• Journal of the Korean Solar Energy Society
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• v.36 no.5
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• pp.31-50
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• 2016

To develope a greenhouse fog cooling system to control the temperature and relative humidity simultaneously to the target value, a theoretical analysis and experiments were done. The control process includes the measuring of environmental variables, setting and coding of the water and heat balance equations to maintain the target temperature and relative humidity in greenhouse, calculating of the open level of the greenhouse roof window that governs the natural ventilation and spray water quantity, and operating of the motor to open/close the roof window and pump to spray for water. The study results were shown to be very good because the average air temperature in the greenhouse was kept to be about $28.2^{\circ}C$ with the standard deviation of about $0.37^{\circ}C$ compared to the target temperature of $28^{\circ}C$ and the average relative humidity was about 75.2% compared to the target relative humidity was 75% during the experiments. The average outside relative humidity was about 41.0% and the average outside temperature was $27.2^{\circ}C$ with the standard deviation of about $0.54^{\circ}C$. The average solar intensity in the greenhouse was 712.9 W. The wind velocity of outside greenhouse was 0.558 m/s with the standard deviation of 0.46 m/s.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 1998.05a
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• pp.39-44
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• 1998

현재 국내에 보급되어 있는 현대화 온실 203개를 대상으로 냉난방과 관련된 설비현황을 조사하여 분석한 결과를 요약하면 다음과 같다. \circled1 온실의 건설방위는 남북동(58.1%)과 동서동(26.8%)이 대부분이었고, 철골온실은 Wide-span형이 81.8%, 플라스틱온실은 1-2W형 온실이 97.5%였다. 휴작하는 온실은 약 41%정도였고, 재배작물은 채소류가 약 80%, 화훼류가 약 20%정도였으며, 재배방식은 철골온실의 경우 양액재배가 57.2%, 플라스틱온실에서는 토양재배가 88.5%였다. \circled2 온실의 외부 피복재는 철골온실은 유리가 92.2%, 플라스틱온실에서는 PE가 43.3%, EVA가 51.9%로 대부분이었다. 철골온실은 1중피복이 98.7%로 거의 전부이었고, 플라스틱온실에서는 2중피복이 78.7%로 나타나, 철골온실에서 보온커튼을 통한 보온성 향상과 밀폐성이 더욱 중요함을 알 수 있다. \circled3 보온용 피복재는 부직포가 64.9%로 가장 많았고 대부분 2층커튼(85.9%)이었으며, 개폐방식은 대부분 예인식(92.7%)의 자동개폐방식(75.2%)이었다. 한편 바닥을 피복한 온실은 약 30% 정도로 나타나, 바닥피복으로 인한 축열이나 반사효과를 감안할 때 효율적인 바닥처리가 요망된다. \circled4 온실의 난방방식은 철골온실에서는 온수안방(47.3%)이 온풍난방(33.8%)보다 다소 많았으며, 플라스틱온실에서는 대부분 온풍난방(90.8%)이었다. 온실의 난방위치는 대부분 지상난방(89.8%)이었고 지중난방은 극소수로 나타나, 앞으로 지중난방을 통한 난방비 절감과 품질향상에 관한 실용화 연구가 요망된다. 난방용 연료는 대부분 경유(83.9%)로 나타나, 난방비를 절감할 수 있는 저가의 연료를 사용할 수 있는 난방시스템의 개발이 요청된다. \circled5 온실의 냉방방법은 차광(51.8%)과 지붕살수(33.9%)가 대부분이었으며 미스트와 포그시스템을 설치한 온실은 소수에 불과하였고, 극소수의 온실에서는 지붕위나 온실내에 지붕면과 평행하게 설치한 경우도 있었다.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.219-228
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• 2019

Thanks to the development of information technology and the vitalization of smart services, the Internet of Things (IoT) technology, in which various smart devices are connected to the network, has been continuously developed. In the legacy IoT architecture, data processing has been centralized based on cloud computing, but there are concerns about a single point of failure, end-to-end transmission delay, and security. To solve these problems, it is necessary to apply decentralized blockchain technology to the IoT. However, it is hard for the IoT devices with limited computing power to mine blocks, which consumes a great amount of computing resources. To overcome this difficulty, this paper proposes an IoT architecture based on the edge computing technology that can apply blockchain technology to IoT devices, which lack computing resources. This paper also presents an operaional procedure of blockchain in the edge computing-based IoT architecture.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1571-1576
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• 2018

Recently, the attractive changes of mobile device are a improvement of the computing performance, dramatic improvement of storage capacity, constant connection to the internet, and sophisticated development of display technology. As a result, database applications utilizing mobile devices are emerging. These applications include databases for mobile servers, databases for edge computing, and fog computing. Therefore, it is important to pay attention to the current mobile database and pay attention to whether it has suitable performance for the applications. In this paper, the most common mobile database, SQLite3 is selected and experimented to test and understand the update performance and characteristics. The results of experiment are compared with the one of Oracle database at the same condition to evaluate the experiment. As a result, Insert Performance of SQLite3 has a lot of points to be improved and Update performance is very good. Especially, the performance of Range Query is excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1117-1122
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• 2020

The improving performance and utilizing application fields of mobile devices are getting bigger and wider. With this trend, applications that use database engines on mobile devices are also becoming common. Applications requiring mobile databases include mobile server databases, edge computing, fog computing, and the like. By the way, the most representative and widely used mobile database is SQLite3. In this paper, we test and compare the update performance of SQLite3 by some file systems. The update performance of the file systems in the mobile environment is an important performance factor in the limited H/W environment. The comparison file system was chosen as FAT, Ext2, and NTFS. Under the same conditions, experiments with each file system to test update performance and characteristics were processed. From the experimental results, we could analyze the advantages and disadvantages of each file system for each database update pattern.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.3
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• pp.1-7
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• 2021

Appropriate containers are deployed to cope with new request arrivals at Fog Computing (FC) hosts. In the case, we can consider two scenarios: (1) the requests may be queued until sufficient resources are prepared for the container deployments; (2) FC hosts may transfer arrived service requests to nearby FC hosts when they cannot accommodate new container deployments due to their limited or insufficient resources. Herein, for more employed neighboring FC hosts, arrived service requests may experience shorter waiting time in container deployment queue of each FC host. In contrast, they may take longer transfer time to pass through increased number of FC hosts. For this reason, there exists a trade-off relationship in the container deployment time depending on the number of employed FC hosts accommodating service request arrivals. Consequently, we numerically analyze the trade-off relationship to employ optimal number of neighboring FC hosts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.162-169
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• 2022

In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A^* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A^* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1551-1558
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• 2022

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.