• Title/Summary/Keyword: Big Data Environment

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Design of Building Biomertic Big Data System using the Mi Band and MongoDB (Mi Band와 MongoDB를 사용한 생체정보 빅데이터 시스템의 설계)

  • Lee, Younghun;Kim, Yongil
    • Smart Media Journal
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    • v.5 no.4
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    • pp.124-130
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    • 2016
  • Big data technologies are increasing the need for big data in many areas of the world. Recently, the health care industry has become increasingly aware of the importance of disease and health care services, as it has become increasingly immune to prevention and health care. To do this, we need a Big data system to collect and analyze the personal biometric data. In this paper, we design the biometric big data system using low cost wearable device. We collect basic biometric data, such as heart rate, step count and physical activity from Mi Band, and store the collected biometric data into MongoDB. Based on the results of this study, it is possible to build a big data system that can be used in actual medical environment by using Hadoop etc. and to use it in real medical service in connection with various wearable devices for medical information.

A Design of Client BBS System for Secure HVA

  • Park, Jae-Kyung;Kim, Young-Ja
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.9
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    • pp.73-80
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    • 2018
  • In this paper, we propose a new type of client server environment to improve the architecture vulnerable to hacking in an existing client server environment. On the server side, move the existing Web server to the client side and This is a way for clients to communicate only the data they need and suggests a structure that completely blocks the web attack itself to the server. This can completely prevent a server from being hacked, spreading malicious code and hacking data on a server. It also presents a new paradigm that will not affect servers even if malware is infected with client PCs. This paper validates the proposed environment through BBS (Big Bad Stick) hardware in the form of USB on the client side. This study proof that secure services are provided through encryption communication with server-side security equipment, indicating that this study is a system with new security.

The Study on Strategy of National Information for Electronic Government of S. Korea with Public Data analysed by the Application of Scenario Planning (공공데이터를 활용한 국가정보화 전략연구 - 시나리오플래닝을 적용하여 -)

  • Lee, Sang-Yun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1259-1273
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    • 2012
  • As a society of knowledge and information has been developed rapidly, because of changing from web environment to ubiquitous environment, a lot of countries across the world as well as S. Korea for national information with electronic Government have a variety of changes with big data. So this study is about development for national information and e-government of S. Korea with public data as big data analysed by the application of scenario planning. And then this research focused on the strategy consulting of national information with e-Government of S. Korea for utilization of public data as big data analysed by the application of 'scenario planning' as a foresight method. As a result, the future policy for utilization of public data as big data for national information with electronic government of S. Korea is to further spur the development of technology for linked data with semantic web for 'understanding of machine' than 'understanding of man'.

An Analysis of Utilization on Virtualized Computing Resource for Hadoop and HBase based Big Data Processing Applications (Hadoop과 HBase 기반의 빅 데이터 처리 응용을 위한 가상 컴퓨팅 자원 이용률 분석)

  • Cho, Nayun;Ku, Mino;Kim, Baul;Xuhua, Rui;Min, Dugki
    • Journal of Information Technology and Architecture
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    • v.11 no.4
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    • pp.449-462
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    • 2014
  • In big data era, there are a number of considerable parts in processing systems for capturing, storing, and analyzing stored or streaming data. Unlike traditional data handling systems, a big data processing system needs to concern the characteristics (format, velocity, and volume) of being handled data in the system. In this situation, virtualized computing platform is an emerging platform for handling big data effectively, since virtualization technology enables to manage computing resources dynamically and elastically with minimum efforts. In this paper, we analyze resource utilization of virtualized computing resources to discover suitable deployment models in Apache Hadoop and HBase-based big data processing environment. Consequently, Task Tracker service shows high CPU utilization and high Disk I/O overhead during MapReduce phases. Moreover, HRegion service indicates high network resource consumption for transfer the traffic data from DataNode to Task Tracker. DataNode shows high memory resource utilization and Disk I/O overhead for reading stored data.

Cost-Effective MapReduce Processing in the Cloud (클라우드 환경에서의 비용 효율적인 맵리듀스 처리)

  • Ryu, Wooseok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.114-115
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    • 2018
  • This paper studies a mechanism for cost-effective analysis of big data in the cloud environment. Recently, as a storage of electronic medical records can be managed outside the hospital, there is a growing demand for cloud-based big data analysis in small-and-medium hospitals. This paper firstly analyze the Amazon Elastic MapReduce which is a popular cloud framework for big data analysis, and proposes a cost model for analyzing big data using Amazon EMR with less cost. Using the proposed model, the user can construct a cost-effective computing cluster, which maximize the effectiveness of the analysis per operational cost.

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BIG DATA ANALYSIS ROLE IN ADVANCING THE VARIOUS ACTIVITIES OF DIGITAL LIBRARIES: TAIBAH UNIVERSITY CASE STUDY- SAUDI ARABIA

  • Alotaibi, Saqar Moisan F
    • International Journal of Computer Science & Network Security
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    • v.21 no.8
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    • pp.297-307
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    • 2021
  • In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.

A Design of DBaaS-Based Collaboration System for Big Data Processing

  • Jung, Yean-Woo;Lee, Jong-Yong;Jung, Kye-Dong
    • International journal of advanced smart convergence
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    • v.5 no.2
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    • pp.59-65
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    • 2016
  • With the recent growth in cloud computing, big data processing and collaboration between businesses are emerging as new paradigms in the IT industry. In an environment where a large amount of data is generated in real time, such as SNS, big data processing techniques are useful in extracting the valid data. MapReduce is a good example of such a programming model used in big data extraction. With the growing collaboration between companies, problems of duplication and heterogeneity among data due to the integration of old and new information storage systems have arisen. These problems arise because of the differences in existing databases across the various companies. However, these problems can be negated by implementing the MapReduce technique. This paper proposes a collaboration system based on Database as a Service, or DBaaS, to solve problems in data integration for collaboration between companies. The proposed system can reduce the overhead in data integration, while being applied to structured and unstructured data.

Application Plan of Column-Family Stores in the Big Data Environment (빅데이터환경에서의 칼럼-패밀리 저장소 활용방안)

  • Park, Sungbum;Lee, Sangwon;Ahn, Hyunsup;Jung, In-Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.237-239
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    • 2013
  • Data so as to meet key values are preserved at Column-Family Stores such as Cassandra, HBase, Hypertable, and Amazon Simple DB in the Big Data environment. In this paper, with referring to Cassandra, we define column-family data stores and its structure. And then, we check out their characteristics such as consistency, transaction, availability, retrieval function (basic queries and advance queries) with CQL (Cassandra Query Language), and expandability. Also, we appropriate or inappropriate subjects for application of column-family stores.

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Utilization and Prospect of Big Data Analysis of Sports Contents (스포츠콘텐츠의 빅데이터 분석 활용과 전망)

  • Kang, Seungae
    • Convergence Security Journal
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    • v.19 no.1
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    • pp.121-126
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    • 2019
  • The big data utilization category in the sports field was mainly focused on the big data analysis to improve the competence of the athlete and the performance. Since then, 'big data technology' which collect and analyze more detailed and diverse data through the application of ICT technology such as IoT and AI has been applied. The use of big data of sports contents in future has value and possibility in the smart environment, but it is necessary to overcome the shortage and limitation of platform to manage and share sports contents. In order to solve such problems, it is important to change the perception of the companies or providers that provide sports contents and cultivate and secure professional personnel capable of providing sports contents. Also, it is necessary to implement policies to systematically manage and utilize big data poured from sports contents.

Big Data and Personal Information: Needs for Regulatory Change (빅데이터와 개인정보: 규제변화의 필요성)

  • Lee, Ho-Sun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.12
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    • pp.1565-1570
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    • 2019
  • Many possibilities of Big Data has been discussed widely for several years. And the importance of protecting personal information has been emphasized more strongly. During the process of integrating several personal information for the improvement of usability of Big Data, there are many problems occured like the likelihood of the identification of one person, the level of personal infomation used to create personalized services in the companies making and using Big Data. In this study, I summarize GDPR(General Data Protection Regulation) of EU, CCPA(California Consumer Privacy Act) of USA and domestic Big Data 3 Acts Amendment proposals. Also I discuss re-identifcation of de-identificated information, social costs of the usage agreement of personal information, possible problems in construction and combination of private and public big data, political suggestions about settlement of regulatory environment.