• 컴퓨터교육학회논문지
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• 제14권2호
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• pp.75-82
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• 2011

클라우드 컴퓨팅은 인터넷 혹은 인트라넷 기반의 대규모 컴퓨팅 자원을 가상화하여 사용자가 원하는 서비스를 언제 어디서든 제공하도록 하는 컴퓨팅 패러다임이다. 이러한 클라우드 컴퓨팅은 시스템 환경 자체가 대규모의 데이터를 처리하며, 다중 사용자 접속 환경 기반이어서 시스템의 신뢰성이 중요한 요소이다. 본 논문에서는 클라우드 환경에서 발생하는 문제(사용자의 요구사항 변경, 자원 결함 발생 등)를 해결하기 위해 시스템 환경 내부의 자원 변화에 대처할 수 있고 결함 포용적인 신뢰성 기반 적응적 스케줄링 기법을 제안한다. 이 기법의 타당성을 검증하기 위해 CloudSim 시뮬레이션 환경에서 실험하였다.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.239-251
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• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.

• 한국멀티미디어학회논문지
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• 제18권8호
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• pp.915-924
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• 2015

With growing popularity of cloud computing services, users can more easily manage massive amount of data by outsourcing them to the cloud, or more efficiently analyse large amount of data by leveraging IT infrastructure provided by the cloud. This, however, brings the security concerns of sensitive data. To provide data security, it is essential to encrypt sensitive data before uploading it to cloud computing services. Although data encryption helps provide data security, it negatively affects the performance of massive data analytics because it forbids the use of index and mathematical operation on encrypted data. Thus, in this paper, we propose a novel algorithm which enables to efficiently process a large amount of encrypted data. In particular, we propose a novel top-k processing algorithm on the massive amount of encrypted data in the cloud computing environments, and verify the performance of the proposed approach with real data experiments.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.637-640
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• 2017

최근 클라우드 기술이 확산되면서 여러 기업이 자신만의 클라우드를 다양하게 제공하고 있으며 세계 각지에 흩어져 있는 다양한 클라우드 공급자들과 여러 프라이빗 클라우드를 연결하여 하나의 서비스를 제공하는 클라우드 서비스 브로커리지(Cloud Services Brokerage) 기술이 등장하게 되었다. 하지만 현재의 CSB 기술은 가상 자원 관리, 가상 머신 라이프 사이클 관리에 초점이 맞추어져 있으며 CSB에서 제공되는 모니터링 요소는 사용자의 복잡한 요구를 만족하기에는 부족한 실정이다. 또한 추가 모니터링 도구를 사용하는 경우도 CSB의 데이터와의 일관성을 만족하지 않는 문제가 있다. 따라서 본 논문에서는 이종 CSB와 연동이 가능한 실시간 모니터링 시스템을 제안한다. 본 논문에서 제안하는 모니터링 기술은 Scalr 및 CompatibleOne을 사용하여 주기적으로 메타데이터 동기화를 진행하며 데이터 일관성을 충족시키고 다양한 모니터링 데이터를 실시간으로 수집하여 사용자에게 제공한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.60-63
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• 2017

Cloud Computing 환경은 사용자로 하여금 네트워크를 통하여 운영플랫폼, 저장매체 등이 운영 가능한 컴퓨터 자원을 신속하게 이용할 수 있는 컴퓨팅 환경이다. 이 환경을 이용하여 사용자들에게 가상의 컴퓨팅 공간을 만들어 resource를 사용하게 만들어주는 Iaas(Infrastructure as a Service)가 급증하고 있다. OpenStack은 Cloud Computing 환경을 이용하여 사용자로 하여금 *aaS제공을 가능하게 해주는 오픈소스 소프트웨어 프로젝트이다. 이 연구는 Openstack을 활용하여 Cloud환경을 구축하고, 이를 활용 하는 방안에 대한 연구이다. GitLab를 이용한 GitLab Service Launching을 시도하고, Hadoop을 통하여 Cloud 환경을 활용한 분산처리 시스템을 구현, Cloud의 활용 방안을 탐구한다.

• 한국IT서비스학회지
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• 제11권3호
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• pp.287-304
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• 2012

Cloud computing, which means a new way of deploying information technology(IT) in organizations as a service and charging per use, has a deep impact on organizations' IT accessibility, agility and efficiency of its usage. More than that, the emergence of cloud computing surpasses a mere technological innovation, making business model innovation possible. We call this innovation realized by could computing a cloud business model. This study develops a comprehensive framework of business model, first, and then defines and analyzes the cloud business model through this framework. This study also examines the case of M-Pesa mobile payment as a cloud business model in which a new value creation and profit realization schemes have been realized and industry value network has changed. Finally, this study discusses the business implications from this new business model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.

• Journal of information and communication convergence engineering
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• 제13권1호
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• pp.15-20
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• 2015

The limited battery power in the mobile environment, lack of sufficient wireless bandwidth, limited resources of mobile terminals, and frequent breakdowns of the wireless network have become major hurdles in the development of mobile cloud computing (MCC). In order to solve the abovementioned problems, This paper propose a proxy-based MCC framework by adding a proxy server between mobile devices and cloud services to optimize the access to cloud services by mobile devices on the network transmission, application support, and service mode levels. Finally, we verify the effectiveness of the developed framework through an experimental analysis. This framework can ensure that mobile users have efficient access to cloud services.

• 한국컴퓨터정보학회논문지
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• 제21권4호
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• pp.31-38
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• 2016

The interface between servers and clients and system management in the cloud computing environment is different from the existing computing environment. The technology for information protection. Management and user authentication has become an important issue. For providing a more convenient service to users, SSO technology is applied to this cloud computing service. In the SSO service environment, system access using a single key facilitates access to several servers at the same time. This SSO authentication service technology is vulnerable to security of several systems, once the key is exposed. In this paper, we propose a technology to solve problems, which might be caused by single key authentication in SSO-based cloud computing access. This is a distributed agent authentication technology using a multiple SSO agent to reinforce user authentication using a single key in the SSO service environment. For user authentication reinforcement, phased access is applied and trackable log information is used when there is a security problem in system to provide a safe cloud computing service.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.59-66
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• 2024

This paper presents the concept and characteristics of cloud computing, and it addresses how cloud computing delivers quality of service (QoS) to the end-user. Next, it discusses how to schedule one's workload in the infrastructure using technologies that have recently emerged such as Machine Learning (ML). That is followed by an overview of how ML can be used for resource management. This paper then looks at the primary goal of this project, which is to outline the benefits of using ML to schedule upcoming demands to achieve QoS and conserve energy. In this survey, we reviewed the research related to ML methods for predicting workloads in cloud computing. It also provides information on the approaches to elasticity, while another section discusses the methods of prediction used in previous studies and those that used in this field. The paper concludes with a summary of the literature on predicting workloads and optimising QoS in the cloud computing.