• 디지털융복합연구
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• 제15권11호
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• pp.147-153
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• 2017

한국 정부는 공공부문에 클라우드를 도입하기 위한 다양한 정책들을 시행하고 있다. 이 연구의 목적은 공공무문의 클라우드 도입을 위한 의사결정 모델을 개발하고 공공부문의 클라우드 도입 로드맵을 제안하는 것이다. 이를 위하여 공공서비스의 특성과 공공부문의 클라우드 서비스의 유형을 분석하였다. 이를 통해 공공부문의 클라우드 도입을 위한 요구사항을 파악하여, 퍼지 AHP기반의 융합의사결정 모델을 이용한 공공부문의 클라우드 도입방법을 개발하였다. 연구결과 클라우드 도입 후보군의 우선순위를 결정하였고, 이를 기반으로 단계별 클라우드 도입 로드맵을 제안하였다. 이 연구의 결과는 공공부문의 클라우드 도입과 전환 및 클라우드 정책 수립에 도움이 될 것으로 기대한다. 향후에는 클라우드 도입을 위한 추가적인 의사결정요인뿐만 아니라 예산계획을 개발하는 것이 필요하다.

• 정보화연구
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• 제10권4호
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• pp.509-516
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• 2013

클라우드 서비스는 낮은 비용과 높은 효율성으로 빠르게 변화하는 스마트사회에서 필수적인 IT인프라로 인식되고 있다. 구글, 아마존 등 해외 유수 기업에서 시작된 클라우드 서비스는 미국과 영국등 외국 정부의 클라우드 서비스 도입 정책에 다양한 영향을 끼쳤다. 특히, 이들 국가들은 정보자원의 효율적 관리를 위해서 클라우드 컴퓨팅의 도입과 아울러 기존 공공서비스의 클라우드 서비스로의 전환을 가속화하고 있다. 본 연구에서는 공공부문에서의 클라우드 서비스 도입을 위한 외국 정부의 다양한 사례 분석을 토대로 공공부문에서의 클라우드 도입시 주요 결정요인을 제시하고 공공부문에서 클라우드 도입 및 활용을 위한 클라우드 서비스 큐브 모델을 제안하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제31권2호
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• pp.63-88
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• 2022

Purpose The purpose of this study is to empirically analyze the factors affecting the intention to use cloud computing in the smart work environment. This study is meaningful in that it examines the characteristics of smart work and the fit of cloud computing characteristics, and it is a study that reveals the factors affecting the intention to use cloud computing by applying the integrated model of TTF and TAM. Design/methodology/approach In order to understand the factors affecting the intention to use cloud computing in the smart work environment, a research model that integrates TTF and TAM with the hypothesis was proposed. In order to verify the research hypothesis, this study conducted a survey on individuals with experience in smart work and cloud computing. And with the data 280 collected in the survey, path analysis was performed using the PLS structural equation. Findings As a result, it was found that task characteristics and technology characteristics had a positive (+) effect on task-skill fit, and task-skill fit had a positive (+) effect on perceived ease of use and usefulness. Also, task-skill fit, perceived ease of use, and perceived usefulness were found to have a positive (+) effect on intention to use.

• 한국차세대컴퓨팅학회논문지
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• 제13권5호
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• pp.80-92
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• 2017

클라우드 컴퓨팅의 대중화로 다양한 유형의 클라우드 서비스가 등장하고 있으며, 퍼블릭 클라우드와 프라이빗 클라우드를 결합하여 이들의 단점을 상쇄시킨 배치 모델인 하이브리드 클라우드가 최근 각광 받고 있다. 하지만 서로 다른 클라우드의 결합에 대한 복잡성 문제와 관련 솔루션 부족에 의해 기업이나 조직의 하이브리드 클라우드 도입과 클라우드 전략 확보가 늦춰지고 있는 실정이다. 이에 본 논문에서는 결합 복잡성 문제 해결을 위한 클라우드 결합기법을 제시한다. 본 논문에서 제시하는 클라우드 결합 기법은 스크립트 기반으로 클라우드 결합을 해결하며, 하이브리드 클라우드 기능을 실현하는 결합 스크립트와 이를 생성, 실행하는 프로세스, 소프트웨어 디자인 패턴을 적용한 스크립트 생성 모델로 구성되어 있다. 제시된 결합 기법을 이용하면 다양한 클라우드 서비스를 결합하여 사용자의 요구에 맞는 스크립트를 빠르게 생성할 수 있으며, 이를 통해 하이브리드 클라우드의 도입과 클라우드 전략 확보를 촉진시킬 수 있을 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• ETRI Journal
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• 제36권6호
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• pp.1008-1015
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• 2014

In this paper, we present a method for reconstructing a surface mesh animation sequence from point cloud animation data. We mainly focus on the articulated body of a subject - the motion of which can be roughly described by its internal skeletal structure. The point cloud data is assumed to be captured independently without any inter-frame correspondence information. Using a template model that resembles the given subject, our basic idea for reconstructing the mesh animation is to deform the template model to fit to the point cloud (on a frame-by-frame basis) while maintaining inter-frame coherence. We first estimate the skeletal motion from the point cloud data. After applying the skeletal motion to the template surface, we refine it to fit to the point cloud data. We demonstrate the viability of the method by applying it to reconstruct a fast dancing motion.

• The Journal of Asian Finance, Economics and Business
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• 제6권1호
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• pp.217-229
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• 2019

The purpose of the research is to verify how task characteristics for business and technology characteristics, economic feasibility, technology readiness, organizational factors, environmental factors of cloud computing affect the performance of cloud computing adoption through Fit and Viability. The research aims to verify the relationship among the success factors for adopting cloud computing based on the Fit-Viability model. Respondents who work for IT companies which is using cloud computing in South Korea were chosen. The data was analyzed by the structural equating model. As a result, Task characteristics and Technology characteristics affected Fit in a positive manner, while Technology readiness, Organizational factors and Environmental factors also positively impacted Viability. Fit and Viability both affected the successful adoption of cloud equally. In particular, Environmental factors were proven to have the biggest impacts on Viability, and affected highly indirect impact on the Performance of cloud computing adoption through Viability. Entering the era of the fourth industrial revolution, corporations have established digital transformation strategies to secure a competitive edge while growing continuously, and are also carrying out various digital transformation initiatives. For the success of adoption of foundational technologies, they need to understand not only the decision-making factors of adopting cloud computing, but also the success factors of adopting cloud computing.

• 대기
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• 제24권1호
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• pp.111-122
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• 2014

In the Korea Meteorological Administration earth system model (HadGEM2-AO), cloud drop number concentration is determined from aerosol number concentration according to the observed relationship between aerosol and cloud drop number concentrations. However, the observational dataset used for establishing the relationship was obtained from limited regions of the earth and therefore may not be representative of the entire earth. Here we reestablished the relationship between aerosol and cloud drop number concentrations based on a composite of observational dataset obtained from many different regions around the world that includes the original dataset. The new relationship tends to provide lower cloud drop number concentration for aerosol number concentration < 600 $cm^{-3}$ and the opposite for > 600 $cm^{-3}$. This new empirical relationship was applied to the KMA earth system model and the historical run (1861~2005) is made again. Here only the 30 year (1861~1890) averages from the runs with the new and the original relationships between aerosol and cloud drop number concentrations (newHIST and HIST, respectively) were compared. For this early period aerosol number concentrations were generally lower than 600 $cm^{-3}$ and therefore cloud drop number concentrations were generally lower but cloud drop effective radii were larger for newHIST than for HIST. The results from the complete historical run with the new relationship are expected to show more significant differences from the original historical run.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.235-247
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• 2021

Today, the cloud computing has become a major demand of many organizations. The major reason behind this expansion is due to its cloud's sharing infrastructure with higher computing efficiency, lower cost and higher fle3xibility. But, still the security is being a hurdle that blocks the success of the cloud computing platform. Therefore, a novel Multi-tenant Decentralized Information Flow Control (MT-DIFC) model is introduced in this research work. The proposed system will encapsulate four types of entities: (1) The central authority (CA), (2) The encryption proxy (EP), (3) Cloud server CS and (4) Multi-tenant Cloud virtual machines. Our contribution resides within the encryption proxy (EP). Initially, the trust level of all the users within each of the cloud is computed using the proposed two-stage trust computational model, wherein the user is categorized bas primary and secondary users. The primary and secondary users vary based on the application and data owner's preference. Based on the computed trust level, the access privilege is provided to the cloud users. In EP, the cipher text information flow security strategy is implemented using the blowfish encryption model. For the data encryption as well as decryption, the key generation is the crucial as well as the challenging part. In this research work, a new optimal key generation is carried out within the blowfish encryption Algorithm. In the blowfish encryption Algorithm, both the data encryption as well as decryption is accomplishment using the newly proposed optimal key. The proposed optimal key has been selected using a new Self Improved Cat and Mouse Based Optimizer (SI-CMBO), which has been an advanced version of the standard Cat and Mouse Based Optimizer. The proposed model is validated in terms of encryption time, decryption time, KPA attacks as well.