• Spatial Information Research
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• v.19 no.4
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• pp.55-71
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• 2011

Recently, interest in cloud computing which provides IT resources as service form in IT field is increasing. As a result, much research has been done on the distributed data processing that store and manage a large amount of data in many servers. Meanwhile, in order to effectively utilize the spatial data which is rapidly increasing day by day with the growth of GIS technology, distributed processing of spatial data using cloud computing is essential. Therefore, in this paper, we review the representative distributed data processing techniques and we analyze the optimization requirements for performance improvement of the distributed processing techniques for a large amount of data. In addition, we uses the Hadoop and we evaluate the performance of the distributed data processing techniques for their optimization requirements.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.112-115
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• 2011

Healthcare is one of the biggest industries that consume IT Infrastructure as a necessity. A reliable reach to secure private information is the essential goal. Most of the healthcare organizations either have their own custom solutions developed or third part CRM software tailored to their needs. This culture satisfies the usability internal to the organization but lacks the ability to provide public access to the users or even to take a step ahead and collaborate with like minded institutes for research and potential growth. Emergence of cloud computing has provided us the opportunity to take a step ahead and build applications available to users on a secure platform, with ability to scale the resources depending on the requirements. The effective use of hybrid and community cloud can create rock solid foundations for healthcare IT Infrastructure. These cloud deployment models not only caters the present needs of healthcare IT Infrastructure but also opens the possibilities to build applications and provide secure and reliable access beyond the limits of organizational boundaries.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.8
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• pp.599-604
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• 2012

Most air pollution and smog are a result of the burning of fossil fuels. The use of fossil fuels also causes acid rain and global warming. So the need for solar energy utilization is increased. It is essentially important to make efforts to reduce usage of fossil energy resources. In this study, we analyzed the correlation between climatic elements(Cloud cover, Duration of sunshine, Temperature) and the photovoltaic power generation. Cloud cover of the correlation coefficient was 0.87. And duration of sunshine of the correlation coefficient was 0.93. The order of the correlation coefficient was duration of sunshine, cloud cover, temperature. To accurately analyze of the degree of correlation for the photovoltaic power generation, additional research about climatic elements that show a high correlation is needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.273-276
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• 2011

In this paper, Cloud services to support the implementation of UNIX virtualization systems, and applications using Java-based service are proposed. Unix Virtualization with Web Server zone NFS zone and FTP zone is divided into three systems and is implemented. Applications are implemented with Java programming. Applicable to Unix systems, applications and data anytime, anywhere by uploading, downloading music, documents tasks, and It provides efficiency. From Unix virtualization for server resources, we can expect energy savings. Smart phone without PC conduct its mission and business with benefits.

• International Journal of Contents
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• v.8 no.4
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• pp.12-20
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• 2012

For a library to be able provide information services and fulfill its function as a knowledge convergence center capable of responding to various information demands, the development of next-generation information systems based on the latest information and communication technology is needed. The development of mobile information services using portable devices such smart phones and tablet PCs and information systems which incorporate the concepts of cloud computing, SaaS (Software as a Service), annotation and Library2.0 is also required. This paper describes a library information system that utilizes collective intelligence and cloud computing. The information system developed for this study adopts the SaaS-based cloud computing service concept to cope with the shift in the mobile service paradigm in libraries and the explosion of electronic data. The strengths of such a conceptual model include the sharing of resources, support of multi-tenants, and the configuration and support of metadata. The user services are provided in the form of software on-demand. To test the performance of the developed system, the efficiency analysis and TTA certification test were conducted. The results of performance tests, It is encouraging that, at least up to 100MB, the job time is approximately linear and with only a moderate overhead of less than one second. The system also passed the level-3 or higher criteria in the certification test, which includes the SaaS maturity, performance and application program functions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.24-30
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• 2014

This study investigates computing offloading effect of cloud in real-time video personal broadcast service, whose server is mobile device. Mobile device does not have enough computing resource for encoding video. The computing burden is offloaded to cloud, which has abundant resources in terms of computing, power, and storage compared to mobile device. By reducing computing burden, computation energy can be saved while transmission data amount increases because of decreasing compression efficiency. This study shows that the optimal operation point can be found adaptively to time-varying LTE communication condition result of tradeoff analysis between offloaded computation burden and increase in amount of transmitted data.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.567-582
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• 2011

The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.41-47
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• 2013

In this paper, for this open system-based virtual resource monitoring system was designed. Virtual resources, CPU, memory, disk, network, each subdivided into parts, each modular implementation. Implementation results in real time CPU, memory, disk, network information, confirmed the results of monitoring. System designed to implement the Windows, Linux, Xen was used for the operating system, implementation language, C++ was used, the structure of the system, such as the ability to upgrade and add scalability and modularity by taking into account the features available in cloud computing environments applicable to cloud computing, virtual resource monitoring system has been implemented.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.160-163
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• 2015

워크플로우 매니지먼트시스템은 오늘날의 어플리케이션들의 처리를 위한 효율적인 워크플로우 설계와 수행을 가능하게 한다. 그러나 전체물리학, 생물학, 지질학과 같이 과학탐구에 목적을 둔 어플리케이션들의 경우 대용량의 데이터를 연산해야 하기 때문에 단일 컴퓨팅 자원으로는 단 시간내에 작업을 완료하기 어렵다. 클라우드 환경에서 워크플로우를 효율적으로 수행하기 위해서는 여러 자원을 효율적으로 활용하기 위한 분산 병렬처리가 필수적이다. 일반적으로 시스템의 마스터노드에서는 클러스터의 원격노드들에게 어플리케이션 수행을 위해 설계된 워크플로우에 맞게 작업들을 분배하게 되는데 이때 마스터노드와 원격노드의 큐에서의 대기시간과 원격노드에서 할당된 작업들을 위한 스케줄링 시간은 성능을 좋지 않게 만드는 원인이 된다. 따라서 본 논문은 클라우드 환경에서 원격노드에서 작업수행이전까지의 지연시간을 줄이기 위한 최적화 방법으로 컴퓨팅 자원 활용도를 고려한 작업들의 병합 기법을 적용해서 워크플로우의 처리 속도를 향상시킨다.