• Journal of Computing Science and Engineering
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• 제8권4호
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• pp.181-186
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• 2014

Web data mining aims at discovering useful knowledge from various Web resources. There is a growing trend among companies, organizations, and individuals alike of gathering information through Web data mining to utilize that information in their best interest. In science, cloud computing is a synonym for distributed computing over a network; cloud computing relies on the sharing of resources to achieve coherence and economies of scale, similar to a utility over a network, and means the ability to run a program or application on many connected computers at the same time. In this paper, we propose a new system framework based on the Hadoop platform to realize the collection of useful information of Web resources. The system framework is based on the Map/Reduce programming model of cloud computing. We propose a new data mining algorithm to be used in this system framework. Finally, we prove the feasibility of this approach by simulation experiment.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2007년도 International Conference
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• pp.357-362
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• 2007

This study presents a methodology that efficiently evaluates and interprets the end-user computing capability in a total perspective in a computing environment. The evaluation system has an evaluation tool, evaluation method and process, and an interpretation system. The validity and reliability of the developed tool construct was verified by factor and reliability analysis with the application of SPSS software. The application and utilization of the developed system was confirmed by applying it to evaluating the computing competency of 316 workers in an enterprise and presenting its evaluation results. This will contribute to developing a methodology for totally evaluating and interpreting the end-user computing capability and improving their computing capability in industrial fields.

• 한국산학기술학회논문지
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• 제12권3호
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• pp.1408-1416
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• 2011

클라우드 컴퓨팅은 컴퓨팅 리소스의 경비 절감과 효율은 물론 서비스의 확장 및 향상을 제공한다. 그러나 클라우드 서비스 사용자(기업 등)들은 클라우드 컴퓨팅 특성에 의한 여러 가지 위험들에 대해서 많은 염려를 갖고 있다. 본 논문에서는 클라우드 컴퓨팅 환경으로 인한, 시큐리티를 포함한 여러 가지 주요 이슈들을 검토하여 보고자 한다. 또한 시큐리티에 관한 문제들을 보다 구체적으로 분석하고 클라우드 컴퓨팅에 관한 위협들을 식별하여 시큐리티 위험을 줄일 수 있는 대략적인 대응책들을 제안하였다.

• 정보처리학회논문지A
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• 제11A권7호
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• pp.563-570
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• 2004

유비쿼터스 컴퓨팅 환경은 보안의 강화와 사생활 보호라는 과제를 안고 있다. 접근 제어는 보안 분야의 하나인데, 유비쿼터스 컴퓨팅 환경은 전통적인 정보시스템과는 여러 면에서 특성을 달리하기 때문에 기존의 접근제어 모델을 그대로 적용하기에는 무리가 있다. 본 연구에서는 접근제어 측면에서 유비쿼터스 컴퓨팅 환경을 정의하고 그 환경에서 접근제어의 특성을 분석한 뒤, 그 환경을 위한 접근제어 모델을 개발할 때 필수적으로 고려해야할 요구사항을 제시하였다. 또한 접근제어 모델의 구현시 가능한 세가지 유형에 대해서도 제시하였다.

• Journal of Computing Science and Engineering
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• 제6권4호
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• pp.280-286
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• 2012

The last decades have witnessed an increasingly indispensible role of high performance computing (HPC) in science, business and financial sectors, as well as military and national security areas. To introduce key aspects of HPC to a broader community, an HPC session was organized for the first time ever for the United States and Korea Conference (UKC) during 2012. This paper summarizes four invited talks that each covers scientific HPC applications, large-scale parallel file systems, administration/maintenance of supercomputers, and green technology towards building power efficient supercomputers of the next generation.

• 한국도서관정보학회지
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• 제43권1호
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• pp.241-259
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• 2012

본 연구의 목적은 최근 다양한 산업분야에서 도입되고 있는 클라우드 컴퓨팅서비스의 관련 문헌을 조사하여 개념과 유형, 적용 사례를 포괄적으로 분석한 후, 도서관 사서들을 대상으로 클라우드 컴퓨팅서비스에 대한 인식을 설문조사하여 그 결과를 기반으로 도서관에서 클라우드 컴퓨팅서비스를 적용할 때의 장점과 문제점, 적용에 적합한 도서관 업무 분야를 사서들의 설문 내용에 근거하여 도출하고, 클라우드 컴퓨팅서비스의 도서관 적용에서 핵심적으로 고려할 사항들을 제안하였다.

• Journal of Computing Science and Engineering
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• 제10권1호
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• Communications for Statistical Applications and Methods
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• 제11권2호
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• pp.287-295
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• 2004

Mark Weiser introduced ubiquitous computing in his article titled 'The computer for 21st Century' in 1991. This has been new paradigm after internet. Now, the rapid development of mobile computer, wireless network, and intelligent system has supported ubiquitous computing environment. In the related area of information science, the researchers have studied on ubiquitous computing. But in the field of Korea statistics, this research has not been worked yet. So, we proposed the connection between statistics and ubiquitous computing in this paper. As an example, we showed an efficient cache hoarding for ubiquitous computing using statistical methods. In experimental results, we verified our proposed issue.

• International Journal of Contents
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• 제8권4호
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.501-505
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• 2007

현재 기술 동향에 따라, 언제 어디서나 통신 및 컴퓨팅이 가능한 유비쿼터스 컴퓨팅 시스템(Ubiquitous Computing System)을 위해 사용자 및 주변 환경의 상황을 인식하는 기술(Context-Aware Computing System)이 필수적인 요소로 부각되고 있다. 하지만, Context-Aware Computing System을 구현하기 위해서 사용자 및 주변 환경으로부터 입력되는 불확실하거나 모호한 상황정보에 대한 표현과 추론에 대한 연구는 부족한 실정이다. 이를 해결하기 위해 Rule-based System을 기반으로 CRS와 DOS의 개념을 도입하여 상황인식 기술을 SoC로 구현할 수 있도록 새로운 Architecture를 제안한다. 마지막으로는 CRS와 DOS가 Network Topolgy에 적용된 RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol)의 예를 통해 그 효용성을 입증하고, Ubiquitous Computing System에서 활용 가능한 방법 등을 제시한다.