• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.230-238
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• 2022

Internet of Things(IoT) is a communication technology that collects information of object remotely and controls the function of object by adding a communication function to object that does not have a communication function. For the IoT, various communication technologies such as Wi-Fi, 3GPP, and Bluetooth are available, and Long Range(LoRa) is communication technologies specialized in the IoT concept. LoRa is a communication technology that support long-distance, low-power, and low-speed communication, and is suitable for collecting information generated form object in remote equipment and controlling equipment. Because of these characteristics, it is used in many application field, and various performance improvement studies are in progress. This paper intends to propose an ultra-long-range LoRa communication module that can be used in a wider range of applications. We design and implement hardware, firmware, and application software for testing to develop ultra-long-range LoRa communication modules. The implemented module will be tested in a real environment to verify its performance and to check its utilization.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.169-177
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• 2024

Industrial Wireless Sensor Network (IWSN) is a key feature of Industrial IoT that enables industrial automation through process monitoring and control by connecting industrial equipment such as sensors, robots, and machines wirelessly, and must support the strict requirements of modern industrial environments such as real-time, reliability, and energy efficiency. To achieve these goals, IWSN uses reliable communication methods such as multipath routing, fixed redundant resource allocation, and non-contention-based scheduling. However, the issue of wasting redundant resources that are not utilized for communication degrades not only the efficiency of limited radio resources but also the energy efficiency. In this paper, we propose a scheme that utilizes reinforcement learning in communication scheduling to periodically identify unused wireless resources and reallocate them to save energy consumption of the entire industrial network. The experimental performance evaluation shows that the proposed approach achieves about 30% improvement of resource efficiency in scheduling compared to the existing method while supporting high reliability. In addition, the energy efficiency and latency are improbed by more than 21% and 38%, respectively, by reducing unnecessary communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1393-1405
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• 2017

It is well known that duty-cycling control by dynamically adjusting the polling interval according to the traffic loads can effectively achieve power saving in wireless sensor networks. Thus, there has been a significant research effort in developing polling interval adaptation schemes. Especially, Dynamic Low Power Listening (DLPL) scheme is one of the most widely adopted open-looping polling interval adaptation techniques in wireless sensor networks. In DLPL scheme, if consecutive idle (busy) samplings reach a given fixed threshold, the polling interval is increased (decreased). However, due to the trial-and-error based approach, it may significantly deteriorate the system performance depending on given threshold parameters. In this paper, we propose a novel DLPL scheme, called SDL (Sequential hypothesis testing based Dynamic LPL), which employs sequential hypothesis testing to decide whether to change the polling interval conforming to various traffic conditions. Simulation results show that SDL achieves substantial power saving over state-of-the-art DLPL schemes.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.792-793
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• 2005

Circuit testing process is very important in IC Manufacturing there are two ways in research for circuit testing improvement. These are ATPG Tool Design and Test simulation application. We are interested in how to use parallel technique such as one-side communication, parallel IO and dynamic Process with data partition for circuit testing improvement and we use one-side communication technique in this paper. The parallel ATPG Tool can reduce the test pattern sets of the circuit that is designed in laboratory for make sure that the fault is not occur. After that, we use result for parallel circuit test simulation to find fault between designed circuit and tested circuit. From the experiment, We use less execution time than non-parallel Process. And we can set more parameter for less test size. Previous experiment we can't do it because some parameter will affect much waste time. But in the research, if we use the best ATPG Tool can optimize to least test sets and parallel circuit testing application will not work. Because there are too little test set for circuit testing application. In this paper we use a standard sequential circuit of ISCAS89.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.6
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• pp.88-94
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• 2015

Large-scale petrochemical and power plants has increased demanting wireless technology for continuous monitoring. However, the current USN technologies, such as ZigBee and Bluetooth, are lackof reliability and security. Therefore, there is a strong need to apply a new wireless technology standard of the ISA. In this study, a petrochemicalplant safety management system based on the ISA wireless transmitter isdeveloped. ISA100.11a communication module and LTE communication module equippedwith an explosion-proof wireless transmitter are developed. A petrochemicalplant safety management system is built based on the IoT technologies. Thedeveloped system is verified through a wide range of testing and thus, on-siteapplicability is proved.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1183-1184
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• 2017

라즈베리파이와 같은 경량 시스템이 보급되면서, 기존의 서버 중심의 분석 기법에서 경량 시스템에서 경량/순간 분석을 하고, 누적/중량 분석은 서버에서 수행할수 있는 계층적 협업 분석에 대한 연구를 진행하고 있으며, 이를 통해 IoT Thing을 논리적으로 묶어서 Cloud of Things과 같이 센서 데이터 수집/처리를 용이하게 하기 위해 구현된 계층적 협업 분석 SW에 대한 시험 검증 사례에 대한 연구 내용을 담고 있다.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.513-523
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• 2015

A complex event processing system, becoming useful in real life domains, efficiently processes stream of continuous events like sensor data from IoT systems. However, those systems do not work well on some types of queries yet, so that programmers should be careful about that. For instance, they do not sufficiently provide detailed guide to choose efficient queries among the almost same meaning queries. In this paper, we propose an query preprocessing tool for event stream processing systems, which helps programmers by giving them the hints to improve performance whenever their queries fall in any possible bad formats in the performance sense. We expect that our proposed module would be a big help to increases productivity of writing programs where debugging, testing, and performance tuning are not straightforward.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.965-973
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• 2022

As IoT(Internet of Things) devices become common, many algorithms have been developed to protect users' personal information. The laser fault injection attack that threatens those algorithms is a side-channel analysis that intentionally injects a laser beam to the outside of a device to acquire confidential information or abnormal privileges of the system. There are many studies to determine the timing of fault injection to reduce the number of necessary fault injections, but the location to inject faults is only repeatedly searched for the entire area of the device. However, when fault injection is performed in an algorithm-independent area, the attacker cannot obtain the intended faulted statement or attempt to bypass authentication, so finding areas vulnerable to fault injection and performing an attack is an important consideration in achieving a high attack success rate. In this paper, we show that a 100% attack success rate can be achieved by determining the vulnerable areas for fault injection by using electromagnetic and thermal information generated from the device's chip. Based on this, we propose an efficient fault injection attack system.