• 제목/요약/키워드: Internet Traffic

검색결과 1,628건 처리시간 0.026초

An Ensemble Cascading Extremely Randomized Trees Framework for Short-Term Traffic Flow Prediction

  • Zhang, Fan;Bai, Jing;Li, Xiaoyu;Pei, Changxing;Havyarimana, Vincent
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.1975-1988
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    • 2019
  • Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.

WEB 기반 교통사고 분석 (Analysis System for Traffic Accident based on WEB)

  • 홍유식;한창평
    • 한국인터넷방송통신학회논문지
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    • 제22권6호
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    • pp.13-20
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    • 2022
  • 겨울철 도로에서 발생하는 안개 및 결빙구간 교통사고 사망률의 경우는 도로조건 및 기상조건이 매우 중요한 요소 이다. 본 논문에서는 교통사고 예측 데이터를 가정하고 교통사고 위험율을 에측 하는 모의실험을 수행하였다. 그뿐만 아니라, 본 논문에서는 교통사고를 줄이고 교통사고를 예방하기 위해서, 교통공단에서 제공하는 교통사고 사망자 데이터를 WEKA 데이터 마이닝 기법 및 TENSOR FLOW 공개 소스를 이용해서 요인 분석 및 교통사고 치사율 사망을 예측하였다. 추가적인 기능으로는 지도 표시 기능을 이용해서, 운전자가 WEB 기반에서, 안개 및 결빙구간 정보를 운전자에게 제공하는 모의실험 및 교통사고 사진을 실시간으로 전송하는 모의실험 결과를 설명하였다.

Adaptive Differentiated Integrated Routing Scheme for GMPLS-based Optical Internet

  • Wei, Wei;Zeng, Qingji;Ye, Tong;Lomone, David
    • Journal of Communications and Networks
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    • 제6권3호
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    • pp.269-279
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    • 2004
  • A new online multi-layer integrated routing (MLIR) scheme that combines IP (electrical) layer routing with WDM (optical) layer routing is investigated. It is a highly efficient and cost-effective routing scheme viable for the next generation integrated optical Internet. A new simplified weighted graph model for the integrated optical Internet consisted of optical routers with multi-granularity optical-electrical hybrid switching capability is firstly proposed. Then, based on the proposed graph model, we develop an online integrated routing scheme called differentiated weighted fair algorithm (DWFA) employing adaptive admission control (routing) strategies with the motivation of service/bandwidth differentiation, which can jointly solve multi-layer routing problem by simply applying the minimal weighted path computation algorithm. The major objective of DWFA is fourfold: 1) Quality of service (QoS) routing for traffic requests with various priorities; 2) blocking fairness for traffic requests with various bandwidth granularities; 3) adaptive routing according to the policy parameters from service provider; 4) lower computational complexity. Simulation results show that DWFA performs better than traditional overlay routing schemes such as optical-first-routing (OFR) and electrical-first-routing (EFR), in terms of traffic blocking ratio, traffic blocking fairness, average traffic logical hop counts, and global network resource utilization. It has been proved that the DWFA is a simple, comprehensive, and practical scheme of integrated routing in optical Internet for service providers.

P2P IPTV 서비스를 위한 세션 제어 메카니즘 (Session Control Mechanism for Peer-to-Peer IPTV Services)

  • 박승철
    • 정보처리학회논문지C
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    • 제15C권2호
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    • pp.87-92
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    • 2008
  • 본 논문은 P2P(Peer to Peer) IPTV(Internet Protocol Television) 서비스를 위한 세션 제어 모델을 제시하고, 제시된 모델에 근거한 IPTV 세션 제어 절차에 대해 논한다. 별도의 전용망에 의해 관련 트래픽이 처리되는 공중 IPTV(Public IPTV)와 달리 P2P IPTV 트래픽은 인터넷 접속 트래픽의 일부로 망에 의해 처리되어야 한다. 따라서 P2P IPTV 세션 제어는 IPTV를 구성하는 TPS(Triple Play Service) 트래픽을 기존 인터넷 트래픽과 분리하여 적절하게 제어할 수 있어야 하고, 분리된 TPS 트래픽을 차별화하여 처리하는 QoS(Quality of Service) 제어 기능을 포함해야 한다. 뿐만 아니라 P2P IPTV 세션 제어는 불특정 다수에 의한 비디오 전송을 효과적으로 지원하기 위한 적절한 멀티캐스트 제어 기능을 반드시 포함해야 한다. 본 논문의 P2P IPTV 세션 제어 모델은 상호 연동성(Inter-operability)이 보장되는 P2P IPTV 플랫폼의 조기 구축에 기여할 수 있도록 표준 SIP(Session Initiation Protocol), IGMP(Internet Group Management Protocol), 그리고 COPS(Common Open Policy Service) 프로토콜에 근거하여 설계되었다.

Performance Evaluation of Service-Aware Optical Transport System

  • Youn, Ji-Wook;Yu, Jea-Hoon;Yoo, Tae-Whan
    • ETRI Journal
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    • 제32권2호
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    • pp.241-247
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    • 2010
  • We propose and experimentally demonstrate a service-aware optical transport system. The proposed service-aware optical transport system makes a flow based on service type and priority of traffic. The generated flow is mapped to a corresponding sub-${\lambda}$ for transport over an optical network. Using sub-${\lambda}$ provided by the centralized control plane, we could effectively provide quality-of-service guaranteed Ethernet service and best-effort service simultaneously in a single link. The committed information rate (CIR) traffic and best-effort traffic are assigned to different sub-${\lambda}s$. The bandwidth of the CIR traffic is guaranteed without being affected by violation traffic because the bandwidth is managed per each sub-${\lambda}$. The failure detection time and restoration time from a link failure is measured to be about 60 ${\mu}s$ and 22 ms, respectively, in the ring network. The measured restoration time is much smaller than the 50 ms industry requirement for real-time services. The fast restoration time allows the proposed service-aware optical transport system to offer high availability and reliability which is a requirement for transport networks.

VC 머징이 가능한 ATM LSR의 구조 및 트래픽 엔지니어링 연구 (Study on Architecture of ATM LSR Supporting VC Merging and Traffic Engineering over It)

  • 정호연;서재영;백장현
    • 산업공학
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    • 제15권2호
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    • pp.152-158
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    • 2002
  • The explosive growth of the internet traffic in the last few years has imposed tremendous stress on today's routers, particularly in the core network. Recently, ATM LSRs(Label Switching Router) are potentially capable of providing the highest forwarding capacity in the backbone Internet network. VC merging is a mechanism in an ATM LSR that allows many IP routes to be mapped to the same VC label, and provides a scalable mapping method that can support thousands of destinations. VC merging requires reassembly buffers so that cells belonging to different packets intended for the same destination do not interleave with each other. In this study, we propose an architecture of the ATM LSR which supports VC merging. We propose traffic control scheme called APD(Active Packet Discard) algorithm so that predicts and controls the congestion of the Internet traffic effectively. We study the performance of this algorithm using simulation.

계층분석방법을 이용한 교차로망의 실시간 교통제어 (Realtime Traffic Control of Traffic Networks using Analytic Hierachy Process)

  • 진현수;홍유식
    • 한국인터넷방송통신학회논문지
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    • 제10권6호
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    • pp.47-53
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    • 2010
  • 본문은 단일 교차로의 주기시간을 결정하는 시간 간격을 계층분석방법(Analytic Hierachy Process)을 이용하여 도출하여 내었다. 주어진 불확실한 상황 가운데 결정적인 도출물을 얻기위해서는 비선형특성의 퍼지 적분이나 적응 계수를 사용하여 얻어내어야 하는데 이를 기반으로한 방법이 계층분석방법이다. 계층분석방법을 사용한 제어기와 고정시간 제어를 한 교통제어기와의 비교를 위하여 모의 실험을 통한 결과를 가지고서 비교 검토하였다.

A Low Complexity PTS Technique using Threshold for PAPR Reduction in OFDM Systems

  • Lim, Dai Hwan;Rhee, Byung Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권9호
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    • pp.2191-2201
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    • 2012
  • Traffic classification seeks to assign packet flows to an appropriate quality of service (QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

A Study of Data Interoperability System using DBaaS for Mobility Handicapped

  • Kwon, TaeWoo;Lee, Jong-Yong;Jung, Kye-Dong
    • International Journal of Internet, Broadcasting and Communication
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    • 제11권1호
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    • pp.97-102
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    • 2019
  • As the number of "Mobility Handicapped" increases, the incidence of "Mobility Handicapped" traffic accidents is also increasing. In order to reduce the incidence of traffic accidents in the "Mobility Handicapped", a service providing system for "Mobility Handicapped" is required. Since these services have different data formats, data heterogeneity occurs. Therefore, the system should resolve the data heterogeneity by mapping the format of the data. In this paper, we design DBaaS as a mobility handicapped system for data interoperability. This system provides a service to extend the flashing time of the traffic lights according to the condition of "Mobility Handicapped" on the occurrence of a fall or a crosswalk in a crosswalk where there is a risk of a traffic accident. These services can reduce the incidence of traffic accidents in "Mobility Handicapped".

Traffic-based reinforcement learning with neural network algorithm in fog computing environment

  • Jung, Tae-Won;Lee, Jong-Yong;Jung, Kye-Dong
    • International Journal of Internet, Broadcasting and Communication
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    • 제12권1호
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    • pp.144-150
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    • 2020
  • Reinforcement learning is a technology that can present successful and creative solutions in many areas. This reinforcement learning technology was used to deploy containers from cloud servers to fog servers to help them learn the maximization of rewards due to reduced traffic. Leveraging reinforcement learning is aimed at predicting traffic in the network and optimizing traffic-based fog computing network environment for cloud, fog and clients. The reinforcement learning system collects network traffic data from the fog server and IoT. Reinforcement learning neural networks, which use collected traffic data as input values, can consist of Long Short-Term Memory (LSTM) neural networks in network environments that support fog computing, to learn time series data and to predict optimized traffic. Description of the input and output values of the traffic-based reinforcement learning LSTM neural network, the composition of the node, the activation function and error function of the hidden layer, the overfitting method, and the optimization algorithm.