• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1910-1917
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• 2011

In this paper, a cloud computing platform is designed and implemented based on an open source cloud platform, OpenNebula, and Xen hypervisor on each node for efficient computer lab system. For the purpose of convenient management, a web-based user interface has been developed for the cloud virtualization system. Once individual virtual machine is allocated to a user based upon class schedule, each user can access the virtual machine remotely and use appropriate operating system and application programs. The developed system can reduce computer lab upgrade cost, management cost, and administration time considerably.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.440-444
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• 2018

Purpose: Cloud-computing technology has several advantages, including maintenance, management, accessibility, and computing power. A greenhouse-control system utilizing these advantages was developed using a private cloud-computing system. Methods: A private cloud needs a collection of servers and a suite of software tools to monitor and control cloud-computing resources. In this study, a server farm, operated by OpenStack as a cloud platform, was constructed using servers, and other network devices. Results: The greenhouse-control system was developed according to the fundamental cloud service models: infrastructure as a service, platform as a service, and software as a service. This system has four additional advantages - security, control function, public data use, and data exchange. There are several considerations that must be addressed, such as service level agreement, data ownership, security, and the differences between users. Conclusions: When the advantages are utilized and the considerations are addressed, cloud-computing technology will be beneficial for agricultural use.

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

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4165-4187
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• 2016

As an emerging technology, cloud computing is a revolution in information technology that attracts significant attention from both public and private sectors. In this paper, we proposed a dynamic approach for live migration to obviate overloaded machines. This approach is applied on OpenStack, which rapidly grows in an open source cloud computing platform. We conducted a cost-aware dynamic live migration for virtual machines (VMs) at an appropriate time to obviate the violation of service level agreement (SLA) before it happens. We conducted a preemptive migration to offload physical machine (PM) before the overload situation depending on the predictive method. We have carried out a distributed model, a predictive method, and a dynamic threshold policy, which are efficient for the scalable environment as cloud computing. Experimental results have indicated that our model succeeded in avoiding the overload at a suitable time. The simulation results from our solution remarked the very efficient reduction of VM migrations and SLA violation, which could help cloud providers to deliver a good quality of service (QoS).

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.445-454
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• 2014

In recent days, trend technologies for cloud, bigdata, or mobile, as the important marketable keywords or paradigm in Information Communication Technology (ICT), are widely used and interrelated each other in the various types of platforms and web-based services. Especially, the combination of cloud and mobile is recognized as one of a profitable business models, holding benefits of their own. Despite these challenging aspects, there are a few application cases of this model dealing with geo-based data sets or imageries. Among many considering points for geo-based cloud application on mobile, this study focused on a performance test of mobile cloud of Bayesian image fusion algorithm with satellite images. Two kinds of cloud platform of Amazon and OpenStack were built for performance test by CPU time stamp. In fact, the scheme for performance test of mobile cloud is not established yet, so experiment conditions applied in this study are to check time stamp. As the result, it is revealed that performance in two platforms is almost same level. It is implied that open source mobile cloud services based on OpenStack are enough to apply further applications dealing with geo-based data sets.

• The Journal of Bigdata
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• v.4 no.1
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• pp.119-127
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• 2019

This study explains how to solve engineering problems easily and efficiently by using cloud based big data platform. To do this, we propose a cloud based big data analysis platform. The application helps users easily create models for data analysis using cloud based big data analysis platform. Analytical models modeled using components are analyzed through an analysis engine. Our platform include pre-processing, analysis, and visualization algorithms required for data analysis. Finally, we show an application of effluent concentration in a sewage treatment process.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.67-75
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• 2019

The Android container is used for various purposes such as Bring Your Own Device (BYOD) solution and Android malware analysis. The strong point of android container than other technologies is it can simulate an android device like a real android phone on a hardware layer. Therefore, automatic management solutions for android container are necessary. This paper introduces a new design of cloud-based management solution for android containers. Through the proposal, android containers are managed automatically from a cloud platform - OpenStack with various tasks like: container configuration, deployment, destroy, android version, hardware device. In addition, the system monitoring and system statistics for android containers and hardware devices are also provided.

• Journal of Distribution Science
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• v.16 no.7
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• pp.67-75
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• 2018

Purpose - In the 21st century, as information technology advances alongside the emergence of the 4th generation, industrial age, industrial environment has become individualized and customized. It is important to hire good quality employees for good service in the industry. The e-learning market is growing every year. Although e-learning companies are finding better quality employees in e-learning, it is not easy to find it. Companies also spend a lot of time and cost to find employee. On the employees side, they want to get a job freely when they want, but they cannot find their job easily. Furthermore, the labor market environment is changing fast. In the 4th generation, industrial age, employers require to find manpower whenever they need and want at little cost. So of their own accord, we have considered the necessity of management of human resources for employees and employers in e-learning. The purpose of this study is to propose a human cloud platform framework for enabling an efficient management of human resources in e-learning industry. Research design, data, and methodology - To pinpoint the items of a human cloud platform framework, the study was initiated according to the following process. First, items of competency relating to e-learning instructional designer was analyzed. Second, based on the items of information from this analysis, selection and validity verification took place with 5 e-learning specialists group. Third, the opinion of experts who were in charge of hiring in e-learning companies were collated with the questionnaire. Lastly, the human cloud platform framework was proposed based on opinion results. Results - The framework was comprised of 7 domains and 27 items in order to develop the human cloud platform for e-learning instructional designer. The analysis results showed that the most highly considered item were 'skill (4.60)' that employee already have the capability. Following this (in order) were 'project type (4.56)', 'work competency (4.56)', and 'strength area of instructional design (4.52)'. Conclusions - The 27 items in the human cloud platform framework were suggested in this study. Following this, we can consider to develop the human cloud platform for finding a job and hiring e-learning instructional designer easily. For successful platform operation, we need to consider reliability between employer and employee. In addition, we need quality assurance system based on operation has public confidence.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.211-224
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• 2016

Based on the 'Government 3.0', the government opens the public data and encourages the active use in the private sector. Recently, the spatial and statistical information that is one of the public data is being widely used in the various web business as a high value-added information. In this study, we propose an architecture of high-availability, high-reliability and high-performance open platform which can provide a variety of services such as searching, analysis, data mining, and thematic mapping. In particular, we present two different system architectures for the government and the public services, by reflecting the importance of the information security and the respective utilization in the private and public sectors. We also compared a variety of server architecture configurations such as a clustered server configuration, a cloud-based virtual server configuration, and a CDN server configuration, in order to design a cost- and performance-effective spatial-statistical information open platform.