use our DSRC service configuration.

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Train Scheduling and Rescheduling In Pakistan

  • Abid, Malik Muneeb;Khan, Muhammad Babar
    • International Journal of Railway
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    • v.6 no.1
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    • pp.7-12
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    • 2013
  • This paper provides an overview of Pakistan Railways scheduling and rescheduling. First of all, Pakistan Railways is introduced with its brief history and importance in this country. Assets of this network with passengers and freight using this are given. Current hope less situation is leading to privatization of this system as well as promoting short distance traveler to use road and Government efforts to retain is also presented. Train scheduling in Pakistan is being done manually, based on manual time distance graph preparation and resolution of conflicts based on manager's experience and ability. In Real-time management of this traffic Lahore head office is connected with six control stations in the Pakistan, decision for resolution of any disturbance is coordinated among them. It is recommended that computer aided tools must be developed for this system to help traffic managers and it is needed to invest on the segments to increase their speed limits which might attract passengers to use this mode of transportation with high priority.

Prediction of Highway Traffic Noise (고속도로 교통소음 예측)

  • 조대승;김진형;최태묵;오정한;장태순
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11b
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    • pp.1280-1286
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    • 2001
  • This paper presents some advanced and supplemental methods to enhance the accuracy in case of calculating geometric divergence attenuation, attenuation by multiple screening structures, ground attenuation at unflat surfaces of sound during propagation outdoors by the methods specified in ISO 9613-2. Moreover, a calculation method for considering short-term wind effect, specified in ASJ Model-1998, is also introduced. To verify the accuracy of adopted methods, we have carried out highway traffic noise prediction and measurement at the twelve locations appearing representative road shapes and structures, such as flat, retained cut, elevated, barrier-constructed roads. From the results, we have confirmed the predicted results show good correspondence with the measured at direct, diffracted and reflected sound fields within 30m from the center of near side lane.

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Optimization of Cyber-Attack Detection Using the Deep Learning Network

  • Duong, Lai Van
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.159-168
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    • 2021
  • Detecting cyber-attacks using machine learning or deep learning is being studied and applied widely in network intrusion detection systems. We noticed that the application of deep learning algorithms yielded many good results. However, because each deep learning model has different architecture and characteristics with certain advantages and disadvantages, so those deep learning models are only suitable for specific datasets or features. In this paper, in order to optimize the process of detecting cyber-attacks, we propose the idea of building a new deep learning network model based on the association and combination of individual deep learning models. In particular, based on the architecture of 2 deep learning models: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), we combine them into a combined deep learning network for detecting cyber-attacks based on network traffic. The experimental results in Section IV.D have demonstrated that our proposal using the CNN-LSTM deep learning model for detecting cyber-attacks based on network traffic is completely correct because the results of this model are much better than some individual deep learning models on all measures.

Low Latency Traffic Transmission Technique Utilizing Interframe Space Communication (인터프레임 스페이스 통신을 활용한 저지연 트래픽 전송 기법)

  • Sun-Jin Lee;Il-Gu Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2024.05a
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    • pp.133-136
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    • 2024
  • 전 산업에서 초고속 저지연 데이터 서비스 수요가 증가하면서 저지연 트래픽 (low latency traffic, LLT) 처리 중요성이 커지고 있다. 기존 연구들은 LLT 에 우선순위를 부여하여 먼저 처리하는 프리 엠프션 기법을 제안했으나 제어 오버헤드가 증가하거나 non-LLT 트래픽 성능을 열화하는 문제를 해결할 수 없었다. 본 논문에서는 이러한 문제를 해결하기 위해 종래에 사용하지 않았던 짧은 인터프레임 스페이스 (Short Interframe Space, SIFS)를 LLT 에 활용하는 새로운 전송 기법을 제안한다. 본 논문에서는 수치 분석을 통해 제안하는 인터프레임 스페이스 통신 (Interframe Space Communication, ISC)이 종래의 전송 방법 대비 스루풋을 평균 50% 개선하고 지연도를 98% 개선할 수 있음을 보였다.

Building a TDM Impact Analysis System for the Introduction of Short-term Congestion Management Program in Seoul (교통수요관리 방안의 단기적 효과 분석모형의 구축)

  • 황기연;김익기;엄진기
    • Journal of Korean Society of Transportation
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    • v.17 no.1
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    • pp.173-185
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    • 1999
  • The purpose of this study is to develope a forecasting model to implement short-term Congestion Management Program (CMP) based on TDM strategies in Seoul. The CMP is composed of three elements: 1) setting a goal of short-term traffic management. 2) developing a model to forecast the impacts of TDM alternatives, and 3) finding TDM measures to achieve the goal To Predict the impacts of TDM alternatives, a model called SECOMM (SEoul COngestion Management Model) is developed. The model assumes that trip generation and distribution are not changing in a short term, and that only mode split and traffic assignment are affected by TDM. The model includes the parameter values calibrated by a discrete mode choice model, and roadway and transit networks with 1,020 zones. As a TDM measure implement, it affects mode choice behavior first and then the speeds of roadway network. The chanced speed again affects the mode choice behavior and the roadway speeds. These steps continue until the network is equilibrated. The study recommends that CMP be introduced in Seoul, and that road way conditions be monitored regularly to secure the prediction accuracy of SECOMM. Also, TDM should be the major Policy tools in removing short-term congestion problems in a big city.

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A Study of Ramp Metering System Using Off-ramp Exit Percentage (램프 진출교통량 비율을 이용한 램프미터링 운영방안 연구)

  • Kang, Woojin;Kim, Youngchan;Lee, Minhyoung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.6
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    • pp.102-115
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    • 2016
  • In this study, a scheme of ramp metering that uses Off-ramp Exit Percentage instead of the O/D table required for systems of integrated control of ramps at the target freeway segment is presented. The segment from Gyeyang IC to Jangsu IC on the Seoul Outer Ring Expressway was selected for the study because the segment frequently shows large volume of traffic on the short distance between the two ICs requiring an integrated on-ramp control by taking the traffic situation on an entire expressway into account despite an unavailability of O/D data. Thus the information of Off-ramp Exit Percentage at each IC were collected instead of securing the O/D table through actual survey, and the congestion on the segment was analyzed to identify the validity of the use of off-ramp traffic instead of O/D data. In addition, the scheme of ramp metering that exploits the off-ramp traffic information was prepared through simulations conducted in a way supporting the traffic control for respective access roads thereof by taking traffic situations and queues on each ramp into account. The results obtained from the simulation analyses revealed an improved level of travel speed and traffic volume on the main line and validated the use of off-ramp traffic instead of the O/D table for the ramp metering.

Methodology for Estimating Highway Traffic Performance Based on Origin/Destination Traffic Volume (기종점통행량(O/D) 기반의 고속도로 통행실적 산정 방법론 연구)

  • Howon Lee;Jungyeol Hong;Yoonhyuk Choi
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.2
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    • pp.119-131
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    • 2024
  • Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.