• 한국정보과학회논문지:정보통신
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• 제34권2호
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• pp.81-87
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• 2007

본 논문은 테스트 환경의 재구축에 의한 번거로움을 제거하고 손쉽게 테스트 환경을 재구성할 수 있는 리눅스 기반의 테스트 베드인 Network Traffic Control Test-bed(NTCT)를 구현하고 이를 활용한 실험 결과를 보인다. 본 논문에서 제시하는 NTCT는 원하는 사용자가 지정하는 네트워크 트래픽을 발생시키는 NS2 연동 트래픽 발생기와, 네트워크의 대역폭을 관리하여 실제 네트워크 상황과 유사한 환경을 유지시키는 트래픽 제어기, 그리고 성능 평가를 위한 실시간 네트워크 모니터로 구성되어 있다. 본 논문에서는 제시하는 NTCT를 이용하여 네트워크 성능을 평가하는 예제를 포함한다.

• ETRI Journal
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• 제46권3호
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• 전기학회논문지
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• 제62권5호
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• pp.688-695
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• 2013

Networked Control Systems(NCS) contain the structure which controllers, actuators and sensors are connected to communication network. And they have been adopted in large and complicated plant area due to the advantages of mitigating computational bottleneck and maintenance. Although this structure provides many benefits, it brings in problems of unpredictable communication delay, data loss and corruption. This phenomena have to be considered in designing NCSs since it affects on overall control system stability. This paper introduces network traffic test method for ethernet based NCSs to find out maximum network usage which guarantee stable control operation. Test results shows this methods can be adopted in various types of NCSs and contributes economical system design and effective system operation.

• 한국산학기술학회논문지
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• 제12권9호
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• pp.4125-4132
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• 2011

IPTV 멀티캐스팅 서비스에서 증가되는 네트워크 트래픽 로드에 따른 화상 품질 측정과 화상 품질 변화에 대한 연구는 IPTV 서비스에 대한 관심이 현실화됨에 따라 필요하게 되었다. 본 연구에서는 네트워크 트래픽 로드에 따른 화상 품질의 효과가 주어지는 네트워크 성능 요소의 최적의 값을 파악하기 위하여, 테스트 베드 네트워크를 통하여 테스트 하는 S/W를 개발하였다. 그리고 테스트 환경을 학교 네트워크로 확장하여 실제 IPTV 서비스 환경과 비슷한 학교 네트워크에서 네트워크 트래픽 로드 증가에 따른 IPTV 멀티캐스팅 서비스의 화상 품질 변화를 측정하고자 하였다.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.240-259
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• 2020

Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the detection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be significantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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• pp.63-67
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• 2009

In this paper we propose a QoS policy, which is based on both DSCP and SPQ, appropriate to TPS users on optical subscriber network. Then we experiment and evaluate QoS policy through the test bed which emulates real optical subscriber network. In order to perform effective and real experiment on test bed we make test traffic equivalent to 400 TPS users and give it to test bed. The experimental result shows that no packet loss in real time service traffic such as voice, IPTV occurs during more than 4 hours. We think that our proposed QoS policy is a proper method which guarantees the service quality of real time services on optical subscriber network.

• Journal of Communications and Networks
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• 제14권3호
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• pp.310-318
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• 2012

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.

• 디지털산업정보학회논문지
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• 제5권3호
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• pp.107-115
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• 2009

Traditionally, simulation method is used to test and evaluate the performance of communication protocol or functional elements for mobile communication service. In this paper, wireless network simulator is implemented using the C++ object-oriented programming language. This simulator can simulate wireless data services, like as ad-hoc networks, by considering the user's mobility. In this paper, the simulator includes network traffic model to reflect wireless data service and traffic source model to represent a user's mobility similar to real service environment and traffic characteristics can be reflected on the simulation, and also more accurate simulation results can be got through that. In addition, by using object-oriented techniques, new service feature or environment can be easily added or changed so that the developed mobile communication simulator can reflect the real service environment all the time. This simulator can be used in adjusting the characteristics of wireless data hosts following the mobility of the user, and also can be used in building new wireless ad-hoc network routing protocols.

• 한국통신학회논문지
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• 제33권8B호
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• pp.707-718
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• 2008

Traffic classification의 방법은 동적으로 변하는 application의 변화에 대처하기 위하여 페이로드나 port를 기반으로 하는 것에서 ML 알고리즘을 기반으로 하는 것으로 변하여 가고 있다. 그러나 현재의 ML 알고리즘을 이용한 traffic classification 연구는 offline 환경에 맞추어 진행되고 있다. 특히, 현재의 기존 연구들은 testing 방법으로 cross validation을 이용하여 traffic classification을 수행하고 있으며, traffic flow를 기반으로 classification 결과를 제시하고 있다. 본 논문에서는 testing방법으로 cross validation과 split validation을 이용했을 때, traffic classification의 정확도 결과를 비교한다. 또한 바이트를 기반으로 한 classification의 결과와 flow를 기반으로 한 classification의 결과를 비교해 본다. 본 논문에서는 J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, NaiveBayes와 같은 ML 알고리즘과 다양한 feature set을 이용하여 트래픽을 분류한다. 그리고 split validation을 이용한 traffic classification에 적합한 최적의 ML 알고리즘과 feature set을 제시한다.