• Smart Structures and Systems
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• 제26권2호
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• 한국경영과학회지
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• 제24권4호
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• pp.111-122
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• 1999

In this paper, we consider a queueing network model. where the population constraint within each subnetwork is controlled by a semaphore queue. The total number of customers that may be present in the subnetwork can not exceed a given value. Each node has a constant service time and the arrival process to the queueing network is an arbitrary distribution. A major characteristics of this model is that the lower layer flow is halted by the state of higher layer. We present some properties that the inter-change of nodes does not make any difference to customer's waiting time in the queueing network under a certain condition. The queueing network can be transformed into a simplified queueing network. A dramatic simplification of the queueing network is shown. It is interesting to see how the simplification developed for sliding window flow control, can be applied to multi-layered queueing network.

• 한국정보통신학회논문지
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• 제19권4호
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• pp.819-824
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• 2015

SDN(Software Defined Network)기술은 네트워크 제어기능이 기존의 스위치나 라우터 등의 하드웨어와 별도로 분리되어야 하고 데이터 전달기능과도 역시 분리되어 개발 및 실행될 수 있는 네트워크 구조를 말한다. 네트워크를 계획하고 디자인할 때에는 SDN 기술을 적용하여 반영해야 자원을 효율적으로 반영할 수 있다. 본 연구에서는 일명 Applications SDN을 제안하며 이는 MPLS(Multiprotocol Label Switching) IOS의 절대적으로 필요한 부분을 코딩한 프로그램과 기존 IOS를 결합한 이점(Combined Benefits)을 통해 Controller 부분을 완성하여 적용한 모델을 제안한다. OpenFlow Controller는 LER(Label Edge Router)에 명령을 하고 라우터는 그 명령에 따라 패킷을 EXP bit에 따라 목적지로 전송한다. TCP/IP를 코딩을 통해 최적화된 IOS로 구성한다. OpenFlow 프로토콜을 이용하여 컨트롤러는 MPLS의 정의된 헤더를 패킷에 캡슐화 하여 전송한다.

• 디지털융복합연구
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• 제12권4호
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• pp.285-291
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• 2014

최근 무선 통신장치들이 매우 빠르게 발전되고 사용자에게 보급되고 있다. 이로 인해서 기존의 유선 네트워크 장치들과 새로운 무선 네트워크 장치들을 통합한 새로운 메쉬 네트워크에 대한 요구가 급속히 발전하고 있다. 이런 유 무선 통합 네트워크 환경에서 자동으로 네트워크를 구성하고, 이런 환경에서 사용자 또는 유 무선 통신장치에 대해 인증서비스를 반드시 제공해야만 한다. 하지만 현실적으로 이런 서비스를 제공하고 있지 못하다. 그러므로 본 논문에서 유 무선 통합 네트워크 환경에서 오픈플로우를 사용해 네트워크를 자동으로 구성하고, 커베로스를 응용한 사용자 인증시스템을 제안하였다. 우리가 제안한 인증시스템은 장치 또는 사용자에 대한 인증서비스를 제공할 수 있을 뿐만 아니라, 비밀성, 무결성 서비스를 제공할 수 있다. 추가로 중간자공격에 대해서도 막을 수 있다.

• 제어로봇시스템학회논문지
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• 제6권8호
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• pp.638-651
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• 2000

When the bandwidth resources in a packet-switched network are shared among sessions by MAX-MIN flow control each session is required to transmit its data into the network subject to the MAX-MIN fair rate which is solely determined by network loadings. This passive behavior of sessions if fact can cause seri-ous QoS(Quality of Service) degradation particularly for real-time multimedia sessions such as video since the rate allocated by the network can mismatch with what is demanded by each session for its QoS. In order to alleviate this problem we extend the concept of MAX-MIN fair bandwidth allocations as follows: Individual bandwidth demands are guaranteed if the network can accommodate them and only the residual network band-width is shared in the MAX-MIN fair sense. On the other hand if sum of the individual bandwidth demands exceeds the network capacity the shortage of the bandwidth is shared by all the sessions by reducing each bandwidth guarantee by the MAX-MIN fair division of the shortage. we present a novel flow control algorithm to achieve this extended MAX-MIN fairness and show that this algorithm can be implemented by the existing ATM ABR service protocol with minor changes. We not only analyze the steady state asymptotic stability and convergence rate of the algorithm by appealing to control theories but also verify its practical performance through simulations in a variety of network scenarios.

• 한국멀티미디어학회논문지
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• 제19권5호
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• pp.924-931
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• 2016

In this paper, Various network adaptive MAC scheduling technique is proposed to effectively overcome limits of narrow bandwidth and low transmission speed in underwater. UPFC(Underwater Packet Flow Control) is a technique to reduce both the number of transmission and transmission time using three types (Normal, Blocked, Parallel) of data transmission. In this technique, the load information, in which a transmission node have, is transmitted to destination node using marginal bit in reserved header. Then the transmitted information is referred to determine weighting factor. According to the weighting factor, scheduling is dynamically changed adaptively. The performance of UPFC is analyzed and flow control technique which can be applied to Cluster Based Network and Ad Hoc network as well.

• Computers and Concrete
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• 제5권5호
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• pp.461-473
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• 2008

The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.

• 대한기계학회논문집A
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• 제24권7호
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• pp.1753-1762
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• 2000

An inverse method is presented to obtain material's flow properties by using small punch test. This procedure employs, as the objective function of inverse analysis, the balance of measured load-di splacement response and calculated one during deformation. In order to guarantee convergence to global minimum, simulated annealing method was adopted to optimize the current objective function. In addition, artificial neural network was used to predict the load-displacement response under given material parameters which is the most time consuming and limits applications of global optimization methods to these kinds of problems. By implementing the simulated annealing for optimization along with calculating load-displacement curve by neural network, material parameters were identified irrespective of initial values within very short time for simulated test data. We also tested the present method for error-containing experimental data and showed that the flow properties of material were well predicted.

• 동력기계공학회지
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• 제9권4호
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• pp.24-30
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• 2005

For a reciprocating compressor of household refrigerators, a direct analogy between the pipe flow network and the electric circuit network has been utilized to set up a mathematical model for oil supply system. Individual lubrication elements of the oil supply system, such as propeller- installed oil cap, oil galleries, radial oil feeding holes, spiral oil grooves, and various sliding surfaces have been analogized by equivalent electric elements, and these have been combined together to form an electric circuit corresponding to the whole oil supply system. By solving the closed network equations of the model, oil flow rates at various lubrication elements could be obtained. Total amount of the oil flow rate drawn into the shaft has been measured and compared reasonably well with the prediction of the numerical simulation.

• 한국IT서비스학회지
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• 제12권2호
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• pp.85-101
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• 2013

The wide spread of smartphones and the growth of the number of internet users are reshaping the SNS (Social Network Service). Merging into other service areas and creating new business models with high profits, SNS is no more a service simply providing personal connections. Now SNS has positioned itself as a service platform. SNG (Social Network Game) is a new outcome utilizing SNS as a game platform and showing a rapid growth rate in a short period of time. The number of SNG users is expected to increase steadily. In this study, we examine whether SNG user motivations lead to flow experience and future intention to use. For that purpose, we conducted a survey with smartphone users. The results indicate that flow experience functions as a mediator and user motivations indirectly affect intention to use through flow experience. This paper concludes with discussions on findings and suggestions for future research.