• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.1105-1108
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• 2003

통신망을 효율적으로 설계하고 운영하기 위하여 통신망에 대한 구체적인 시뮬레이션이 필요하며 이에 관한 연구가 현재 활발히 이루어지고 있다. 본 논문에서는 통신망 성능 분석을 위한 시뮬레이션 시 필요한 트래픽 생성기의 설계를 위해 실제 트래픽 자료를 수집, 분석하여 HTTP 요구 수준에서 통계적 방법을 통해 확률 분포로 모델링하였다. 기존 연구에서는 응답 크기에 대하여 파레토 분포만을 사용하여 그 특성을 모델링하였지만, 본 연구에서는 지수 분포와 파레토 분포의 혼합으로 모델링할 수 있음을 확인하였다. 또한 응답 크기의 특성은 서버 내 파일 크기의 특성을 그대로 반영하는 것이 아니라 사용자의 웹 문서 요청의 편중화 현상에 영향을 받아 그 특성이 달라질 수 있다는 것을 분석을 통해 확인하였다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2117-2126
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• 1998

본 논문에서는 내부 스피드업을 갖는 배처-베니안 망 스위칭 구조에 관한 분석적 모델을 제안하고 성능분석 결과를 제시한다. 또한, 이 모델에서 다양한 큐잉 기법들이 다른 트래픽 분포하에서 비교된다. 높은 스위칭 스피드업을 갖는 배처-베니안 망에서, 입력 및 출력 트래픽 분포에 영향을 받는 버퍼링 기법의 성능은 전체 스위칭 망의 성능에 커다란 영향을 주게 된다. 따라서 본 고에서는 제안된 모델링 기법을 사용하여 베니안 망들의 큐잉 기법을 분석하며, 큐잉 기법을 통하여 큐잉 성능과 입력 트래픽의 관계를 규명한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1069-1076
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• 2016

Recent development in visual sensor technologies has encouraged various researches on adding imaging capabilities to sensor networks. Video data are bigger than other sensor data, so it is essential to manage the amount of image data efficiently. In this paper, a new method of video traffic estimation is proposed for efficient traffic management of visual sensor networks. In the proposed method, a first order autoregressive model is used for modeling the traffic with the consideration of the characteristics of video traffics acquired from visual sensors, and a Kalman filter algorithm is used to estimate the amount of video traffics. The proposed method is computationally simple, so it is proper to be applied to sensor nodes. It is shown by experimental results that the proposed method is simple but estimate the video traffics exactly by less than 1% of the average.

• Journal of Internet Computing and Services
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• v.5 no.1
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• pp.41-49
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• 2004

Analytical performance evaluation is crucial for justifying the merit of the design of Multistage Interconnection Networks(MINs) in different operational conditions. While several analytical models have been proposed for the performance evaluation of MlNs, they are mainly for uniform traffics. Even the models for nonuniform traffics have various shortcomings. In this paper, an accurate model for the performance evaluation of multi buffered banyan-type MIN's under nonuniform traffic condition is obtained. The accuracy of proposed models are conformed by comparing with the results from simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2B
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• pp.279-288
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• 2004

Rapidly emerging P2P(Peer to Peer) applications generate very bursty traffic, which gives a lot of burden to network, and the amount of such traffic is increasing rapidly. Thus it is becoming more important to understand the characteristics of such traffic and reflect it when we design and analyze the network. To do that we measured the traffic in a campus network and present flow statistics and traffic models of the measured traffic, and compare them with those of the web traffic. The results indicate that P2P traffic is much burstier than web traffic and as a result it negatively affects network performance. We modeled P2P traffic using self-similar traffic model to predict packet delay and loss occurred in network which are very important to evaluate network performance. We also predict queue length distribution and loss probability in SSQ(Single Sewer Queue). To assess accuracy of traffic model, we compare the SSQ statistics of traffic models with that of the traffic trace. The results show that self-similar traffic models we use can predict P2P traffic behavior in network precisely. It is expected that the traffic models we derived can be used when we design network capacity and predict network performance and QoS of the P2P applications.

• Proceedings of the KAIS Fall Conference
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• 2007.11a
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• pp.174-177
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• 2007

이동통신망의 규모나 서비스 등이 기하급수적으로 증가하기 때문에 데이터 트래픽에 대한 정확한 특성분석은 매우 어렵지만, 트래픽 특성분석이 망 설계나 운용에 상당한 영향을 미친다는 점을 고려하면, 데이터 트래픽 모델링에 대한 연구는 가장 기본적으로 이루어져야 할 사항이라 할 수 있다. 따라서 본 논문에서는 데이터 트래픽에 대한 특성을 분석하기 위해 cdma2000 시스템의 국제적인 표준화 단체인 3GPP2에서 언급한 HTTP, FTP, WAP, Near Real Time Video 트래픽에 대한 트래픽 특성을 분석하여 자기 유사성(Self-similarity)을 가짐을 입증하였다.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.635-648
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• 2006

As the advances of Internet infra structure and the support of console and mobile for network games, the industry of online game has been growing rapidly, and the online game traffic in the Internet has been increasing steadily. For design and simulation of game network, the analysis of online game traffic have to be preceded. Therefore a number of papers have been proposed for the purpose of analyzing the traffic data of network games and providing the models. We make and use GameNet Analyzer as a dedicated tool for game traffic measurement and analysis in this paper. We measure the traffic of FPS Quake 3, RTS Starcraft and MMORPG World of Warcraft (WoW), and analyze the packet size, packet IAT(inter-arrival time), data rate and packet rate according to the number of players and in-game behaviors. We also present the traffic models using measured traffic data. These analysis and models of game traffic can be used for effective network simulation, performance evaluation of game network and the design of online games.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.416-420
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• 2002

Traditional queueing analyses are very useful for designing a network's capacity and predicting there performances, however most of the predicted results from the queueing analyses are quite different from the realistic measured performance. And recent empirical studies on LAN, WAN and VBR traffic characteristics have indicated that the models used in the traditional Poisson assumption can't properly predict the real traffic properties due to under estimation of the long range dependence of network traffic and self-similarity In this parer self-similar characteristics over statistical approaches and real time network traffic measurements are estimated It is also shown that the self- similar traffic reflects network traffic characteristics by comparing source model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.104-107
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• 2002

Traditional queueing analyses are very useful for designing a network's capacity and predicting there performances, however most of the predicted results from the queueing analyses are quite different from the realistic measured performance. And recent empirical studies on LAN, WAN and VBR traffic characteristics have indicated that the models used in the traditional Poisson assumption can't properly predict the real traffic properties due to under estimation of the long range dependence of network traffic and self-similarity. In this paper self-similar characteristics over statistical approaches and real time network traffic measurements are estimated. It is also shown that the self-similar traffic reflects network traffic characteristics by comparing source model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.667-680
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• 2008

In this work, we present the results of our empirical study on 802.11 wireless LAN network traffic. We collect the packet trace from existing campus wireless LAN infra-structure. We analyzed four different data sets: aggregate traffic, upstream traffic, downstream traffic, tcp only packet trace from aggregate traffic. We analyze the time series aspect of underlying traffic (byte count process and packet count process), marginal distribution of time series, and packet size distribution. We found that in all four data sets there exist long-range dependent property in byte count and packet count process. Inter-arrival distribution is well fitted with Pareto distribution. Upstream traffic, i.e. from the user to Internet, exhibits significant difference in its packet size distribution from the rests. Average packet size of upstream traffic is 151.7 byte while average packet size of the rest of the data sets are all greater than 260 bytes. Packets with full data payloads constitutes 3% and 10% in upstream traffic and the downstream traffic, respectively. Despite the significant difference in packet size distribution, all four data sets have similar Hurst values. The Hurst alone does not properly explain the stochastic characteristics of the underlying traffic. We model the underlying traffic using fractional-ARIMA (FARIMA) and fractional Gaussian Noise (FGN). While the fractional Gaussian Noise based method is computationally more efficient, FARIMA exhibits superior performance in accurately modeling the underlying traffic.