• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10c
• /
• pp.262-264
• /
• 1999

이동 통신 텔레트래픽 모델은 Traffic Source 모델과 Network Traffic 모델이라는 2개의 하부 모델로 구성된다. 본 논문에서는 기지국이 설치되어 있는 지역특성을 고려한 Network Traffic 모델을 제시한다. 기존의 Network Traffic 모델에서는 이동 통신 환경을 시뮬레이션 하기 위해 동일한 환경에 설치되어 있는 몇 개의 기지국을 가정하여 제시하고 있기 때문에, 기지국이 설치되어 있는 지역적 특성에 따라 다른 사용자 호 특성 및 설치 지역 특성이 전혀 반영되지 않고 있다. 도시를 상업, 주거, 준공업, 그리고 녹지지역으로 되어 있는 도시 계획 용도지역과 이외에 특이한 호 발생 패턴이 예측되는 역과 터널 주변이라는 6개의 지역으로 구분하고, 여기에 설치되어 있는 기지국으로부터 실제 데이터를 수집하였다. 이 자료를 이용하여 기지국이 설치되어 있는 지역에 따라 이동 통신 기지국의 요일별 통화량 분포를 분석하였으며, 이를 시뮬레이터에 적용하기 위한 평균값 및 분포값을 제시하였다. 이 파라메터들은 이동통신 시스템의 성능 및 신뢰성을 측정하기 위한 매우 중요한 값들이다.

• Journal of Korean Society of Transportation
• /
• v.14 no.4
• /
• pp.49-76
• /
• 1996

Until recently, the inductive loop detecters(ILD) have been used to collect a traffic information in a part of traffic manangment and control. The ILD is able to collect a various traffic data such as a occupancy time and non-occupancy time, traffic volume, etc. The occupancy time of these is very important information for traffic control algorithms, which is required a high accuracy. This accuracy may be improved by classifying a vehicle type with ILD. To classify a vehicle type based on a Analog Digital Converted data collect form ILD, this study used a typical and modifyed statistic method and General Learning Vector Quantization unsuperviser neural network model and a hybrid model of GLVQ and statistic method, As a result, the hybrid model of GLVQ neural network model is superior to the other methods.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.7 no.5
• /
• pp.178-185
• /
• 1999

Recently, Collision Warning System is developed to improve vehicle safety. This system chiefly uses radar. But the detected vehicle from radar must be decide whether it is the vehicle in the same lane of my vehicle or not. Therefore, Vision System is needed to detect traffic lane. As a preparative step, this study presents the development of algorithm to recognize traffic lane curve direction. That is, the Neural Network that can recognize traffic lane curve direction is constructed by using the information of short distance, middle distance, and decline of traffic lane. For this procedure, the relation between used information and traffic lane curve direction must be analyzed. As the result of application to sampled 2,000 frames, the rate of success is over 90%.t text here.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.11
• /
• pp.3098-3103
• /
• 2009

In this paper, self-similar characteristics over statistical approaches and real-time Ethernet network traffic measurements are estimated. It is also shown that the self-similar traffic reflects real Ethernet traffic chareacteristics by comparing TCP-MT source model which is exactly self-similar model to the traditional Poisson model.

• Journal of Communications and Networks
• /
• v.9 no.4
• /
• pp.408-418
• /
• 2007

In this paper, we address the question of dynamic network provisioning for time-varying traffic rates, with the objective of maximizing the system throughput. We assume that the network is capable of providing bandwidth guaranteed traffic tunnels for an ingress-egress pair and present an approach that (1) updates the tunnel routes and (2) adjusts the tunnel bandwidths, in an incremental, adaptive manner, based on the variations in the incoming traffic. First, we consider a simpler scenario where tunnel routes are fixed, and present an approach for adjusting the tunnel bandwidths dynamically. We show, through simulations, that our dynamic bandwidth assignment algorithm significantly outperforms the optimal static bandwidth provisioning policy, and yields a performance close to that of the optimal dynamic bandwidth provisioning policy. We also propose an adaptive route update algorithm, which can be used in conjunction with our dynamic bandwidth assignment policy, and leads to further improvement in the overall system performance.

• Journal of Korea Multimedia Society
• /
• v.11 no.12
• /
• pp.1706-1715
• /
• 2008

In a super-peer based P2P network, the network is clustered and each cluster is managed by a special peer, which is called a super-peer. A Super-peer has information of all the peers in its cluster. This type of clustered P2P model is known to have efficient information search and less traffic load than unclustered P2P model. In this paper, we compute the message traffic cost incurred by peers' query, join and update actions within a cluster as well as between the clusters. With these values, we estimate the optimal number of super-peers that minimizes the traffic cost for the various size of super-peer based P2P networks.

• ETRI Journal
• /
• v.41 no.5
• /
• pp.560-573
• /
• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.2
• /
• pp.67-72
• /
• 2021

MANET(Mobile Ad Hoc Network) is the structure in which a source node communicates with a destination node by establishing a route with neighbor nodes without using the existing wired or wireless network. Therefore, the routing protocol for MANET must correspond well to changes in the channel state of moving nodes, and should have simple operation, high reliability, and no routing loop. In this paper, the simulation was perform by using a traffic model with on/off two states provided by the NS-3 network simulator. Also, the duration of the ON state and the duration of the OFF state used the traffic where inter arrival time of data is irregular by generating random values with constant, exponential distribution, and Pareto distribution. The performance of the DSDV, OLSR, and AODV protocols was compare and analyzed using the generated traffic model.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.1
• /
• pp.85-91
• /
• 2013

Recently, the weight of high-quality multimedia contents is explosively growing out of the network total traffic. This steep increase of media contents to require huge traffic does not contribute to the generation of revenue streams and it leads to the situation of dumb pipe to trouble network providers into the big burden of investment on the network expansion. Accordingly, the transfer to the smart network to enable the effective delivery of large-scale media is imminently challenging issue to the network providers to seek the profitable business. The smart network revolves around the technologies to enhance end-to-end quality and fair usage with network resources and to optimize the traffic for the contents delivery over the concept of Content-Centric Network. In this paper, we propose an architecture and fundamental functions suitable for the smart network and suggest improved test results through the construction of an experimental network.

• Information and Communications Magazine
• /
• v.32 no.10
• /
• pp.31-40
• /
• 2015

This paper investigates several existing techniques to reduce high-availability seamless redundancy (HSR) traffic. HSR is a redundancy protocol for Ethernet networks that provides duplicated frames for separate physical paths with zero recovery time. This feature makes it very useful for real-time and mission-critical applications, such as military applications and substation automation systems. However, the major drawback of HSR is that it generates too much unnecessary redundant traffic in HSR networks. This drawback degrades network performance and may cause congestion and delay. Several HSR traffic reduction techniques have been proposed to reduce the redundant traffic in HSR networks, resulting in the improvement of network performance. In this paper, we provide an overview of these HSR traffic reduction techniques in the literature. The operational principles, advantages, and disadvantages of these techniques are investigated and summarized. We also provide a traffic performance comparison of these HSR traffic reduction techniques.