• KIISE Transactions on Computing Practices
• /
• v.20 no.12
• /
• pp.658-663
• /
• 2014

Due to the rapid development of open source based Cloud management platforms such as OpenStack, many and various individuals and institutions are trying to construct Cloud computing systems based on open source software projects. It is essential, for those who install, administrate or operate a Cloud, to validate the integrity of the constructed Cloud system. This paper, therefore, proposes the design of a testing tool for validating the integrity of a constructed OpenStack-based Cloud system. Especially, the proposed testing tool utilizes the Tempest project which is an open source project that consists of OpenStack test cases. The proposed testing tool is expected to help developing Cloud technology and Cloud users.

• Korean Journal of Remote Sensing
• /
• v.33 no.4
• /
• pp.339-350
• /
• 2017

In recent, cloud computing paradigm and open source as a huge trend in the Information Communication Technology (ICT) are widely applied, being closely interrelated to each other in the various applications. The integrated services by both technologies is generally regarded as one of a prospective web-based business models impacting the concerned industries. In spite of progressing those technologies, there are a few application cases in the geo-based application domains. The purpose of this study is to develop a cloud-based service system for satellite image processing based on the pure and full open source. On the OpenStack, cloud computing open source, virtual servers for system management by open source stack and image processing functionalities provided by OTB have been built or constructed. In this stage, practical image processing functions for KOMPSAT within this service system are thresholding segmentation, pan-sharpening with multi-resolution image sets, change detection with paired image sets. This is the first case in which a government-supporting space science institution provides cloud-based services for satellite image processing functionalities based on pure open source stack. It is expected that this implemented system can expand with further image processing algorithms using public and open data sets.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.16 no.4
• /
• pp.141-152
• /
• 2013

The applications and concerned technologies of cloud computing services, one of major trends in the information communication technology, are widely progressing and advancing. OpenStack, one of open source cloud computing platforms, is comprised of several service components; using these, it can be possible to build public or private cloud computing service for a given target application. In this study, a remote sensing image analysis processing service on cloud computing environment has designed and implemented as an operational test application in the private cloud computing environment based on OpenStack. The implemented service is divided into instance server, web service, and mobile app. A instance server provides remote sensing image processing and database functions, and the web service works for storage and management of remote sensing image from user sides. The mobile app provides functions for remote sensing images visualization and some requests.

• Korean Journal of Remote Sensing
• /
• v.31 no.1
• /
• pp.1-9
• /
• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.5
• /
• pp.485-490
• /
• 2016

The era of IoT in which all objects are intelligent and are connected to the internet has been started. In order to establish and activate an IoT eco system, open IoT services platform is very important. In this paper, we develop an open IoT services platform and verified the function by building a testbed. Our platform based on the open source hardware and commercial cloud services such as AWS which is a component of an open service IoT platform.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.5
• /
• pp.1146-1154
• /
• 2010

A virtual machine lease service in the cloud computing environment has been implemented using the open source cloud computing platform, OpenNebula. In addition, a web-based cloud user interface is developed for both convenient resource management and efficient service access. The present virtual machine allocation scheme adopted in OpenNebula has performance reduction problem because of not considering CPU allocation scheduler of the virtualization software. In order to address this problem we have considered both the priority of the idle CPU resources of the cluster and credit scheduler of Xen, which resulted in performance improvement of the OpenNebula virtual machine scheduler. The experimental results showed that the proposed allocation scheme provided more virtual machine creations and more CPU resource allocations for cloud service.

• Informatization Policy
• /
• v.26 no.3
• /
• pp.90-106
• /
• 2019

The cloud services market is growing rapidly from the on-premises environment to the cloud computing environment and the domestic cloud software market in Korea is expected to grow at a CAGR of around 15%. In Korea, research teams are providing open cloud platforms using open source software under the government taking the initiative, which intends to enhance the reliability and functionality of open cloud platforms, provide users with a world-class open cloud platform-based and developer-friendly environment that is managed on heterogeneous cloud infrastructure and supported by full-lifecycle management of application software. In this paper, we propose a method to utilize CaaS in the open cloud platform, through incorporating the platform with the container orchestration platform. Finally, by providing users with the application runtime and container runtime, it presents how the two platforms can coexist and cooperate in the same ecosystem.

• Journal of Digital Contents Society
• /
• v.14 no.4
• /
• pp.505-511
• /
• 2013

Recently, cloud computing is being emerged paradigm that a support computing resource flexible and scalable to users as the want in distributed computing environment. Actually, cloud computing can be implemented and provided by virtualization technology. In this paper, we studied open source based cloud computing and built a educational practice system through cloud computing. Virtualization-based cloud computing provides optimized computing resources, as well as easy to manage practical resource and result. Therefore, we can save the time for configuration of practice environment. In the view of faculty, they can easily handle the practice result. Also, those practice condition reuse comfortably and apply to various configuration simply. And then we can increase capabilities and availabilities of limited resources.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.4
• /
• pp.193-202
• /
• 2023

In recent years, the outstanding performance of large language models (LLMs) trained on extensive datasets has become a hot topic. Since studies on LLMs are available on open-source approaches, the ecosystem is expanding rapidly. Models that are task-specific, lightweight, and high-performing are being actively disseminated using additional training techniques using pre-trained LLMs as foundation models. On the other hand, the performance of LLMs for Korean is subpar because English comprises a significant proportion of the training dataset of existing LLMs. Therefore, research is being carried out on Korean-specific LLMs that allow for further learning with Korean language data. This paper identifies trends of open source based LLMs and introduces research on Korean specific large language models; moreover, the applications and limitations of large language models are described.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.169-171
• /
• 2013

Cloud computing provides access to big volumes of data and computational resources through various services. Cloud computing also supports to process these volumes of data using set of computers. Cloud computing can satisfy resource requirements through virtualization technology. Eucalyptus is an open source cloud computing environment helps the users to setup their own private cloud based on virtualization. In this paper, monitoring of virtual machines is explained with the eucalyptus cloud setup.