• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1463-1470
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• 2021

With the development of ICT technology, a monitoring system to check the status of an object to be managed in real time in various industrial fields is widely used. Existing monitoring systems implemented individual systems according to monitoring targets, but recently, monitoring systems have been implemented using open sources such as Prometheus and Grafana. When using Prometheus and Grafana, many parts become more convenient compared to the existing monitoring system development method, but there are still problems. In this paper, to solve this problem, we propose an integrated monitoring system that supports Prometheus and Grafana. The proposed system is a detailed module that collects, stores, visualizes, and manages data to be monitored, and each module is implemented so that roles can be divided and existing problems can be solved. The proposed system can conveniently manage and monitor monitoring targets stored in heterogeneous databases, and create dashboards through simple operation.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.118-121
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• 2021

슈퍼컴퓨터는 수백~수천 노드의 컴퓨팅 자원이 연결되어 복잡한 계산이나 대규모 데이터를 병렬 처리하며 일부 노드에서 발생하는 예상치 못한 문제는 전체적인 시스템 성능 저하로 이어질 수 있기 때문에 슈퍼컴퓨터 모니터링과 성능 분석은 슈퍼컴퓨터를 구축하고 운영하는데 필수적인 요소로 볼 수 있다. 본 논문에서는 오픈소스 소프트웨어인 Performance Co-Pilot, Bpftrace, Grafana를 활용한 슈퍼컴퓨터 모니터링 및 성능분석 시스템 구축 방안을 제안하였으며 이를 통해서 확장가능하면서도 유연한 구조의 슈퍼컴퓨터 모니터링 및 성능 분석이 가능함을 보였다.

• Smart Media Journal
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• v.10 no.2
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• pp.110-118
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• 2021

The Internet of Things (IoT) technology, a key growth engine of the 4th industrial revolution, has grown to a stage where it can autonomously communicate with each other and process data according to space and circumstances. Accordingly, the IT infrastructure becomes increasingly complex and the importance of the monitoring field for maintaining the system stably is increasing. Monitoring technology has been used in the past, but there is a need to find a flexible monitoring system that can respond to the rapidly changing ICT technology. This paper conducts research on designing and testing an open source-based Prometheus monitoring system. We builds a simple infrastructure based on IoT devices and collects data about devices through the Exporter. Prometheus collects data based on pull and then integrates into one dashboard using Grafana and visualizes data to monitor device information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2801-2815
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• 2022

With the advent and realization of Software Defined Network (SDN) architecture, many organizations are now shifting towards this paradigm. SDN brings more control, higher scalability, and serene elasticity. The SDN spontaneously changes the network configuration according to the dynamic network requirements inside the constrained environments. Therefore, a monitoring system that can monitor the physical and virtual entities is needed to operate this type of network technology with high efficiency and proficiency. In this manuscript, we propose a real-time monitoring system for data collection and visualization that includes the Prometheus, node exporter, and Grafana. A node exporter is configured on the physical devices to collect the physical and virtual entities resources utilization logs. A real-time Prometheus database is configured to collect and store the data from all the exporters. Furthermore, the Grafana is affixed with Prometheus to visualize the current network status and device provisioning. A monitoring system is deployed on the physical infrastructure of the KOREN topology. Data collected by the monitoring system is further pre-processed and restructured into a dataset. A monitoring system is further enhanced by including machine learning techniques applied on the formatted datasets to identify the elephant flows. Additionally, a Random Forest is trained on our generated labeled datasets, and the classification models' performance are verified using accuracy metrics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1706-1712
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• 2022

Recently, the safety of chemical substances has gained attention due to incidents occurring in petrochemical industrial complexes, such as gas leaks and fires. In particular, industrial complexes in Ulsan and Yeosu (South Korea) are valuable as they significantly contribute to the petrochemical industry, but accidents may occur due to chemical leakage. Therefore, in this study, sensor nodes are configured at an interval of 20 [m] based on outdoor facilities standards to respond to chemical accidents, and exposure consideration of 8 h (TWA) and 15 min (STEL) are proposed in TLVs. The proposed system pre-processes data collected in multi-hop communication at a cycle of 0.6-0.75 [s] using Python and stores it in the MySQL database through SQL and a real-time remote monitoring system that updates the stored data once every 5 s is implemented by linking MySQL and Grafana.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.551-557
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• 2024

Hydrogen is a renewable energy source with various characteristics such as clean, carbon-free and high-energy, and is internationally recognized as a "future energy". With the rapid development of the hydrogen energy industry, more hydrogen infrastructure is needed to meet the demand for hydrogen. However, hydrogen infrastructure accidents have been occurring frequently, hindering the development of the hydrogen industry. HyRAM+, developed by Sandia National Laboratories, is a software toolkit that integrates data and methods related to hydrogen safety assessments for various storage applications, including hydrogen refueling stations. HyRAM+'s physics mode simulates hydrogen leak results depending on the hydrogen refueling station components, graphing gas plume dispersion, jet frame temperature and trajectory, and radiative heat flux. In this paper, hydrogen leakage data was extracted from a hydrogen refueling station in Samcheok, Gangwon-do, using HyRAM+ software. A hydrogen leakage simulator was developed using data extracted from HyRAM+. It was implemented as a dashboard that shows the data generated by the simulator using a database and Grafana.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.115-117
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• 2021

최근 인공지능 및 빅데이터 연구가 대두되면서 슈퍼컴퓨터와 같은 고성능컴퓨터를 이용하여 다양한 연구환경을 제공할 수 있어야 한다는 요구가 증가하고 있다. 이에 한국과학기술정보연구원(KISTI)에서는 슈퍼컴퓨터 등 고성능컴퓨터를 인프라로 활용하는 KI(KISTI Intelligent) Cloud를 개발하여 서비스하고 있다. 본 논문에서는 KI Cloud의 모니터링 기능의 설계 및 구현 방법을 기술하였다. KI Cloud는 다양한 자원으로부터 데이터를 효율적으로 수집하고, 데이터를 시각화할 수 있는 오픈소스인 Prometheus와 Grafana를 이용하여 모니터링 기능을 개발하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.81-87
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• 2023

SAE J2601 and SAE J2799, the communication protocols between a hydrogen refueling station and a fuel cell electric vehicle, only cover hydrogen charging. In this paper, we measure the hydrogen detection, current, and voltage of a fuel cell electric vehicle and transmit the sensor data to the hydrogen refueling station by changing the WiFi protocol. A small-scale laboratory model was built using Raspberry Pi for sensing, controlling, and transmitting sensor data of a fuel cell electric vehicle. The sensor data was stored in the database of the hydrogen refueling station, and a dashboard was configured using Grafana to analyze the stored data. When hydrogen is detected, the dispenser valve of the hydrogen refueling station is locked. Then, we measured the average transmission delay according to the WiFi protocol. The results showed that IEEE 802.11a is the most suitable WiFi protocol for transmitting sensor data between the hydrogen refueling station and the fuel cell electric vehicle.