• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1087-1094
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• 2023

Due to the development of technologies, such as big data, cloud, IoT, and AI, The high data throughput is required, and the importance of network flexibility and scalability is increasing. However, existing network systems are dependent on vendors and equipment, and thus have limitations in meeting the foregoing needs. Accordingly, SDN technology that can configure a software-centered flexible network is attracting attention. In particular, a load balancing method based on SDN can efficiently process massive traffic and optimize network performance. In the existing load balancing studies in SDN environment have limitation in that unnecessary traffic occurs between servers and controllers or performing load balancing only after the server reaches an overload state. In order to solve this problem, this paper proposes a method that minimizes unnecessary traffic and appropriate load balancing can be performed before the server becomes overloaded through a method of assigning weights to servers in stages according to server load.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.1-7
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• 2015

This study is a case study of the research study and education with high school students of natural sciences. Recent development of the Internet of Things (IoT) based on the subject of various studies exist. This study is one of the most portable communication devices of these infancy, yet students were easy to define the molding process of contacting a pager that can go along way in making research topics. We called a pager. Today, it is given a large and complex smart mobile communication devices that can be used for big data. Prior pagers are taught the meaning of the first mobile communication means in our lives were given device. The internal structure is relatively simple and is thought to function relatively simple, just suitable as a teaching practices of high school students with an interest in science and engineering universities. This study can see all of the mechanical, electronic information contents of the radio pager in a relatively simple analysis of the injection molding ONE CAVITY analysis. Furthermore, the students also rated good educational practices that give meaning to remind the convergence training on mass production and process automation.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.121-134
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• 2017

With rapid increasing the development and use of IoT Devices, requirements for safe IoT devices and services such as reliability, security are also increasing. In Security engineering, SDLC (Secure Development Life Cycle) is applied to make the trustworthy system. Secure Development Life Cycle has 4 big steps, Security requirements, Design, Implementation and Operation and each step has own goals and activities. Deriving security requirements, the first step of SDLC, must be accurate and objective because it affect the rest of the SDLC. For accurate and objective security requirements, Threat modeling is used. And the results of the threat modeling can satisfy the completeness of scope of analysis and the traceability of threats. In many countries, academic and IT company, a lot of researches about drawing security requirements systematically are being done. But in domestic, awareness and researches about deriving security requirements systematically are lacking. So in this paper, I described about method and process to drawing security requirements systematically by using threat modeling including DFD, STRIDE, Attack Library and Attack Tree. And also security requirements are described via Common Criteria for delivering objective meaning and broad use of them.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.27-33
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• 2023

In this study, it was analyzed with the dyeing pattern of Diospyros kaki Thunb (persimmon) and was tried to numerically evaluate how the dyeing pattern in silk fabrics and cells was changed by different mordants. When the dyed silk fabrics were sufficiently dried, the silk fabrics were found to have a pale yellow color. Interestingly, iron II sulfate mordant changed the color change the most, silk fabrics were dyed with a color close to brown or dark purple. For numerical analysis, 19% and 62.5% color changes could be induced by sodium tartrate plus citric acid and copper acetate, respectively. Iron II sulfate induced the greatest difference than that of untreated mordants at 88%. About 5% and 10% of Chinese hamster ovary (CHO) cells were stained by sodium tartrate plus citric acid and copper acetate, respectively. The staining effect induced by iron II sulfate was about 2.4 times higher than the staining effect by sodium tartrate plus citric acid. In previous studies, staining results have been visually confirmed. However, this results not only visually confirmed the dyeing, but also quantified the color change. In particular, if numerical results are continuously integrated into big data, any researcher will be able to easily obtain similar results even if the method, time, volume, etc. are changed. In addition, the numerical data of this study is considered to be an important basis for building a database for IoT construction and computer analysis.

• Knowledge Management Research
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• v.21 no.1
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• pp.41-59
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• 2020

This explorative study examines the difference in firm performance according to the adoption of the core technology of the Fourth industrial revolution, including artificial intelligence(AI), internet of things (IoT), cloud computing, and big data technology. Additionally, we investigate the importance of internal organizational structure exclusively responsible for information security. We analyze unique microdata offered by the Korea Information Society Development Institute to examine the impact of the adoption of the new technologies and the existence of organizational structure for information protection on firm performance, i.e., firm sales. By considering the core information technology as powerful knowledge assets, we argue that the adoption of such technology leads firms to have comparative advantage comparing to the competitors. Also, we emphasize the need to consider the organizational structure suitable for information security, which can become a structural asset of a firm.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1228-1231
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• 2017

The development of ICT brings the change in daily life and the digitized data are increasing in usage. The combination between GPS and internet results in extensive diffusion of space related information by way of smartphone, sensor and SNS. Jeju Island is only one special self-governing province in Republic of Korea and deserves to be proud of the unique culture, having those designated Intangible Cultural Heritage from UNESCO such as Culture of Jeju Haenyeo or Women Divers and Jeju Chilmeoridang Yeongdeunggut or Exorcism of Praying big Catch. In this paper, I suggest how to preserve fadable tradition economically and technically and expect to develop Haenyeo fitted portable sensors and IoT platform.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.136-137
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• 2017

4차 산업혁명시대가 도래함에 따라 해운항만기업에서 4차 산업혁명을 주도하는 ICT를 활용하기 위한 노력이 다양하게 전개되고 있다. 특히 해운항만물류분야에서는 IoT센서가 만들어내는 다양한 데이터를 분석하여 도출된 인사이트를 기반으로 업무효율성을 높이고자 빅데이터분석 기법을 적용하기 시작하고 있다. 본 연구에서는 해운항만기업들 중 빅데이터분석을 도입해서 활용하고 있거나, 빅데이터를 업무에 활용하기 위해 도입의도를 가지고 있는 기업의 종사자들을 대상으로 어떤 요인들이 빅데이터 사용의도를 높여주는 지에 대하여 실증분석.