• 전자통신동향분석
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• 제35권6호
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• pp.78-87
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• 2020

With the evolution of the Internet of Things (IoT), a computing paradigm shift from cloud to edge computing is rapidly taking place to effectively manage the rapidly increasing volume of data generated by various IoT devices. Edge computing is computing that occurs at or near the physical location of a user or data source. Placing computing services closer to these locations allows users to benefit from faster and more reliable services, and enterprises can take advantage of the flexibility of hybrid cloud computing. This paper describes the concept and main benefits of edge computing and presents the trends and future prospects for edge computing technology.

• 한국통신학회:학술대회논문집
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• 한국통신학회 2006년도 하계종합학술발표회 논문 초록집
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• pp.416-416
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• 2006

• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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• pp.37-61
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• 2016

Purpose This study examines firms at various industries to identify key organizational characteristics that positively drive the evaluation of cloud computing. In addition, this study tests the impact of one's evaluation has on the adoption and integration of cloud computing within their respective firm. Design/methodology/approach A total of 172 responses from various firms currently using cloud computing service were analyzed using the structural equation modeling(SEM). Findings Results show that organizational Needs(Mobility and Job Relevance), Perceived Factors(Relative Advantages and Cost Savings), and Organizational Readiness(Technical Knowledge, Financial Supports, and Managerial Supports) have a significant impact on cloud computing evaluation; and evaluation influences its adoption, and integration. However, two variables(IT Performance Gaps and Compatibility) have no significant impact on cloud computing evaluation. Finally, Evolutional Leadership has a significant moderating effect within the relationship among variables in the process of cloud computing implementation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.287-289
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• 2009

The conventional computing is a centralizing system, but it has been gradually going to develop ubiquitous computing which moves roles away from the main. The Community Computing, a new paradigm, is proposed to implement environment of ubiquitous computing. In this environment, it is important to accept the user demand. Hence in this paper recognizes pattern of user's activity statistically and proposes a method of pattern estimation in community computing. In addition, user's activity varies with time and the activity has the priority We reflect these. Also, we improve accuracy of the method through Knowledge Base organization and the feedback system. We make program using Microsoft Visual C++ for evaluating performance of proposed method, then simulate it. We can confirm it from the experiment result that using proposal method is better in environment of community computing.

• 대한임베디드공학회논문지
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• 제16권6호
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• pp.259-266
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• 2021

Edge Computing enables real-time big data processing by performing computing close to the physical location of the user or data source. However, in an edge computing environment, various situations that affect big data processing performance may occur depending on temporary service requirements or changes of physical resources in the field. In this paper, we proposed a BigCrawler system that dynamically configures the computing module and storage module according to the big data collection status and computing resource usage status in the edge computing environment. And the feature of big data processing workload according to the arrangement of computing module and storage module were analyzed.

• 전자통신동향분석
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• 제34권2호
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• pp.51-59
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• 2019

Edge computing, which is computing on the edge of the network, is becoming a market value as a means of overcoming the fear of communication disconnection and delay reduction, which are the technical weaknesses of cloud computing. Edge computing is continuously expanding applications in various applications such as safety industry, smart factories, autonomous vehicles, mobile communications, and AR/VR. Looking at edge computing trends from Microsoft, IBM, HPE, and Dell EMC, current edge computing must be understood as an integral binding technology and not as a simple complement to the cloud. This paper examines market trends in edge computing and analyzes the impact of edge computing on major related industries.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.

• Journal of Information Technology Applications and Management
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• 제12권4호
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• pp.173-195
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• 2005

As the amount of informatization investment is rapidly increasing in many organizations, it becomes more inevitable to manage computing resources (information systems, computing facilities and manpower etc.) effectively. Specially, in public sector It is thought to be very important to achieve the economy of scale by integrating computing resources which are managed individually in many agencies. Also, our government have been recently making much efforts to raise the effectiveness of operating the information systems by promoting joint information use among many public agencies, enhancing the operating systems and the expertise of IS staff and applying the optimal information security systems. This study focuses on presenting the framework to effectively integrate omputing resources and proposing the ways of constructing and operating the integrated computing environment for the institutions and the affiliated groups under the Ministry of Culture & Tourism which are in charge of implementing cultural informatization. The main implications of this study are 1) building the ideal model of the integrated computing environment architecture suitable to cultural informatization area, 2) showing the criteria of deciding whether the organizations use the Integrated computing environment or not and how extensively they commit their computing resources to it, and 3) suggesting the ways of the phased integration and the change management to minimize confusion in the process of adopting the integrated computing environment and behavioral problems such as conflict and resistance of IS-related Personnel Influenced by Implementing the integrated computing environment.

• 한국컴퓨터정보학회논문지
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• 제9권4호
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• pp.221-231
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• 2004

유비쿼터스 컴퓨팅이란 마크 와이저의 주장처럼 급진적이지 않으며 포괄적으로 유비쿼터스 컴퓨팅을 정의할 수 있는 적절한 정의로 판단된다. 각국의 실태에서 미국이나 유럽에서 실시되고 있는 프로젝트는 전반적으로 유비퀴터스 컴퓨팅 인프라 구축을 위한 연구와 사물의 지능화, 인간-컴퓨터 상호작용 연구, 공간의 지능화 등을 목표로 반면 일본은 어디서나 컴퓨터의 능력이 발휘되는 네트워크의 편재화를 위한 연구가 중심을 이룬다. 유비퀴터스 컴퓨팅 연구는 컴퓨터 과학의 특정 분야에 국한된 것이 아니라 사회, 경제, 윤리, 법 등 다양한 측면에서 연구되고 있으며, 국가의 적극적 지원을 기반으로 한다. 유비쿼터스 컴퓨팅이 다양한 센서를 통해 정보를 받아들이고, 판단하며, 커뮤니케이션 기술을 등을 제시하였다. 이를 근거로 유비쿼터스 컴퓨팅의 발전모델을 제시하였으며 진화과정에서 정형화된 가치시스템에 한계가 있으나 5가지 유형의 비즈니스모델이 나타날 것으로 전망한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 춘계학술발표대회
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• pp.499-502
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• 2012

빅 데이터 분석의 시대가 도래하면서 대용량 데이터의 특성과 계산 집약적 연산의 특성을 동시에 가지는 문제 해결에 대한 요구가 늘어나고 있다. 대용량 데이터 처리의 경우 각종 분산 파일 시스템과 분산/병렬 컴퓨팅 기술들이 이미 많이 사용되고 있으며, 계산 집약적 연산 처리의 경우에도 GPGPU 활용 기술의 발달로 보편화되는 추세에 있다. 하지만 대용량 데이터와 계산 집약적 연산 이 두 가지 특성을 모두 가지는 문제를 처리하기 위해서는 많은 제약 사항들을 해결해야 하는데, 본 논문에서는 이에 대한 대안으로 분산 컴퓨팅 프레임워크인 Hadoop MapReduce와 Nvidia의 GPU 병렬 컴퓨팅 아키텍처인 CUDA 흘 연동하는 방안을 제시하고, 이를 밀집행렬(dense matrix) 연산에 적용했을 때 얻을 수 있는 성능 개선 효과에 대해 소개하고자 한다.