• Title/Summary/Keyword: 대용

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An Efficient Graph Cycle Detection Technique based on Pregel (프리겔 기반의 효율적인 그래프 순환 검출 기법)

  • Kim, Taeyeon;Kim, Hyunwook;Park, Kisung;Lee, Young-Koo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.152-154
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    • 2013
  • 페타 바이트 이상의 규모의 빅 데이터 분석은 다양한 분야에서 연구되고 있다. 최근 소셜 네트워크, XML 등과 같은 구조적인 정보를 갖는 대용량의 그래프들을 분석하는 기술이 활발히 연구되고 있다. 이러한 대용량의 그래프를 분석하기 위한 연산중의 하나로 순환 그래프가 사용되고 있다. 대용량의 그래프 환경에서 순환을 검출하는 연산은 단일 컴퓨팅 시스템에서 처리가 불가능하거나 많은 시간 비용이 발생하여 분산처리가 필요하다. 본 논문에서는 그래프 처리에 효율적인 프리겔 프레임워크를 이용하여 효율적으로 순환을 검출하고, 중복 순환을 제거하기 위해 정규 순환 코드를 제안한다. 실험을 통하여 제안하는 기법이 대용량 그래프에서 효율적으로 순환을 찾을 수 있음을 보인다.

Designing and building a DTN cluster based on massively scalable storage (대용량 스토리지 기반의 데이터 전송 노드 클러스터 설계 및 구축)

  • Hong, Wontaek;An, Dosik;Lee, Jaekook
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.05a
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    • pp.63-65
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    • 2020
  • 과학응용분야의 원활한 협업 지원을 위해서는 원거리간 대용량 연구데이터의 고속 전송이 반드시 요구된다. 이와 관련하여, 본 논문은 기 구축된 대용량 파일 시스템을 다수의 데이터 전송 노드(DTN)에 연동하기 위해 필요한 요구사항들을 정리하고, 이에 기반하여 DTN 클러스터를 설계하고 구축한 사례를 제시한다. 추가적으로, 종단간 왕복지연 시간이 약 130ms에 달하는 원거리 종단 포인트와 대용량 실험데이터를 송수신함으로써 구축된 결과물의 전송 성능을 측정하고 확인한다.

An Implementation of High Performance Transmission System for Large-scale Experimental Data (대용량 실험데이터 고속전송 시스템 구현)

  • Jin, Duseok
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.506-507
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    • 2021
  • 대용량 실험데이터를 생성하는 가속기, 전자현미경, 전파망원경 등과 같은 첨단 실험장비들의 기술적 발전으로, 생성되는 실험데이터의 규모가 폭발적으로 증가하고 있다. 이에 따라, 데이터 분석연구에 대용량 데이터의 저장이 가능하고, 데이터 분석에 필요한 고성능 계산 서버를 갖춘 전문 데이터센터의 활용이 증가하고 있다. 본 논문에서는 이러한 전문 데이터센터를 연계한 데이터 분석 연구환경구축에서 가장 기본이 되는 데이터수집을 위한 고성능 데이터 전송 시스템을 구현하고, 이를 적용한 사례를 통해 제안하는 시스템의 효율성을 검증한다.

전력용 반도체 소자

  • 한민구
    • 전기의세계
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    • v.34 no.3
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    • pp.141-144
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    • 1985
  • 다이리스터는 power semiconduct or device중에서 가장 광범위 또한 대용량의 전류와 전압을 취급할 수 있는 소자로써 널리이용되고 있다. 또한 silicon wafer의 크기가 증가하고 있기때문에 전류의 증가가 기대가 되고 있다. 그러나 MOSFEF의 power device의 응용이 증가되고 있으나 대용량의 전류와 전압의 조절분야에서는 다이리스터의 역할을 두드러질 것이다.

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BIM Geometry Cache Structure for Data Streaming with Large Volume (대용량 BIM 형상 데이터 스트리밍을 위한 캐쉬 구조)

  • Kang, Tae-Wook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.9
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    • pp.1-8
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    • 2017
  • The purpose of this study is to propose a cache structure for processing large-volume building information modeling (BIM) geometry data,whereit is difficult to allocate physical memory. As the number of BIM orders has increased in the public sector, it is becoming more common to visualize and calculate large-volume BIM geometry data. Design and review collaboration can require a lot of time to download large-volume BIM data through the network. If the BIM data exceeds the physical free-memory limit, visualization and geometry computation cannot be possible. In order to utilize large amounts of BIM data on insufficient physical memory or a low-bandwidth network, it is advantageous to cache only the data necessary for BIM geometry rendering and calculation time. Thisstudy proposes acache structure for efficiently rendering and calculating large-volume BIM geometry data where it is difficult to allocate enough physical memory.

Engineering Model Design and Implementation of Mass Memory Unit for STSAT-2 (과학기술위성 2호 대용량 메모리 유닛 시험모델 설계 및 구현)

  • Seo, In-Ho;Ryu, Chang-Wan;Nam, Myeong-Ryong;Bang, Hyo-Choong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.11
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    • pp.115-120
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    • 2005
  • This paper describes the design and implementation of engineering model(EM) of Mass Memory Unit(MMU) for Science and Technology Satellite 2(STSAT-2) and the results of integration test. The use of Field-Programmable Gate Array(FPGA) instead of using private electric parts makes a miniaturization and lightweight of MMU possible. 2Gbits Synchronous Dynamic Random Access Memory(SDRAM) module for mass memory is used to store payload and satellite status data. Moreover, file system is applied to manage them easily in the ground station. RS(207,187) code improves the tolerance with respect to Single Event Upset(SEU) induced in SDRAM. The simulator is manufactured to verify receiving performance of payload data.

High-Volume Data Processing using Complex Event Processing Engine in the Web of Next Generation (차세대 웹 환경에서 Complex Event Processing 엔진을 이용한 대용량데이터 처리)

  • Kang, Man-Mo;Koo, Ra-Rok;Lee, Dong-Hyung
    • Journal of KIISE:Databases
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    • v.37 no.6
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    • pp.300-307
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    • 2010
  • According to growth of web, data processing technology is developing. In the Web of next generation, high-speed or high-volume data processing technologies for various wire-wireless users, USN and RFID are developing too. In this paper, we propose a high-volume data processing technology using Complex Event Processing(CEP) engine. CEP is the technology to process complex events. CEP Engine is the following characteristics. First it collects a high-volume event(data). Secondly it analyses events. Finally it lets event connect to new actions. In other words, CEP engine collects, analyses, filters high-volume events. Also it extracts events using pattern-matching for registered events and new events. As the results extracted. We use it by an input event of other work, real-time response for demanded event and can trigger to database for only valid data.

RDFS Rule based Parallel Reasoning Scheme for Large-Scale Streaming Sensor Data (대용량 스트리밍 센서데이터 환경에서 RDFS 규칙기반 병렬추론 기법)

  • Kwon, SoonHyun;Park, Youngtack
    • Journal of KIISE
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    • v.41 no.9
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    • pp.686-698
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    • 2014
  • Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

A High Performance Transmission Method for Massively Delivering Multimedia Data in WMSN (무선 멀티미디어 센서 네트워크(WMSN) 환경에서 멀티미디어 데이터 전송을 위한 대용량 전송 기법에 대한 연구)

  • Lee, Jae-Ho;Eom, Doo-Seop
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37A no.11
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    • pp.903-917
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    • 2012
  • For transmitting sensed data, wireless sensor networks have been developed and researched for the improvement of energy efficiency, hence, many MAC protocols in WSN employ the duty cycle mechanism. Since the progressed development of the low power transceiver and processor let the high energy efficiency come true, the delivery of the multimedia data which occurs in area of sensor work should be needed to provide supplemental information. In this paper, we design a new scheme for massive transmission of large multimedia data where the duty cycle is used in contention based MAC protocol, for WMSN. The proposed scheme can be applied into the previous duty cycle mechanism because it provides two operation between normal operation and massive transmission operation. Measuring the buffer status of sender and the condition of current radio channel can be criteria for the decision of the above two operations. This paper shows the results of the experiment by performing the simulation. The target protocol of the experiment is X-MAC which is contention based MAC protocol for WSN. And two approaches, both X-MAC which operates only duty cycle and X-MAC which operates combined massive transmission scheme, are used for the comparative experiment.

Analysis and Evaluation of DBMS Bulk Data Loading Through Multi-tiered Architecture for Heterogeneous Systems (이기종 시스템에서 다층 구조를 통한 DBMS 대용량 데이터 로딩의 분석 및 평가)

  • Tan, Hee-Yuan;Lim, Hyo-Taek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.167-176
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    • 2010
  • Managing the growing number of data generated through various processes requires the aid of Database Management System (DBMS) to efficiently handle the huge amount of data. These data can be inserted into database m real time or in batch, that come from multiple sources, including those that are coming from inside and outside of a network. The insertion of large amount of data is commonly done through specific bulk loading or insertion function supplied by each individual DBMS. In this paper, we analyze and evaluate on handling data bulk loading for heterogeneous systems that is organised as multi-tiered architecture and compare the result of DBMS bulk loader against program insertion from a software development perspective. We propose a hybrid solution using staging database that can be easily deployed for enhancing bulk loading performance compared to insertion by application.