• Journal of Communications and Networks
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• v.3 no.4
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• pp.383-395
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• 2001

Recent measurement and simulation studies have revealed that wide area network traffic displays complex statistical characteristics-possibly multifractal scaling-on fine timescales, in addition to the well-known properly of self-similar scaling on coarser timescales. In this paper we investigate the performance and network engineering significance of these fine timescale features using measured TCP anti MPEG2 video traces, queueing simulations and analytical arguments. We demonstrate that the fine timescale features can affect performance substantially at low and intermediate utilizations, while the longer timescale self-similarity is important at intermediate and high utilizations. We relate the fine timescale structure in the measured TCP traces to flow controls, and show that UDP traffic-which is not flow controlled-lacks such fine timescale structure. Likewise we relate the fine timescale structure in video MPEG2 traces to sub-frame encoding. We show that it is possibly to construct a relatively parsimonious multi-fractal cascade model of fine timescale features that matches the queueing performance of both the TCP and video traces. We outline an analytical method ta estimate performance for traffic that is self-similar on coarse timescales and multi-fractal on fine timescales, and show that the engineering problem of setting safe operating points for planning or admission controls can be significantly influenced by fine timescale fluctuations in network traffic. The work reported here can be used to model the relevant characteristics of wide area traffic across a full range of engineering timescales, and can be the basis of more accurate network performance analysis and engineering.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.931-936
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• 2004

GBFCM(DM), Gradient-based Fuzzy c-means with Divergence Measure, for efficient clustering of GPDF(Gaussian Probability Density Function) in MPEG VBR video data modeling is proposed in this paper. The proposed GBFCM(DM) is based on GBFCM( Gradient-based Fuzzy c-means) with the Divergence for its distance measure. In this paper, sets of real-time MPEG VBR Video traffic data are considered. Each of 12 frames MPEG VBR Video data are first transformed to 12-dimensional data for modeling and the transformed 12-dimensional data are Pass through the proposed GBFCM(DM) for classification. The GBFCM(DM) is compared with conventional FCM and GBFCM algorithms. The results show that the GBFCM(DM) gives 5∼15% improvement in False Alarm Rate over conventional algorithms such as FCM and GBFCM.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.235-247
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• 1997

In this study, the performance of ATM multiplexer with MPEG(Motion Pictures Experts Group) video is analyzed by considering the effect of the MPEG GOP(Group of Pictures) structure. By assuming that frame starting times are synchronized, aggregated traffics are considered to be transmitted at the beginning of each frame time units. The aggregated number of cells generated during a frame time unit is, therefore, derived from distributions of individual sources. The stationary probability of buffer occupancy can be easily obtained by using a property of the periodicity of aggregated traffics. Simulation approach is also used to determine the traffic load for a given probability of satisfying QoS(Quality of Service).

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.156-167
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• 2007

In this paper, we develop the model based prediction algorithm for Variable-Bit-Rate(VBR) video traffic with regular Group of Picture(GOP) pattern. We use multiplicative ARIMA process called GOP ARIMA (ARIMA for Group Of Pictures) as a base stochastic model. Kalman Filter based prediction algorithm consists of two process: GOP ARIMA modeling and prediction. In performance study, we produce three video traces (news, drama, sports) and we compare the accuracy of three different prediction schemes: Kalman Filter based prediction, linear prediction, and double exponential smoothing. The proposed prediction algorithm yields superior prediction accuracy than the other two. We also show that confidence interval analysis can effectively detect scene changes of the sample video sequence. The Kalman filter based prediction algorithm proposed in this work makes significant contributions to various aspects of network traffic engineering and resource allocation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.575-596
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• 2009

Facing limited network resources such as bandwidth and processing capability, the Internet will have congestion from time to time. In this paper, we propose a scheme to maximize the total utility offered by the network to the end user during congested times. We believe the only way to achieve our goal is to make the scheme application-aware, that is, to take advantage of the characteristics of the application. To make our scheme scalable, it is designed to be class-based. Traffic from applications with similar characteristics is classified into the same class. We adopted the RED queue management mechanism to adaptively control the traffic belonging to the same class. To achieve the optimal utility, the traffic belonging to different classes should be controlled differently. By adjusting link bandwidth assignments of different classes, the scheme can achieve the goal and adapt to the changes of dynamical incoming traffic. We use the control theoretical approach to analyze our scheme. In this paper, we focus on optimizing the control on two types of traffic flows: TCP and Simple UDP (SUDP, modeling audio or video applications based on UDP). We derive the differential equations to model the dynamics of SUDP traffic flows and drive stability conditions for the system with both SUDP and TCP traffic flows. In our study, we also find analytical results on the TCP traffic stable point are not accurate, so we derived new formulas on the TCP traffic stable point. We verified the proposed scheme with extensive NS2 simulations.

• The KIPS Transactions:PartC
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• v.8C no.2
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• pp.164-172
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• 2001

최근 인터넷의 확산과 더불어 디지털 비디오 라이브러리(DVL : Digital Video Library) 서비스에 대한 관심이 고조되고 있다. 그러나 현재의 통신망 대역폭과 스위칭 환경 하에서는 종단간 QoS 보장하는데 많은 제약사항이 존재한다. 따라서 본 논문에서는 비디오 스트림 처리를 효율적으로 수행하여, 지연-처리율 특성을 만족할 수 있는 스트림 스위칭 구조를 제안하고 이에 대한 성능을 분석하였다. 제안된 ATM-기반 스트림 스위치는 각각 다중화되는 CBR(Constant Bit Rate) 및 VBR(Variable Bit Rate) 스트림의 QoS(Quality of Service)를 보장해야만 한다. 성능분석 결과는 제안된 스위치의 처리율이 r=4일 때 약 0.996의 값을 보였으며, 지연시간도 부하가 0.7 이하일 때 2미만으로 특정되었다. 이 결과는 제안된 구조가 적당한 입력 스트림의 그룹핑을 통하여 비디오 응용을 위한 처리율 및 지연 요구사항 QoS를 보장할 수 있음을 보여준다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.324-326
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• 2005

An adaptive Chunk algorithm is newly devised and a collaborative streaming is designed for high quality multimedia streaming service under time varying traffic conditions. An LMS based prediction filter is used to compensate the effect of time varying background traffic of the WAN. The underflow is generated for the $20\~28\%$ of the data stored in the central server by applying the FARIMA(Fractional Autoregressive Integrated Moving Average) traffic modeling method. The proposed algorithm is tested with the MPEG-2 video files and compensates $71\~85\%$ of central stream underflow.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1377-1383
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• 2012

The first frame of a GOP is encoded in intra mode which generates a larger number of bits. In addition, the first frame is used for the inter mode encoding of the following frames. Thus the intial QP for the first frame affects the first frame as well as the following frames. Traditionally, the initial QP is determined among four constant values only depending on the bpp. Although this initialization scheme is simple, yet it is not accurate enough. An accurate intial QP prediction scheme should not only depends on bpp but also on the complexity of the video sequence and the output bandwidth. In this paper, we propose a traffic model for finding the optimal initial QP which maximizes the PSNR of the GOP. We also propose a method to find model parameters for real-time video encoding. It is shown by experimental results that the proposed traffic model captures initial QP characteristics effectively and the proposed method for model parameters accurately estimates the real values.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.95-103
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• 2009

Global interests for construction of 3 dimensional spatial information has risen due to development of measurement sensors and data processing technologies. In spite of criticism for the violation of personal privacy, CCTV cameras equipped in outdoor public space of urban area are used as a fundamental sensor for traffic management, crime prevention or hazard monitoring. For safety guarantee in urban environment and disaster prevention, a surveillance system integrating pre-constructed 3 dimensional spatial information with CCTV data or video sequence is needed for monitoring and observing emergent situation interactively in real time. In this study, we proposed applicability of the prototype system for web visualization based on X3D, an international standard of real time web visualization, by integrating 3 dimensional spatial information with video sequence.