• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1317-1320
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• 2002

네트워크에서 실시간으로 통신 트래픽의 변화량을 감시하고 시계열 분석을 이용해 변화량의 추이를 모형화한다. 트래픽의 변화량을 모형화하게 되면 트래픽에 대한 예측이 가능하게 되므로 트래픽 예측을 이용하여 성능관리를 수행할 수 있다. 본 연구에서는 실시간 트래픽을 이용한 성능관리 시스템에 대해 다룬다. 기존의 성능관리 시스템은 SNMP를 이용한 MIB-II 정보를 바탕으로 하는 분석 방법으로 이는 누적 데이터를 기본으로 하는 관리 방법으로 이상 징후의 판단이 즉각적이지 않았고 또한 모니터링을 수행하기 위해서는 통신 트래픽의 증가를 가져왔다. 대부분의 성능관리 시스템은 단순히 망에서의 트래픽이나 에러율 등을 관리자에게 보고하는 데 그치고 있어 능동적인 성능관리가 이루어지지 않는다. 따라서, 본 논문에서는 실시간 트래픽 감시를 위해 네트워크에 들어오거나 나가는 트래픽의 양을 측정하여 분석하고, 이 정보를 바탕으로 특정 시점 이후의 트래픽 추이를 모형화하여 미래의 트래픽 양을 예측하고, 예측된 정보를 바탕으로 하는 성능관리 시스템에 대해 연구한다. 예측 알고리즘으로는 시계열 분석을 통해 시계열 자료의 예측을 가능하게 하는 알고리즘으로 설계한다. 이 성능관리시스템을 바탕으로 망 관리자가 전체 통신 네트워크의 부하 상태를 예측하여 신속하게 대응을 할 수 있다.

• The KIPS Transactions:PartC
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• v.18C no.1
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• pp.31-44
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• 2011

The applicability of network-based computing depends on the availability of the underlying network bandwidth. Such a growing gap between the capacity of the backbone network and the end users' needs results in a serious bottleneck of the access network in between. As a result, ISP incurs disadvantages in their business. If this situation is known to ISP in advance, or if ISP is able to predict traffic volume end-to-end link high-load zone, ISP and end users would be able to decrease the gap for ISP service quality. In this paper, simulation tools, such as ACE, ADM, and Flow Analysis, were used to be able to perceive traffic volume prediction and end-to-end link high-load zone. In using these simulation tools, we were able to estimate sequential transaction in real-network for e-Commerce. We also imported virtual network environment estimated network data, and create background traffic. In a virtual network environment like this, we were able to find out simulation results for traffic volume prediction and end-to-end link high-load zone according to the increase in the number of users based on virtual network environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.900-908
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• 2012

Owing to the proliferation of smart phone users, a proactive spectrum policy is needed in order to deal with increasing data traffic. Therefore, the prediction of frequency requirements for future wireless local area network (WLAN) as well as a licensed cellular communication is necessary. In this paper, we proposed a new prediction method for WLAN spectrum requirements. This method includes both a traditional prediction method and an offloading percentage from cellular network, Also, it can consider a frequency interference between access points using a statistical approach. Based on these approaches, we can predict the spectrum requirements of future domestic WLAN services considering the frequency interference. Finally, we suggest the spectrum policy for WLAN which can prevent spectrum shortage of future WLAN services.

• 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.

• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.1031-1038
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• 2005

In this paper, the maximum traffic quantity and actual traffic quantify of the data which are needed to grasp the statement of a system will be measured more accurately. A concrete quality measurement will be conducted by analysing a change of traffic quantity according to a protocol change and traffic under an overload condition when there is an accident. As a result can make an opportunity to maximize safety of power SCADA. Furthermore, future traffic quantity can be prospected by knowing current traffic quantity and grasping the rate of increase by the analysis and the information can be used as data to secure the band width in advance. It can make stable operation of power SCADA by arranging the limited network resources efficiently by information analysis of a network and expects more confidence.

• Information and Communications Magazine
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• v.29 no.9
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• pp.56-62
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• 2012

초고속 인터넷, 다양한 통신 기기, 신규 인터넷 애플리케이션 등의 확산으로 인터넷 상의 콘텐츠 트래픽 규모가 급격하게 증가하고 있다. 비디오와 같은 대용량 멀티미디어 콘텐츠 트래픽이 전체 트래픽에서 차지하는 비중은 날로 증가하여, 2014년에는 전체 인터넷 트래픽 중 90% 이상을 차지할 것이라고 예측되기도 한다. 따라서 트래픽의 대부분을 차지하는 콘텐츠 중심으로 네트워크 아키텍처를 혁신할 필요성이 대두되고 있다. 본 논문은 최근 급증하는 콘텐츠 서비스의 송수신 특성에 적합한 네트워크 아키텍처에 대한 학계와 산업체의 연구동향과 콘텐츠 네트워킹 관련 기술의 국제 표준화 동향을 고찰하고, 향후 실제 적용을 위한 이슈를 분석한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.12
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• pp.1329-1336
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• 2015

Due to the advances in hardware technologies for low-power CMOS cameras, there have been various researches on wireless video sensor network(WVSN) applications including agricultural monitoring and environmental tracking. In such a system, its core technologies include video compression and wireless transmission. Since data of video sensors are bigger than those of other sensors, it is particularly necessary to estimate precisely the traffic after video encoding. In this paper, we present an estimation method for the encoded video traffic in WVSN networks. To estimate traffic characteristics accurately, the proposed method first measures complexities of frames and then applies them to the bit rate estimation adaptively. It is shown by experimental results that the proposed method improves the estimation of bit rate characteristics by more than 12% as compared to the existing method.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.1006-1009
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• 2007

모바일 애드혹 네트워크는 기존의 셀룰러 네트워크와는 달리 고정된 기지국이 존재하지 않고 모바일 노드들만으로 구성된 네트워크이다. 모바일 애드혹 네트워크의 각각의 노드들은 제한된 자원과 한정된 용량을 가진 배터리로 동작한다. 만일 이 배터리를 모두 소모하게 된다면 중간 노드들이 다운이 되고, 결과적으로 전체 네트워크가 단절되는 문제가 발생할 수 있다. 이러한 문제점을 해결하기 위해서는 한정된 자원을 최대한 효율적으로 사용해야 한다. 이를 위해 본 논문에서는 클러스터 기반의 애드 혹 네트워크 환경에서 발생하는 경로 요청 시 클러스터 내부의 에너지 분산을 통한 네트워크 생존 시간을 연장시키고자 하였다. 효율적인 에너지 분산을 위해 칼만 필터를 통한 클러스터 내부의 트래픽 변화량을 예측하고, 예측값과 노드의 에너지 잔량을 기준으로 경로를 설정하도록 하였다. 실험 결과 생존 시간을 23% 증가시켰고, 칼만 필터를 통한 트래픽 변화량 예측값의 오차는 6.3%로 나타났다. 앞으로 칼만 필터의 관측값을 확장하여 예측값에 대한 오차를 줄이고, 보다 복잡한 네트워크 환경에 적용하는 연구가 필요하다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.307-312
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• 2000

Asynchronous transfer mode(ATM) is flexible to support the various multimedia communication services such as data, voice, and image by applying asynchronous time-sharing and statistical multiplexing techniques to the existing data communication. ATM service is categorized to CBR, VBR, UBR, and ABR according to characteristics of the traffic and a required service qualities. Among them, ABR service guarantees a minimal bandwidth and can transmit cells at a maximum transmission rate within the available bandwidth. To minimize the cell losses in transmission and switching, a feedback information in ATM network is used to control the traffic. In this paper, predictive control algorithms are proposed for the feedback information. When the feedback information takes a long propagation delay to the backward nodes, ATM switch can experience a congestion situation from the queue length increases, and a high queue length fluctuations in time. The control algorithms proposed in this paper provides predictive control model using slop changes of the queue length function and previous data of the queue lengths. Simulation shows the effectiveness result of the proposed control algorithms.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.