• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.265-281
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• 2019

With the advent of the Internet-based economy, the dramatic changes in consumption patterns have been witnessed during the last decades. The seminal change has led by Data Technology, the integrated platform of mobile, online, offline and artificial intelligence, which remained unchallenged. In this paper, I use data analysis tool (TexTom) in order to articulate the definitfite notion of data technology from Internet sources. The data source is collected for last three years (November 2015 ~ November 2018) from Google and Naver. And I have derived several key keywords related to 'Data Technology'. As a result, it was found that the key keyword technologies of Big Data, O2O (Offline-to-Online), AI, IoT (Internet of things), and cloud computing are related to Data Technology. The results of this study can be used as useful information that can be referred to when the Data Technology age comes.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.174-175
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• 2017

최근 모바일 디바이스 대상 애플리케이션이 급속도로 성장하며 모바일 컴퓨팅과 클라우드 컴퓨팅을 결합한 모바일 클라우드 컴퓨팅의 패러다임이 확산되고 있다. 한편 사물인터넷이 확산되며 다양한 센서 데이터를 수집할 수 있는 사물인터넷 디바이스를 통한 클라우드 컴퓨팅의 필요성이 증가하고 있다. 이러한 IoT 디바이스는 적지 않은 컴퓨팅 성능을 가지고 있음에도 불구하고 대부분 비교적 저수준의 컴퓨팅을 수행하거나 많은 시간을 유휴 리소스의 형태로 낭비하고 있는 실정이다. 본 논문에서는 IoT 디바이스의 리소스를 통합해 모바일 클라우드 컴퓨팅 인프라의 구축 및 운영을 위한 스킴 IDRIS(IoT device's Resource Integration Scheme)를 제안한다. IDRIS는 IoT 디바이스를 통해 수집한 센서 데이터의 처리를 외부 클라우드의 원격 서버가 아닌 사용자가 구성한 개인 모바일 클라우드를 통해 컴퓨팅을 수행할 수 있도록 하는 스킴을 제공한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1110-1116
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• 2015

This paper analyzes global research trend on information security. All technical fields based on information requires security so that discovering technologies (technical terms) which are developing newly or dramatically is able to guide the future direction of the field of information security. In this paper, the ultimate of this research is to figure out the technologies related to information security and to forecast the future through understanding their trends. The paper, as a beginning for the analysis on macroscopic viewpoint, contains measurement of yearly relatedness between technical terms from 2001 to 2014 by using temporal co-occurrence and interpretation of its meaning through comparing the relatedness with trends of top-related technical terms. And to conclude, we could find that Android platform, Big data, Internet of things, Mobile technologies, and Cloud computing are emerging technologies on information security.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.8-15
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• 2012

In this paper, we propose a new monitor for collecting job information from Hadoop clusters in real time. This monitor is made of two programs called Collector and Agent. Agent collects Hadoop cluster's node information and job information, and Collector analyzes the collected information and saves it in a database. Also, Collector was placed in a new node outside the Hadoop cluster so that it does not affect Hadoop's work and will not cause overload. When the proposed monitor was implemented and applied, the testbed cluster was able to detect the occurrence of dead nodes immediately. In addition, we were able to find Hadoop jobs which were inefficient and when we modified such jobs to further enhance the performance of Hadoop.

• Journal of Digital Contents Society
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• v.14 no.3
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• pp.313-321
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• 2013

In recent, proliferation of mobile smart devices have led to big-data era, the importance of location-based services is increasing due to the exponential growth of trajectory related data. In order to process trajectory data, parallel processing platforms such as cloud computing and MapReduce are necessary. Currently, the researches based on MapReduce are on progress, but due to the MapReduce's properties in using batch processing and simple key-value structure, applying MapReduce framework for real time LBS is difficult. Therefore, in this research we propose a suitable system design on efficient indexing and search techniques for real time service based on detailed analysis on the properties of MapReduce.

• The Research Journal of the Costume Culture
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• v.22 no.2
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• pp.313-325
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• 2014

This study seeks to establish a ubiquitous wardrobe with a clothing management function through detailed and subdivided integration research. To create a database, a survey was conducted, and the output data were analyzed and used as the basic data. In particular, this study researched clothing management programs and companies' standards of clothing product classification systems. First, through an in-depth analysis centering on specialists, we established the contents of a ubiquitous wardrobe and used the concept of cloud computing to support the wardrobe contents and smart phone applications. Second, this research found significant differences between individuals, schools, and enterprises in their applications of, and the importance they attach to, design images. A detailed database composed of various categories was established to present the ubiquitous wardrobe contents with efficient functions. Third, we facilitated the search process by designating clothes with QR codes, which is one of the functions of contents. Fourth, the code numbers generated in the process of entering clothes into the database were utilized as RFID information as a way to arrange the products in a simpler manner. The ubiquitous wardrobe was constructed as a web-style hybrid, and its contents areavailable through mobile applications and QR codes.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.181-182
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• 2014

본 논문에서는 현시대의 핵심이슈인 신속성과 유용성에 맞춘 갤러리 카테고라이징 어플리케이션(이하 앱)을 제안한다. 해당 앱은 기존에 모바일 기기에 내재된 갤러리 시스템의 여러 가지 단점들을 파악하여 사용자에게 방대한 양의 사진 파일들을 보다 효율적으로 관리할 수 있는 환경을 제공한다. 또한 외부의 서버를 개인 메모리 공간처럼 사용하는 일종의 클라우드 컴퓨팅 기술을 사용하여 모바일 사진 파일을 동기화한다. 이를 통해 비디오, 음악 등 모바일에서 다루는 고용량의 파일들과 수많은 응용프로그램으로부터 요구되는 메모리 공간으로 인한 모바일 기기의 용량 부족 현상을 완화하고, 모바일 기기의 한정적인 메모리 공간을 보완한다. 시뮬레이션을 통하여 제안하는 갤러리 카테고라이징 기법이 기존의 사용하는 갤러리 시스템에 비해 사진 탐색시간의 효율 면에서 우수함을 확인하였다.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.357-363
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• 2017

The Linux operating system, considered to be a subset of the UNIX operating system, is becoming the backbone of the enterprise server market and is seen as the key to building cloud computing and big data infrastructures. Linux has a variety of Linux distributions due to the fact that the source is open and anyone can freely modify and distribute it. First of all, Linux dominated the server market, the emergence of various distributions dominates the desktop and mobile operating system markets. In this paper, we examine the birth and history of Linux and classify and characterize various Linux distributions. The emergence of various Linux distributions will play a pivotal role in the Internet of Things and will further expand their power.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5465-5480
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• 2018

Energy-efficient task scheduling on multi-core server is a fundamental issue in green cloud computing. Multi-core processors are widely used in mobile devices, personal computers, and servers. Existing energy efficient task scheduling methods chiefly focus on reducing the energy consumption of the processor itself, and assume that the cores of the processor are controlled independently. However, the cores of some processors in the market are divided into several voltage islands, in each of which the cores must operate on the same status, and the cost of the server includes not only energy cost of the processor but also the energy of other components of the server and the cost of user waiting time. In this paper, we propose a cost-aware scheduling algorithm ICAS for computation intensive tasks on multi-core server. Tasks are first allocated to cores, and optimal frequency of each core is computed, and the frequency of each voltage island is finally determined. The experiments' results show the cost of ICAS is much lower than the existing method.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.