• International Journal of Computer Science & Network Security
• /
• 제22권2호
• /
• pp.290-296
• /
• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• Journal of Information Processing Systems
• /
• 제17권6호
• /
• pp.1035-1043
• /
• 2021

An Internet of Things (IOT) sensor network is an effective solution for monitoring environmental conditions. However, IOT sensor networks generate massive data such that the abilities of massive data storage, processing, and query become technical challenges. To solve the problem, a Hadoop cloud platform is proposed. Using the time and workload genetic algorithm (TWLGA), the data processing platform enables the work of one node to be shared with other nodes, which not only raises efficiency of one single node but also provides the compatibility support to reduce the possible risk of software and hardware. In this experiment, a Hadoop cluster platform with TWLGA scheduling algorithm is developed, and the performance of the platform is tested. The results show that the Hadoop cloud platform is suitable for big data processing requirements of IOT sensor networks.

• Spatial Information Research
• /
• 제23권3호
• /
• pp.55-65
• /
• 2015

현대도시와 환경에서 발생하는 여러 종류의 사회문제를 해결하기 위한 목적으로 다양한 정보를 처리하고 운영하는 U-City 통합플랫폼이 도입되었다. 시간이 지나감에 따라 더 많은 자료를 처리해야 하는 어려움과 더불어 제한된 자원으로 적시의 필요한 정보를 찾는 사용자들의 요구를 만족시켜야 하는 어려움에 직면하게 되었다. 플랫폼의 운영비가 더 증가하면 할수록, 이를 유지하고 지속적인 투자를 해야 하는가에 대한 우려가 거세졌다. 이에 우리는 기존의 플랫폼의 한계점을 집어보고, 새로운 요구가 무엇인지 분석하고 기능 등을 개선하고자 하는 항목을 도출하였다. 이를 위해, 대용량 데이터를 처리할 수 있는 새로운 기술을 적용하였으며 전산환경의 기반을 제시하였다. U-City 통합플랫폼의 고도화로 비용절감의 효과와 편익 증가를 기대한다.

• 한국BIM학회 논문집
• /
• 제9권4호
• /
• pp.62-74
• /
• 2019

Because the existing BIM platform is based on user services, the focus is on the development of SaaS (Software as a Service), which provides business services online. However, since a harbor is a security facility, the harbor BIM platform is preferably provided in a private form, rather than relying on the infrastructure environment provided by external cloud providers. Therefore, this study analyzes and reviews the main functions to be provided as SaaS services of the harbor BIM platform. The goal is to build a cloud-based harbor BIM platform that can provide this service to users. To this end, we built IaaS (Infrastructure as a Service) environment of the harbor BIM platform based on the open source Open Stack and integrate and develop PaaS environment with Open Shift applied with IaaS. We applied the GPU to the harbor BIM platform to verify the performance of the harbor BIM platform, and found that the rendering and loading times are improved. In particular, it is expected to reduce the cost of introduction and provide it as the basic cloud environment of similar BIM platform for infrastructure facilities.

• 전기학회논문지
• /
• 제58권7호
• /
• pp.1424-1434
• /
• 2009

DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권5호
• /
• pp.1998-2014
• /
• 2016

In recent years, cloud computing services based on smart phones and other mobile terminals have been a rapid development. Cloud computing has the advantages of mass storage capacity and high-speed computing power, and it can meet the needs of different types of users, and under the background, mobile cloud computing (MCC) is now booming. In this paper, we have put forward a new classification-based virtual machine placement (CBVMP) algorithm for MCC, and it aims at improving the efficiency of virtual machine (VM) allocation and the disequilibrium utilization of underlying physical resources in large cloud data center. By simulation experiments based on CloudSim cloud platform, the experimental results show that the new algorithm can improve the efficiency of the VM placement and the utilization rate of underlying physical resources.

• Journal of Information Processing Systems
• /
• 제19권4호
• /
• pp.450-464
• /
• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• 대한공업교육학회지
• /
• 제41권2호
• /
• pp.89-118
• /
• 2016

본 연구의 목적은 피지컬 컴퓨팅 플랫폼인 아두이노와 앱 인벤터를 대한민국의 자랑스런 전통 과학기술의 유산이자 세계 최초의 돌격용 철갑전선(鐵甲戰船)으로 평가되는 거북선의 모형과 융합하여, 공업계열 특성화고 학생들이 실제적인 경험을 통해 과학기술적인 지식뿐만 아니라, 그와 더불어 역사 문화유산에 대한 인식과 가치 또한 제고해 볼 수 있는 피지컬 컴퓨팅 플랫폼 기반의 모형 거북선을 개발하는데 있다. 이 연구를 통하여 얻은 결론은 다음과 같다. 첫째, 아두이노 기반의 메인 컨트롤러 설계 및 제작은 전기 전자 제어와 관련된 하드웨어 및 소프트웨어 지식을 익히고, 아두이노와 전기전자 부품간의 기본적인 상호특성과 성능을 확인하는데 도움이 된다. 둘째, 회로도 및 패턴도 설계, 기술적 프로그래밍, 모바일 앱 개발 등의 과정을 통해 회로 설계 능력, 논리적 사고력과 문제해결력을 향상시키는데 효율적이다. 셋째, 피지컬 컴퓨팅 플랫폼 기반의 모형 거북선 개발을 통해 과학기술과 인문학적 소양을 통합적으로 함양할 수 있는 기초적인 토대를 마련하였다.

• 한국산업정보학회논문지
• /
• 제19권5호
• /
• pp.117-128
• /
• 2014

본 연구에서는 최근 정부의 중소기업 정보화지원이 플랫폼기반의 클라우드 방식으로 변화함에 따라, 정부의 지원 기대효과를 극대화하기 위해서는 장기적 비전 수립과 목표 시스템 아키텍처 설계 및 효과적 실행 관리체계에 대한 정책적 필요사안을 제시하였다. 이를 위하여 본 연구에서는 우선적으로 중소기업 정보화 현황과 기존 중소기업 정보화지원 방식에 대한 한계점을 분석하고, 클라우드 컴퓨팅 등 신기술동향을 바탕으로 정부가 중소기업의 정보화와 관련하여 어떠한 역할을 해야 하는 가에 대한 미션과 범위를 도출하였다. 이를 바탕으로 중장기 비전을 도출하였으며 목표 시스템 아키텍처를 소상공인기업과 소기업 등 클라우드 서비스 무상 지원 영역등을 포함하여 설계하였다. 본 연구의 공헌점은 기존의 기업중심 정보전략 연구를 정보화지원전략으로 확장하였다는 데 있으며, 본 연구에서 도출된 정책적 시사점은 중기청에서 추진 중인 중소기업 정보화지원사업에 기본적 가이드라인으로, 그리고 정부의 다른 정보화지원 사업에 활용될 수 있다.

• 전자통신동향분석
• /
• 제35권7호
• /
• pp.36-45
• /
• 2020

The method and process of research and development (R&D) is changing when we develop artificial intelligence (AI), and the way R&D results are dispersed is also changing. For the R&D process, using and participating in open-source ecosystems has become more important, so we need to be prepared for open source. For product and service development, a combination of AI algorithm, data, and computing power is needed. In this paper, we introduce ETRI AI Strategy #4, "Expanding AI Open Platform." It consists of two key tasks: one to build an AI open source platform (OSP) to create a cooperative AI R&D ecosystem, and another to systematize the "x+AI" open platform (XOP) to disperse AI technologies into the ecosystem.