• 한국멀티미디어학회논문지
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• 제18권2호
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• pp.189-198
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• 2015

Despite the fact that traffic engineering techniques have been comprehensively utilized in the past to enhance the performance of communication networks, the distinctive characteristics of Software Defined Networking (SDN) demand new traffic engineering techniques for better traffic control and management. Considering the behavior of traffic, large flows normally carry out transfers of large blocks of data and are naturally packet latency insensitive. However, small flows are often latency-sensitive. Without intelligent traffic engineering, these small flows may be blocked in the same queue behind megabytes of file transfer traffic. So it is very important to identify large flows for different applications. In the scope of this paper, we present an approach to detect large flows in real-time without even a short delay. After the detection of large flows, the next problem is how to control these large flows effectively and prevent network jam. In order to address this issue, we propose an approach in which when the controller is enabled, the large flow is mitigated the moment it hits the predefined threshold value in the control application. This real-time detection, marking, and controlling of large flows will assure an optimize usage of an overall network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2170-2190
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• 2012

There are nowadays strong demands for intelligent surveillance systems, which can infer or understand more complex behavior. The application of crowd density estimation methods could lead to a better understanding of crowd behavior, improved design of the built environment, and increased pedestrian safety. In this paper, we propose a new crowd density estimation method, which aims at estimating not only a moving crowd, but also a stationary crowd, using images captured from surveillance cameras situated in various public locations. The crowd density of the moving people is measured, based on the moving area during a specified time period. The moving area is defined as the area where the magnitude of the accumulated optical flow exceeds a predefined threshold. In contrast, the stationary crowd density is estimated from the coarseness of textures, under the assumption that each person can be regarded as a textural unit. A multilayer neural network is designed, to classify crowd density levels into 5 classes. Finally, the proposed method is experimented with PETS 2009 and the platform of Gangnam subway station image sequences.

• International Journal of Automotive Technology
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• 제7권2호
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• pp.227-235
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• 2006

In this paper a robust image processing method with modified Otsu algorithm to recognize the road lane for a real-time controlled autonomous vehicle is presented. The main objective of a proposed method is to drive an autonomous vehicle safely irrespective of road image qualities. For the steering of real-time controlled autonomous vehicle, a detection area is predefined by lane segment, with previously obtained frame data, and the edges are detected on the basis of a lane width. For stable as well as psudo-robust autonomous driving with "good", "shady" or even "bad" road profiles, the variable threshold with modified Otsu algorithm in the image histogram, is utilized to obtain a binary image from each frame. Also Hough transform is utilized to extract the lane segment. Whether the image is "good", "shady" or "bad", always robust and reliable edges are obtained from the algorithms applied in this paper in a real-time basis. For verifying the adaptability of the proposed algorithm, a miniature vehicle with a camera is constructed and tested with various road conditions. Also, various highway road images are analyzed with proposed algorithm to prove its usefulness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.608-627
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• 2016

Wireless mesh networks (WMNs) based on IEEE 802.11s have emerged as one of the prominent technologies in multi-hop communications. However, the deployment of WMNs suffers from serious interference problem which severely limits the system capacity. Using multiple radios for each mesh router over multiple channels, the interference can be reduced and improve system capacity. Nevertheless, interference cannot be completely eliminated due to the limited number of available channels. An effective approach to mitigate interference is to apply dynamic channel switching (DCS) in WMNs. Conventional DCS schemes trigger channel switching if interference is detected or exceeds a predefined threshold which might cause unnecessary channel switching and long protocol overheads. In this paper, a P-learning based dynamic switching algorithm known as learning automaton (LA)-based DCS algorithm is proposed. Initially, an optimal channel for communicating node pairs is determined through the learning process. Then, a novel switching metric is introduced in our LA-based DCS algorithm to avoid unnecessary initialization of channel switching. Hence, the proposed LA-based DCS algorithm enables each pair of communicating mesh nodes to communicate over the least loaded channels and consequently improve network performance.

• Journal of electromagnetic engineering and science
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• 제11권2호
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• pp.128-132
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• 2011

In interference tolerance based spectrum sharing systems, primary receivers (PRs) are protected by a predefined peak or average interference power constraint. To implement such systems, cognitive radio (CR) transmitters are required to adjust their transmit power so that the interference power received at the PR receivers is kept below the threshold value. Hence, a CR-transmitter requires knowledge of its channel and the primary receiver in order to allocate the transmit power. In practice, it is impossible or very difficult for a CR transmitter to have perfect knowledge of this channel state information (CSI). In this paper, we investigate the impact of imperfect knowledge of this CSI on the performances of both a primary and cognitive radio network. For fixed transmit power, average interference power (AIP) constraint can be maintained through knowledge of the channel distribution information. To maintain the peak interference power (PIP) constraint, on the other hand, the CR-transmitter requires the instantaneous CSI of its channel with the primary receiver. First, we show that, compared to the PIP constraint with perfect CSI, the AIP constraint is advantageous for primary users but not for CR users. Then, we consider a PIP constraint with imperfect CSI at the CR-transmitter. We show that inaccuracy in CSI reduces the interference at the PR-receivers that is caused by the CR-transmitter. Consequently the proposed schemes improve the capacity of the primary links. Contrarily, the capacities of the CR links significantly degrade due to the inaccuracy in CSI.

• 천문학회보
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• 제37권2호
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• pp.157.2-157.2
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• 2012

Direct-conversion receivers often suffer from a DC-offset that is a by-product of the direct conversion process to baseband. In general, a basic approach to reduce the DC-offset is to do simple average of the baseband signal and remove the DC by subtracting the average. However, this gives rise to a residual DC offset which degrades the performance when the receiver adopts the coding schemes with high coding rates such as 8-PSK. Therefore, more advanced methods should be additionally required for better performance. While the training sequences are basically designed to have good auto-correlation properties to facilitate the channel estimation, they may be not good for the simultaneous estimation of the channel response and the DC-offset. Also the DC offset compensation under a bad condition does not give good results due to the estimation error. Correspondingly, the proposed scheme employs the two important points. First, the training sequence codes are divided into two groups by MSE(Mean Squared Errors) for estimating the channel taps and then SNR calculated from each group is compared to predefined threshold to do fine DC-offset estimation. Next, ON/OFF module is applied for preventing performance degradation by large estimation error under severe channel conditions. The simulation results of the proposed scheme shows good performances compared to the existing algorithm. As a result, this scheme is surely applicable to the receiver design in many communications systems.

• 대한산업공학회지
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• 제29권4호
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• pp.312-320
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• 2003

Recently there is a growing interest in mobile cellular network providing multimedia service. However, the link bandwidth of mobile cellular network is not sufficient enough to provide satisfactory services to users. To overcome this problem, an adaptive framework has been proposed. In this study, we propose a new method of estimating DPR(Degradation Period Ratio) in an adaptive multimedia network where the bandwidth of ongoing call can be dynamically adjusted during its lifetime. DPR is a QoS(Quality of Service) parameter which represents the ratio of allocated bandwidth below a pre-defined target to the whole service time of a call. We improve estimation method of DPR using DTMC(Discrete Time Markov Chain) model by calculate mean degradation period, degradation probability more precisely than in existing studies. Under Threshold CAC(Call Admission Control) algorithm, we present analytically how to guarantee QoS to users and illustrate the method by numerical examples. The proposed method is expected to be used as one of CAC schemes in guaranteeing predefined QoS level of DPR.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.848-859
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• 2016

System failures in thermal power plants (TPPs) can lead to serious losses because the equipment is operated under very high pressure and temperature. Therefore, it is indispensable for alarm systems to inform field workers in advance of any abnormal operating conditions in the equipment. In this paper, we propose a clustering-based fault detection method for steam boiler tubes in TPPs. For data clustering, k-means algorithm is employed and the number of clusters are systematically determined by slope statistic. In the clustering-based method, it is assumed that normal data samples are close to the centers of clusters and those of abnormal are far from the centers. After partitioning training samples collected from normal target systems, fault scores (FSs) are assigned to unseen samples according to the distances between the samples and their closest cluster centroids. Alarm signals are generated if the FSs exceed predefined threshold values. The validity of exponentially weighted moving average to reduce false alarms is also investigated. To verify the performance, the proposed method is applied to failure cases due to boiler tube leakage. The experiment results show that the proposed method can detect the abnormal conditions of the target system successfully.

• 한국정보과학회논문지:시스템및이론
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• 제29권4호
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• pp.213-219
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• 2002

비밀분산법이란 하나의 비밀정보를 다수의 비밀조각으로 분할하여 다수의 신뢰할 수 있는 사람들에게 공유시킴으로써 비밀정보를 안전하게 유지.관리하는 암호학적 방법이다. 그러나 비밀정보를 공유하는 참가자들이 비밀정보 복원에 대해 서로 다른 권한을 가지고 있을 경우, 이러한 참가자들간의 계층구조를 반영할 수 있는 비밀분산법의 설계가 필요하다. 각 참가자들이 갖는 비밀정보에 대한 복원 권한을 가중치로 표현함으로써 가중치에 따른 비밀정보 공유 및 복원이 가능한 가중치를 갖는 비밀분산법을 제안한다.

• ETRI Journal
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• 제43권5호
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• pp.941-949
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• 2021

In this study, a spatial spectrum method is proposed to cope with the pilot spoofing attack (PSA) problem by exploiting the of uplink-downlink channel reciprocity in time-division-duplex multiple-input multiple-output systems. First, the spoofing attack in the uplink stage is detected by a threshold derived from the predefined false alarm based on the estimated spatial spectrum. When the PSA occurs, the transmitter (That is Alice) can detect either one or two spatial spectrum peaks. Then, the legitimate user (That is Bob) and Eve are recognized in the downlink stage via the channel reciprocity property based on the difference between the spatial spectra if PSA occurs. This way, the presence of Eve and the direction of arrival of Eve and Bob can be identified at the transmitter end. Because noise is suppressed by a spatial spectrum, the detection performance is reliable even for low signal-noise ratios and a short training length. Consequently, Bob can use beamforming to transmit secure information during the data transmission stage. Theoretical analysis and numerical simulations are performed to evaluate the performance of the proposed scheme compared with conventional methods.