• Title/Summary/Keyword: big data ecosystem

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The Cloud Computing Ecosystem and Policy Directions (클라우드 컴퓨팅 생태계 및 정책 방향)

  • Kim, B.I.;Shin, H.M.
    • Electronics and Telecommunications Trends
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    • v.27 no.2
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    • pp.137-148
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    • 2012
  • 최근 클라우드 컴퓨팅은 대형 데이터 센터를 건립하면서 관련 투자가 확대되고 있고 이러한 추세는 최근 스마트폰 확산과 모바일 네트워크의 고도화로 인해 모바일 클라우드 시장이 급속히 성장하는 등 Big Data 대응 수단으로 더욱 더 주목받는 분야 중의 하나이다. 이에 정부는 클라우드 컴퓨팅 분야에 대한 종합적인 정책을 추진하기 위해서 각 기관 또는 부처 합동으로 정책 방향을 마련하고 있는 상황이다. 본고에서는 클라우드 컴퓨팅을 구성하는 생태계를 관련 기술과 연계하여 분석해 봄으로써 각 생태계 구성요소별 경쟁력 및 시사점을 먼저 도출한다. 이를 통해 국내 클라우드 산업 경쟁력 강화를 위해 기술개발(R&D), 인력양성, 기반구축 및 제도개선 측면에서 정책 방향을 제시함으로써 향후 클라우드 컴퓨팅 경쟁력 강화를 통한 산업 활성화를 위해서 정부 및 관련 연구기관이 추진해야 할 아젠다를 수립하는 데 있어 그 방향을 제시한다.

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Analysis of Sound Distribution Characteristics and Its Impact on National Park - Mudeungsan National Park - (국립공원 내 소리 분포 특성 분석 연구 - 무등산국립공원 -)

  • Yoo, Ji-su;Ryu, Hun-jae;Moon, Sung-joon;Chang, Seo-Il;Ki, Kyong-Seok
    • Korean Journal of Environment and Ecology
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    • v.36 no.3
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    • pp.350-357
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    • 2022
  • A national park is a place to conserve natural resources and visitors to experience nature, and thus, it is necessary to identify the noise distribution characteristic in the national park and preserve and restore the soundscape. However, most national parks in Korea are exposed to noise, leading to negative perceptions of the national park's soundscape and affecting the ecosystem. Many national parks in other countries have investigated the ecosystem impacts caused by noise and have performed various management to reduce the noise. However, in Korea, there is still a lack of awareness of the effect on the ecosystem, overlooking the need for soundscape management. Therefore, in this study, we developed a noise map of Mudeungsan National Park to investigate the quantitative impact of noise on visitors and the ecosystem. Also, we measured the trail's soundscape to describe a sound grade classification, and the soundscape of main spots in the park was recorded for a year and then analyzed. Finally, the sound resource distribution map was described, which can be used as preliminary data to determine the national park's sound distribution characteristics and manage the soundscape.

A study on the evolution of post-smartphone technologies in the 5G technology environment

  • Kwak, Jeong Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.4
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    • pp.1757-1772
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    • 2020
  • As the smartphone market becomes saturated, an innovative device equipped with new features is expected to appear soon in mobile communications. In particular, various possibilities were raised regarding the alternative technologies that can develop post-smartphones, which are differentiated from the current smartphones, as Korea commercialized the 5G infrastructure for the first time in the world. Under these circumstances, the Korean government announced the "5G+ Strategy for Realizing Innovative Growth" in April 2019, vowing to build an innovative industrial ecosystem quickly while creating various convergence services based on the 5G infrastructure. As described above, the policy importance of the alternative technologies that will develop post-smartphones is increasing, but the theoretical study on the technology evolution of post-smartphones has not been systematically conducted until now. This study reviewed the alternative technologies that can develop post-smartphones through documentary research, and data mining analysis was performed on the research result using actual data. The policy priority was also set quantitatively for the alternative technologies of post-smartphones in order to determine the alternative post-smartphone technology that the government should focus on given the constraint of limited resources. As a results, autonomous vehicle(43.68%) was found to be most important, followed by artificial intelligence(17.4%) and Internet of Things(13.1%), among alternative technologies that could develop into the post-smartphone.

A Study on Disaster Safety Management Policy Using the 4th Industrial Revolution and ICBMS (4차 산업혁명과 ICBMS를 활용한 재난안전관리에 관한 연구)

  • Kang, Heau-Jo
    • Journal of Digital Contents Society
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    • v.18 no.6
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    • pp.1213-1216
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    • 2017
  • Recently due to the increasing uncertainty of the disaster environment caused by climate change the effects of disasters have become larger due to the confluence and solidification diversification into disaster type and secondary damage. In this paper, we apply ICBMS through intelligent information technology and big data analysis to all processes of disaster safety management to minimize human, social, economic and environment damage from accidents or disasters, and prevention by control technology preparation by education and training expansion to remember by body, response by advanced technology of disaster response unmanned technology restoration by creation of local community environment ecosystem, investigation and analysis by intelligent information technology learn about disaster safety management 4.0. In addition, technical limitation and problems in the $4^{th}$ industrial revolution and the application of big data were analyzed and suggested alternatives and strategies to overcome.

Blockchain based SDN multicontroller framework for Secure Sat_IoT networks (안전한 위성-IoT 네트워크를 위한 블록체인 기반 SDN 분산 컨트롤러 구현)

  • June Beom Park;Jong Sou Park
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.141-148
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    • 2023
  • Recent advancements in the integration of satellite technology and the Internet of Things (IoT) have led to the development of a sophisticated network ecosystem, capable of generating and utilizing vast amounts of big data across various sectors. However, this integrated network faces significant security challenges, primarily due to constraints like limited latency, low power requirements, and the incorporation of diverse heterogeneous devices. Addressing these security concerns, this paper explores the construction of a satellite-IoT network through the application of Software Defined Networking (SDN). While SDN offers numerous benefits, it also inherits certain inherent security vulnerabilities. To mitigate these issues, we propose a novel approach that incorporates blockchain technology within the SDN framework. This blockchain-based SDN environment enhances security through a distributed controller system, which also facilitates the authentication of IoT terminals and nodes. Our paper details the implementation plan for this system and discusses its validation through a series of tests. Looking forward, we aim to expand our research to include the convergence of artificial intelligence with satellite-IoT devices, exploring new avenues for leveraging the potential of big data in this context.

Designing a Platform Model for Building MyData Ecosystem (마이데이터 생태계 구축을 위한 플랫폼 모델 설계)

  • Kang, Nam-Gyu;Choi, Hee-Seok;Lee, Hye-Jin;Han, Sang-Jun;Lee, Seok-Hyoung
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.123-131
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    • 2021
  • The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.

History and Trends of Data Education in Korea - KISTI Data Education Based on 2001-2019 Statistics

  • Min, Jaehong;Han, Sunggeun;Ahn, Bu-young
    • Journal of Internet Computing and Services
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    • v.21 no.6
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    • pp.133-139
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    • 2020
  • Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI's data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees' interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.

Auto Configuration Module for Logstash in Elasticsearch Ecosystem

  • Ahmed, Hammad;Park, Yoosang;Choi, Jongsun;Choi, Jaeyoung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.39-42
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    • 2018
  • Log analysis and monitoring have a significant importance in most of the systems. Log management has core importance in applications like distributed applications, cloud based applications, and applications designed for big data. These applications produce a large number of log files which contain essential information. This information can be used for log analytics to understand the relevant patterns from varying log data. However, they need some tools for the purpose of parsing, storing, and visualizing log informations. "Elasticsearch, Logstash, and Kibana"(ELK Stack) is one of the most popular analyzing tools for log management. For the ingestion of log files configuration files have a key importance, as they cover all the services needed to input, process, and output the log files. However, creating configuration files is sometimes very complicated and time consuming in many applications as it requires domain expertise and manual creation. In this paper, an auto configuration module for Logstash is proposed which aims to auto generate the configuration files for Logstash. The primary purpose of this paper is to provide a mechanism, which can be used to auto generate the configuration files for corresponding log files in less time. The proposed module aims to provide an overall efficiency in the log management system.

Identification of Visitation Density and Critical Management Area Regarding Marine Spatial Planning: Applying Social Big Data (해양공간계획 수립을 위한 방문밀집도 및 중점관리지역 규명: 소셜 빅데이터를 활용하여)

  • Kim, Yoonjung;Kim, Choongki;Kim, Gangsun
    • Journal of Environmental Impact Assessment
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    • v.29 no.2
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    • pp.122-131
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    • 2020
  • Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.

Analyzing Global Startup Trends Using Google Trends Keyword Big Data Analysis: 2017~2022 (Google Trends 의 키워드 빅데이터 분석을 활용한 글로벌 스타트업 트렌드 분석: 2017~2022 )

  • Jaeeog Kim;Byunghoon Jeon
    • Journal of Platform Technology
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    • v.11 no.4
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    • pp.19-34
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    • 2023
  • In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated.

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