• 제목/요약/키워드: Cloud Architecture

검색결과 369건 처리시간 0.025초

개인용 클라우드 컴퓨팅 사용에 미치는 영향요인 분석 (Analysis of Influence Factors on the Intention to Use Personal Cloud Computing)

  • 류재홍;문혜영;최진호
    • 한국IT서비스학회지
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    • 제12권4호
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    • pp.319-335
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    • 2013
  • Cloud computing allows users to access software or specific programs that support the cloud platform through an information communicating device that can connect to the internet anywhere or anytime. Also, the cloud architecture not only reduces the expenses of IT infrastructure construction and maintenance, but also speeds up processing and mobility, which leads to a significant ease of use. In spite of the advantages of cloud computing, previous studies have been centered on case studies of the execution, advantages, and problems of cloud computing. In contrast, empirical research on individual cloud computing up till now is very insufficient. Thus, the research aims to create a model of an individual user's perspective and verify validation. This study reveals types of influence that characteristics can have on an individual user's intention to use, by searching the characteristics that the individual user recognizes on cloud computing services. The results are as follows:first, the characteristics of cloud computing indicates a significant influence on usage intention. Second, all characteristics in cloud computing, accessibility, reliability, perceived ease of use, and fusibility, are confirmed in providing significant influences in shaping social influence forms. Third, social influence has a significant influence on usage intention.

MyData Cloud: 개인 정보 통제 강화를 위한 안전한 클라우드 아키텍쳐 설계 (MyData Cloud: Secure Cloud Architecture for Strengthened Control Over Personal Data)

  • 허승민;권용희;김범중;전기석;이중희
    • 정보보호학회논문지
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    • 제34권4호
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    • pp.597-613
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    • 2024
  • 마이데이터는 개인데이터 활용 체계의 새로운 패러다임으로, 데이터 주체가 자신의 데이터를 어떻게 사용하고 어디에 제공할 것인지 결정할 수 있다. 데이터 주체의 동의 하에 서비스 제공자는 여러 서비스에 걸쳐 흩어져있는 고객의 데이터를 수집하고 이를 바탕으로 고객 맞춤화된 서비스를 제공한다. 기존의 마이데이터 서비스 모델들에서, 데이터 주체는 데이터 스토리지에 저장된 자신의 개인 정보를 서비스 제공자 또는 제3자의 데이터 프로세서에게 판매할 수 있다. 하지만 개인정보가 한 번 제3자의 프로세서에게 판매되어 그들의 프로세서에 의해 처리될 경우 그 순간부터 데이터를 추적하고 통제할 수 없다는 문제가 발생한다. 따라서 본 논문에서는 기존 마이데이터 운영 모델들의 문제점들을 개선하여 데이터 주체에게 더 높은 통제권을 부여하는 클라우드 모델을 제시한다. 동시에, 클라우드 모델과 같이 데이터 스토리지, 컨트롤러, 프로세서가 모두 한 곳에 모여있는 경우 클라우드가 침해될 시 모든 데이터가 한 번에 침해될 수 있다는 점을 고려하여, 이러한 위험을 줄일 수 있도록 클라우드-디바이스 간 협력적 암호화와 클라우드 컴포넌트들 간 격리 기술을 적용한 클라우드 모델 아키텍쳐를 함께 제시한다.

RAS: Request Assignment Simulator for Cloud-Based Applications

  • Rajan, R. Arokia Paul;Francis, F. Sagayaraj
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권6호
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    • pp.2035-2049
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    • 2015
  • Applications deployed in cloud receive a huge volume of requests from geographically distributed users whose satisfaction with the cloud service is directly proportional to the efficiency with which the requests are handled. Assignment of user requests based on appropriate load balancing principles significantly improves the performance of such cloud-based applications. To study the behavior of such systems, there is a need for simulation tools that will help the designer to set a test bed and evaluate the performance of the system by experimenting with different load balancing principles. In this paper, a novel architecture for cloud called Request Assignment Simulator (RAS) is proposed. It is a customizable, visual tool that simulates the request assignment process based on load balancing principles with a set of parameters that impact resource utilization. This simulator will help to ascertain the best possible resource allocation technique by facilitating the designer to apply and test different load balancing principles for a given scenario.

차량 클라우드 환경에서 블룸 필터를 이용한 계층적 하이브리드 콘텐츠 전송 방법의 설계 및 평가 (Design and Evaluation of a Hierarchical Hybrid Content Delivery Scheme using Bloom Filter in Vehicular Cloud Environments)

  • 배인한
    • 한국멀티미디어학회논문지
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    • 제19권8호
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    • pp.1597-1608
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    • 2016
  • Recently, a number of solutions were proposed to address the challenges and issues of vehicular networks. Vehicular Cloud Computing (VCC) is one of the solutions. The vehicular cloud computing is a new hybrid technology that has a remarkable impact on traffic management and road safety by instantly using vehicular resources. In this paper, we study an important vehicular cloud service, content-based delivery, that allows future vehicular cloud applications to store, share and search data totally within the cloud. We design a VCC-based system architecture for efficient sharing of vehicular contents, and propose a Hierarchical Hybrid Content Delivery scheme using Bloom Filter (H2CDBF) for efficient vehicular content delivery in Vehicular Ad-hoc Networks (VANETs). The performance of the proposed H2CDBF is evaluated through an analytical model, and is compared to the proactive content discovery scheme, Bloom-Filter Routing (BFR).

멀티 브랜치 네트워크 구조 탐색을 사용한 구름 영역 분할 (Semantic Segmentation of Clouds Using Multi-Branch Neural Architecture Search)

  • 정치윤;문경덕;김무섭
    • 대한원격탐사학회지
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    • 제39권2호
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    • pp.143-156
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    • 2023
  • 인공위성이 촬영한 영상의 내용을 정확하게 분석하기 위해서는 영상에 존재하는 구름 영역을 정확하게 인지하는 것이 필요하다. 최근 다양한 분야에서 딥러닝(deep learning) 모델이 뛰어난 성능을 보여줌에 따라 구름 영역 검출을 위해 딥러닝 모델을 적용한 방법들이 많이 제안되고 있다. 하지만 현재 구름 영역 검출 방법들은 의미 영역 분할 방법의 네트워크 구조를 그대로 사용하여 구름 검출 성능을 향상하는 데는 한계가 있다. 따라서 본 논문에서는 구름 검출 데이터 세트에 다중 브랜치 네트워크 구조 탐색을 적용하여 구름 영역 검출에 최적화된 네트워크 모델을 생성함으로써 구름 검출 성능을 향상하는 방법을 제안한다. 또한 구름 검출 성능을 향상하기 위하여 의미 영역 분할 모델의 학습 단계와 평가 단계의 평가 기준 불일치를 해소하기 위해 제안된 soft intersection over union (IoU) 손실 함수를 사용하고, 다양한 데이터 증강 방법을 적용하여 학습 데이터를 증가시켰다. 본 논문에서 제안된 방법의 성능을 검증하기 위하여 아리랑위성 3/3A호에서 촬영한 영상으로 구성된 구름 검출 데이터 세트를 사용하였다. 먼저 제안 방법과 의미 영역 분할 데이터 세트에서 탐색된 기존 네트워크 모델의 성능을 비교하였다. 실험 결과, 제안 방법의 mean IoU는 68.5%이며, 기존 모델보다 mIoU 측면에서 4%의 높은 성능을 보여주었다. 또한 soft IoU 손실 함수를 포함한 다섯 개의 손실 함수를 적용하여 손실 함수에 따른 구름 검출 성능을 분석하였으며, 실험 결과 본 연구에서 사용한 soft IoU 함수가 가장 좋은 성능을 보여주었다. 마지막으로 의미 영역 분할 분야에서 활용되는 최신 네트워크 모델과 제안 방법의 구름 검출 성능을 비교하였다. 실험 결과, 제안 모델이 의미 영역 분할 분야의 최신 모델들보다 mIoU와 정확도 측면에서 더 나은 성능을 보여주는 것을 확인하였다.

Big Data Architecture Design for the Development of Hyper Live Map (HLM)

  • Moon, Sujung;Pyeon, Muwook;Bae, Sangwon;Lee, Dorim;Han, Sangwon
    • 한국측량학회지
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    • 제34권2호
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    • pp.207-215
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    • 2016
  • The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

딥러닝 기반 LNGC 화물창 스캐닝 점군 데이터의 비계 시스템 객체 탐지 및 후처리 (Object Detection and Post-processing of LNGC CCS Scaffolding System using 3D Point Cloud Based on Deep Learning)

  • 이동건;지승환;박본영
    • 대한조선학회논문집
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    • 제58권5호
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    • pp.303-313
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    • 2021
  • Recently, quality control of the Liquefied Natural Gas Carrier (LNGC) cargo hold and block-erection interference areas using 3D scanners have been performed, focusing on large shipyards and the international association of classification societies. In this study, as a part of the research on LNGC cargo hold quality management advancement, a study on deep-learning-based scaffolding system 3D point cloud object detection and post-processing were conducted using a LNGC cargo hold 3D point cloud. The scaffolding system point cloud object detection is based on the PointNet deep learning architecture that detects objects using point clouds, achieving 70% prediction accuracy. In addition, the possibility of improving the accuracy of object detection through parameter adjustment is confirmed, and the standard of Intersection over Union (IoU), an index for determining whether the object is the same, is achieved. To avoid the manual post-processing work, the object detection architecture allows automatic task performance and can achieve stable prediction accuracy through supplementation and improvement of learning data. In the future, an improved study will be conducted on not only the flat surface of the LNGC cargo hold but also complex systems such as curved surfaces, and the results are expected to be applicable in process progress automation rate monitoring and ship quality control.

멀티 클라우드 서비스 공통 플랫폼 설계 및 구현 (Design and Implementation of Multi-Cloud Service Common Platform)

  • 김수영;김병섭;손석호;서지훈;김윤곤;강동재
    • 한국멀티미디어학회논문지
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    • 제24권1호
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    • pp.75-94
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    • 2021
  • The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

An Efficient Log Data Processing Architecture for Internet Cloud Environments

  • Kim, Julie;Bahn, Hyokyung
    • International Journal of Internet, Broadcasting and Communication
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    • 제8권1호
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    • pp.33-41
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    • 2016
  • Big data management is becoming an increasingly important issue in both industry and academia of information science community today. One of the important categories of big data generated from software systems is log data. Log data is generally used for better services in various service providers and can also be used to improve system reliability. In this paper, we propose a novel big data management architecture specialized for log data. The proposed architecture provides a scalable log management system that consists of client and server side modules for efficient handling of log data. To support large and simultaneous log data from multiple clients, we adopt the Hadoop infrastructure in the server-side file system for storing and managing log data efficiently. We implement the proposed architecture to support various client environments and validate the efficiency through measurement studies. The results show that the proposed architecture performs better than the existing logging architecture by 42.8% on average. All components of the proposed architecture are implemented based on open source software and the developed prototypes are now publicly available.

Vehicular Cyber-Physical Systems for Smart Road Networks

  • 정재훈;이은석
    • 정보와 통신
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    • 제31권3호
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    • pp.103-116
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    • 2014
  • This paper proposes the design of Vehicular Cyber-Physical Systems (called VCPS) based on vehicular cloud for smart road networks. Our VCPS realizes mobile cloud computing services where vehicles themselves or mobile devices (e.g., smartphones and tablets of drivers or passengers in vehicles) play a role of both cloud server and cloud client in the vehicular cloud. First, this paper describes the architecture of vehicular networks for VCPS and the delay modeling for the event prediction and data delivery, such as a mobile node's travel delay along its navigation path and the packet delivery delay in vehicular networks. Second, the paper explains two VCPS applications as smart road services for the driving efficiency and safety through the vehicular cloud, such as interactive navigation and pedestrian protection. Last, the paper discusses further research issues for VCPS for smart road networks.