• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.574-581
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• 2002

Traditional queueing analyses are very useful for designing a network's capacity and predicting their 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 characteristic have indicated that the models used in the traditional Poisson assumption cannot properly predict the real traffic properties due to underestimation of the long-range dependence of network traffics and self-similar properties. In this paper, It is also shown that the self-similar traffic reflects real Ethernet traffic characteristics by comparing Pareto-like ON/OFF source model which is exactly self-similar model to the traditional Poisson model. It is also performed optimization design and performance analysis of ATM network using Internet traffic characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.267-271
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics. Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real network Traffic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.296-300
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• 2000

In previous papers, it proved relevant to using together with EFCI and ER switch for effective ABR traffic managements. It also applied to EFCI and ER switch algorithm, that consider ABR traffic as poisson pattern. However, in recently network environment, it has been proved about traffic pattern, that is similar to self-similar pattern than poisson pattern. In this paper, we will compare previous poisson pattern with self-similar pattern under ATM network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4B
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• pp.162-169
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• 2005

Network traffic measurements show that the data traffic on packet switched networks has the self-similar features which is different from the traditional traffic models such as Poisson distribution or Markovian process model. Most of the call admission control researches have been done on the performance analysis of a single network switch. It is necessary to consider the performance analysis of the proposed admission control scheme under interconnected switch environment because the data traffic transmits through switches in networks. From the simulation results, it is shown that the call admission control scheme may not operate properly on the interconnected switch even though the scheme works well on a single switch. In this parer, we analyze the cell loss probability, utilization and self-similarity of output ports of the interconnected networks switch by using shared buffer memory management schemes and propose the new call admission control scheme considering the interconnected network switches under self-similar traffic environments.

• 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 KIPS Transactions:PartC
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• v.10C no.1
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• pp.51-60
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• 2003

One of the most important matters in designing network and realizing service, is to grip on the traffic characteristics. Conventional traffic prediction and analysis used the models which based on the Poisson or Markovian. Recently, experimental research on the LAN, WAN and VBR traffic properties have been pointed rut that they weren't able to display actual real traffic specificities because the models based on the Poisson assumption had been underestimated the long range dependency of network traffic and self-similar peculiarities, it has been lately presented that the new approach method using self-similarity characteristics as similar as the real traffic models. Therefore, in this paper, we generated self-similar data traffic like real traffic as background load. On the existing ABR congestion control algorithm, we analyzed by classify into ACR, buffer utilization. cell drop rate, transmission throughput with the representative EFCI, ERICA, EPRCA and NIST twitch algorithm to show the efficient reaction about the burst traffic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.263-267
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• The KIPS Transactions:PartC
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• v.8C no.3
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• pp.327-334
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• 2001

네트워크를 설계하고 서비스를 구현하는데 있어서 중요한 변수중의 하나는 트래픽의 특성을 파악하는 것이다. 기존의 트래픽 예측과 분석은 포아송(Poisson) 또는 마코비안(Markovian)을 기본으로 하는 모델을 사용하였다. LAN, WAN 및 VBR(Variable Bit Rate) 트래픽 특성에 관한 최근의 실험적 연구들은 기존의 포아송 가정에 의한 모델들이 네트워크 트래픽의 장기간 의존성 및 self-similar 특성들을 과소평가 함으로써 실제 트래픽의 특성을 제대로 나타낼 수 없다는 것을 지적해 왔다. 따라서 최근 실제 트래픽 모델과 유사한 모델로서 self-similarity 특성을 이용한 접근법이 대두되고 있다. 본 논문에서는 self-similarity 트래픽의 정의에 대해서 논한다. 그리고 실제 트래픽을 수집하고, 인위적으로 self-similarity한 트래픽과 포아송 모델을 적용시킨 트래픽을 발생시켜 비교한 다음 ATM 스위치의 큐(Queue)에 적용하였다. 본 논문에서는 ATM 스위치의 큐에 self-similarity 트래픽을 적용했을 경우 low bound상에서 버퍼 오버플로우 확률 및 셀 손실 확률에 대해 평가하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.344-355
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• 2008

In this paper, we are dealing with the problems of performance evaluation of Differentiated Services(DiffServ) networks. For successful performance evaluation, the ability to accurately represent "real" traffic on the network by suitable traffic models is an essential ingredient. Many research results on the nature of real traffic measurements demonstrated LRD(long-range dependence) property for the Internet traffic including Web, TELNET, and P2P traffic. The LRD can be effectively represented by self-similarity. In this paper, we design and implement self-similar traffic generator using the aggregated On/Off source model, based on the analysis of the On-Off source model, FFT-FGN(Fast Fourier Transform-Fractional Gaussian Noise) model, and RMD(Random Midpoint Displacement) model. We confirmed the self-similarity of our generated traffic by checking the packet inter-arrival time of TCPdump data. Further we applied the implemented traffic generator to the performance evaluation of DiffServ networks and observed the effect of performance to the a value of the On/Off model, and performance of EF/BE class traffic by CBQ.