• ETRI Journal
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• 제44권2호
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• pp.313-326
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• 2022

This study presents a noble scheme for distributed and parallel simulations with optimized agent placement for simulation instances. The traditional parallel simulation has some limitations in that it does not provide sufficient performance even though using multiple resources. The main reason for this discrepancy is that supporting parallelism inevitably requires additional costs in addition to the base simulation cost. We present a comprehensive study of parallel simulation architectures, execution flows, and characteristics. Then, we identify critical challenges for optimizing large simulations for parallel instances. Based on our cost-benefit analysis, we propose a novel approach to overcome the performance constraints of agent-based parallel simulations. We also propose a solution for eliminating the synchronizing cost among local instances. Our method ensures balanced performance through optimal deployment of agents to local instances and an adaptive agent placement scheme according to the simulation load. Additionally, our empirical evaluation reveals that the proposed model achieves better performance than conventional methods under several conditions.

• 신재생에너지
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• 제19권3호
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• pp.13-21
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• 2023

Smart windows are capable of varying their visible light transmittance (VLT) in response to changing environmental conditions. The VLT variability of architectural windows is highly valuable because it enables indoor lighting and energy environments to align with external changes. However, challenges such as high installation costs and assurance of glass visibility have prompted the exploration of alternative solutions, including models incorporating partially applied smart windows., Prior research focused on useful daylight illuminance (UDI) analysis for south-facing office buildings, pointing out suitable areas for smart-window implementation to enhance lighting control. In this study, we broadened this scope by determining optimal smart-window application zones under changing building orientation. Furthermore, we studied the correlation between building orientation and smart-window deployment areas.

• Journal of Information Processing Systems
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• 제19권5호
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• pp.702-712
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• 2023

Load balancing plays a crucial role in ensuring the stable operation of information management systems during periods of high user access requests; therefore, load balancing approaches should be reasonably selected. Moreover, appropriate load balancing techniques could also result in an appropriate allocation of system resources, improved system service, and economic benefits. Nginx is one of the most widely used loadbalancing software packages, and its deployment is representative of load-balancing application research. This study introduces Nginx into an educational administration system, builds a server cluster, and compares and sets the optimal cluster working strategy based on the characteristics of the system, Furthermore, it increases the stability of the system when user access is highly concurrent and uses the Nginx reverse proxy service function to improve the cluster's ability to resist illegal attacks. Finally, through concurrent access verification, the system cluster construction becomes stable and reliable, which significantly improves the performance of the information system service. This research could inform the selection and application of load-balancing software in information system services.

• 대한임베디드공학회논문지
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• 제18권6호
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• pp.293-301
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• 2023

With the advancement of artificial intelligence and its various use cases, accessing it through edge computing environments is gaining traction. However, due to the nature of edge computing environments, efficient management and optimization of clusters distributed in different geographical locations is considered a major challenge. To address these issues, this paper proposes a centralization and automation tool called KubEVC-Agent based on Kubernetes. KubEVC-Agent centralizes the deployment, operation, and management of edge clusters and presents a use case of the data transformation for optimizing intra-cluster communication. This paper describes the components of KubEVC-Agent, its working principle, and experimental results to verify its effectiveness.

• 시스템엔지니어링학술지
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• 제13권1호
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• pp.79-88
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• 2017

For the PBL contract, it is necessary for the contracting parties to share information regarding the reasonable inventory-level and the cost of its repair parts for the estimated demand. There are various models which can be used for this purpose. Among them, V-METRIC model is considered to be the most efficient and is most frequently applied. However, this model is usually used for optimizing the inventory level of the repair parts of the system under operation. The model uses a time series forecast model to determine the demand rate, which is a mandatory input factor for the model, based on past field data. However, since the system at the deployment stage has no operational performance record, it is necessary to find another alternative to be used as the demand rate of the model application. This research applies the V-METRIC model to find the optimal inventory level and cost estimation for repairable items to meet the target operational availability, which is a key performance indicator, at the time of the PBL contract for the deployment system. This study uses the calculated value based on the allocated MTBF to the system as the demand rate, which is used as input data for the model. Also, we would like to examine changes in inventory level and cost according to the changes in target operational availability and MTBF allocation.

• 한국음향학회지
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• 제22권3호
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• pp.224-232
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• 2003

본 논문에서는 능동 소나의 구성 방법 및 관측 오차에 따른 위치 추정 성능에 대해서 다룬다. 능동 소나는 구성 방법에 따라서 크게 단상태 (Monostatic) 소나, 양상태 (Bistatic) 소나, 다중상태 (Multistatic) 소나로 분류될 수 있으며, 각각의 오차에 대한 특성이 서로 다르다 각 수신기가 거리 정보와 방위 정보를 얻을 수 있다는 가정하에 단상태, 양상태 소나와 다중상태 소나의 위치 추정 성능에 대해 비교해 보고 기존의 정보 융합 방법인 최소 자승법 (LS: Least square)에 가중치를 주는 가중치 최소 지승법 (WLS: Weighted least square)을 제안하였다. 또한, 제안된 방법을 이용하여 수신기의 수, 송수신기간 거리와 위치 추정 성능과의 연관성에 대하여 알아보고 효과적인 다중상태 소나 배치에 대한 연구를 수행하였다. 모의 실험결과 다중상태 소나의 위치 추정 제곱근 오차평균이 단상태 소나에 비해 약 35.98%, 양상태 소나에 비해 약 37.45% 우수한 것을 볼 수 있었으며 WLS가 LS에 비해 평균 7.4% 우수한 성능을 나타내었고 각 센서에 입력되는 정보의 분산 차가 클수록 성능 향상율이 증가하는 경향을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권9호
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• pp.1544-1572
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• 2011

Task placement and scheduling are traditionally studied in following aspects: resource utilization, application throughput, application execution latency and starvation, and recently, the studies are more on application scalability and application performance. A methodology for task placement and scheduling centered on tasks based on virtual machines is studied in this paper to improve the performances of systems and dynamic adaptability in applications development and deployment oriented parallel computing. For parallel applications with no real-time constraints, we describe a thought of feature model and make a formal description for four layers of task placement and scheduling. To place the tasks to different layers of virtual computing systems, we take the performances of four layers as the goal function in the model of task placement and scheduling. Furthermore, we take the personal preference, the application scalability for a designer in his (her) development and deployment, as the constraint of this model. The workflow of task placement and scheduling based on virtual machines has been discussed. Then, an algorithm TPVM is designed to work out the optimal scheme of the model, and an algorithm TEVM completes the execution of tasks in four layers. The experiments have been performed to validate the effectiveness of time estimated method and the feasibility and rationality of algorithms. It is seen from the experiments that our algorithms are better than other four algorithms in performance. The results show that the methodology presented in this paper has guiding significance to improve the efficiency of virtual computing systems.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• 한국융합학회논문지
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• 제6권4호
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• pp.139-146
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• 2015

융합환경의 대표적인 도구인 WSN은 환경 구성의 기본 인프라에서부터 기업의 재고-생산-유통 관리에 이르는 비즈니스 모델까지 다양한 방향으로 활용되고 있다. 그러나, 안전하게 보호되어야 할 조직의 고유정보가 WSN과 같은 ICT와 융합되어 정보화 되면서 외부로 손쉽게 유출될 수 있는 위험에 놓여져 있다. 이에 따라, 안정적인 기업의 비즈니스를 위하여 보안성 있는 센서노드의 배치 전략이 필요한 시점이다. 조직의 보안현황을 고려하지 않은 단편적인 보안성 강화전략의 수립은 보안사고 발생 시 조직의 비즈니스 연속성에 큰 영향을 미친다. 그러나 그간의 조직의 보안성 진단을 위한 보안 수준평가 모형들은 대부분 기술적 중심의 측정방법이 진행되고 있으며, 관리적 요인과 환경적 요인에 대한 연구는 매우 부족한 상태이다. 따라서, 본 연구에서는 보안성 있는 센서노드 배치전략을 수립하기 위하여 융합환경을 기반으로 조직의 보안성을 진단하고 이에 따르는 전략수립방안을 연구하고자 한다.

• 한국ITS학회 논문지
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• 제18권1호
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• pp.27-42
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• 2019

대심도 실내공간에서 직면하는 재난상황에서 재실자는 종합적인 상황인지가 불가능하며, 공간지각 능력 저하로 황금시간 내 탈출이 쉽지 않다. 주어진 시간내 피난대피가 어려운 상황에서는 최대한 안전한 구역으로 이동 가능한 설계를 제시하여야 하는데, 본 연구에서는 실내 공간 보행 통행량 기반 평가 시뮬레이션인 PATS (Pedestrian movement based Assessment Toolkit for Simulation)을 활용하여, 복합환승센터 피난대피구역 적정 위치 선정을 위한 분석 체계를 수립하고, 지하 6층 대심도 복합환승센터의 시나리오 분석을 통해 피난대피 경로 상 문제점을 도출하여 이에 적합한 피난대피 구역 적정 위치를 제안하였다.