• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.716-717
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• 2017

In this paper, we propose a modeling approach for marine environment monitoring by leveraging open-source software to link IoT and Cloud together. The proposed model can be scale out by employing Apache Hadoop-based time-series database so that it can handle collected data increase with a resource pool of the same computers. It can also support the analyze monitored data of marine environment by visualizing collected data.

• Smart Media Journal
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• v.6 no.3
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• pp.75-82
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• 2017

Recently, the marine monitoring technology is actively being studied since the sea is a rich repository of natural resources that is taken notice in the world. In particular, the marine environment data should be collected continuously in order to understand and analyze the marine environment, however the study of automatic monitoring of marine environment in Korea is not enough. In this paper, we proposed the marine environment monitoring system based on open source. The proposed system can be designed as a scale out system using Hadoop based time series database which it can easily process the increasing collection data by a scale out computer resources. It can also be used to analyze marine data by visualizing collected data.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.11-21
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• 2013

Recently operating a large scale computing resource like a data center becomes easier because of the virtualization technology that virtualize servers and enable flexible resource provision. The most of public cloud services provides automatic scaling in the form of scale-in or scale-out and these scaling approaches works well to satisfy the service level agreement (SLA) of users. However, a novel scaling approach is required to operate private clouds that has smaller amount of computing resources than vast resources of public clouds. In this paper, we propose a hybrid server scaling architecture and related algorithms using both scale-in and scale-out to achieve higher resource utilization rate for private clouds. We uses dynamic resource allocation and live migration to run our proposed algorithm. Our propose system aims to provide a fine-grain resource scaling by steps. Thus private cloud systems are able to keep stable service and to reduce server management cost by optimizing server utilization. The experiment results show that our proposed approach performs better in resource utilization than the scale-out approach based on the number of users.

• Proceedings of the Materials Research Society of Korea Conference
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• 2003.11a
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• pp.40-40
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• 2003

최근 나노기술의 발달과 더불어 나노재료에 대한 특성평가 요구가 높아지고 있고, 따라서 나노스케일에서 재료의 기계적 거동을 분석할 수 있는 나노인덴테이션 기법이 심도있게 연구되고 있다. 본 연구에서는 나노인덴테이션, 주사탐침현미경(SPM), 투과전자현미경(TEM) 기법을 이용하여 여러가지 재료의 탄성 소성 변형 거동과 팝인/괍아웃 현상을 조사하고 해석하였다. 나노인덴테이션 기법으로는 50 마이크로뉴턴 (5 mg) 이하의 매우 작은 하중 하에서는 접촉 응력조건이라도 인장시험에서 관찰되는 영구변형이 제로인 완전탄성 변형 거동을 관찰할 수 있었다. 또한, 50-250 마이크로 뉴턴의 하중 범위에서 재료는 탄성변형 이후에 갑작스런 항복거동과 더불어 수십-수백 나노미터를 미끌어지듯 변형하는 팝인(pop-in), 또는 탈선(excursion) 현상을 관찰할 수 있었다. 이 현상은 하중을 가하는 동안에 여러 번 발생하였으며 재료의 표면상태와 전위밀도와 밀접한 상관관계를 보였다. 반복 압입 시험에서는 전형적인 가공경화 현상으로 항복점이 높아지고 새로운 항복점 이후에야 다시 팝인 발생함을 보였다. 한편, 하중을 가할 때 발생하는 팝인과는 달리 하중을 제거할 때 급격히 회복하는 팝아웃 현상 또한 관찰되었다.

• Electronics and Telecommunications Trends
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• v.31 no.4
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• pp.44-54
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• 2016

클라우드 스토리지에 대한 수요가 증가하면서 전 세계적으로 수십 페타바이트까지 지원 가능한 구축 사례들이 점점 늘어나고 있다. 그러나 소셜, 모바일, IoT와 같이 클라우드 스토리지를 이용하는 데이터가 기하급수적으로 증가하면서 2020년경에는 엑사바이트 시대에 진입할 것으로 예상되고 있다. 이처럼 급증하는 클라우드 환경에서의 데이터를 수용하기 위해서는 보다 고용량의 클라우드 스토리지 구축에 대한 필요성이 대두되고 있는 상황이다. 본고에서는 클라우드 환경에서 효율적인 스케일-아웃 방식의 클라우드 스토리지와 관련한 기술동향을 살펴보고 스토리지의 고용량화를 위해 해결해야 할 기술적 이슈들이 무엇인지 분석한다.

• Smart Media Journal
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• v.8 no.4
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• pp.46-52
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• 2019

The size of data generated and collected at industrial sites or in public institutions is growing rapidly. The existing data processing server often handles the increasing data by increasing the performance by scaling up. However, in the big data era, when the speed of data generation is exploding, there is a limit to data processing with a conventional server. To overcome such limitations, a distributed cluster computing system has been introduced that distributes data in a scale-out manner. However, because distributed cluster computing systems distribute data, inefficient use of network bandwidth can degrade the performance of the cluster as a whole. In this paper, we propose a scheme that compresses data when transmitting data in a Hadoop cluster considering network bandwidth. The proposed scheme considers the network bandwidth and the characteristics of the compression algorithm and selects the optimal compression transmission scheme before transmission. Experimental results show that the proposed scheme reduces data transfer time and size.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.45-50
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• 2017

Micro-service Architecture is a service architecture optimized for large-scale distributed systems such as real-time realistic broadcasting systems, so that are fiercely adopted by Global leading service platform vendors such as Netflix and Twitter due to the merit of horizontal performance scalability enabling the scale-out technique. In addition, micro-service architecture makes it possible to execute image processing and real-time data analysis using an asynchronous-based processing that are difficult to handle in Web API such as REST. In this paper, an event stream processing framework applicable to asynchronous based micro services is proposed in the sense that the accountability of event processing order is not guaranteed in the events such as IoT sensor data analysis or cloud-based image editing because these are the situations where the real-time media editing generates multiple event streams and asynchronous processes in the platform.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.4
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• pp.15-26
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• 2008

The purpose of this study is to attempt to interpret golf courses as event-generating spaces with consideration given to the time factor. Through a golf game, a variety of events such as the tee shot, second shot, putt, and hole out are generated. These events have been connected to a series of events after hole out such as birdie, par, bogey and so on. The series of events do not always occur in the same way. They reveal unexpected changes over time. These unexpected changes cause changes in the spatial characteristics and offer unforgettable memories for golfers. Gilles Deleuze mentioned the spatial characteristics as striated space and smooth space. Striated space can be defined as sedentary space. It is distant vision-optical space that has dimensional, metric and centered characteristics, whereas smooth space is defined as nomadic, close vision-haptic space that has directional and acentered characteristics. This study focused on the analysis of spatial characteristics according to striated space and smooth space. Golf courses generally show the characteristics of striated space before beginning the game. As soon as the game begins, however, the golf courses are converted into an event-generating space. The characteristics of striated space are transformed into smooth space, a nomadic space that amplifies the dynamic, changeable, de-scaled and non-metric system. Through the whole game, this transformation is dramatically repeated. On the other hand, the golfer, the subject of the game, senses the phenomenological experience in the process of orientation, center, definition, and domestication.