• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.313-329
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• 2021

Purpose - Digital trade, which started in the early 2000s, is showing a sharp increase due to the recent pandemic. However, despite this proliferation, users' acceptance of innovation is very slow. Cloud services are at the center of digital trade activation. This study aims to contribute to the spread of digital trade through empirical analysis of the resistance factors that hinder the use of cloud service-based digital trade using the innovation resistance theory and the status quo bias theory. Design/Methodology/Approach - In order to achieve the research purpose, this study was conducted with 171 entrepreneurs using cloud service-based digital trade. Structural equation model(SEM) was used through empirical analysis. Findings - As a result of the study, it was found that the complexity of technology, perceived risk, compatibility, and trust in service providers had a significant effect on innovation resistance, and policy trust did not affect innovation resistance. Also, security concerns and institutional trust were analyzed to have a significant effect on the trust of service providers. Research Implications - This study is meaningful to help the rapid diffusion of innovative technologies through empirical analysis of factors that lower the intention to accept cloud service-based digital trade.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.95-105
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• 2015

In this paper, we propose the security requirements for developing the security functions of server virtualization system. The security requirements are based on the security threats of server virtualization system, and we verified the validity by defending the security threats of server virtualization system. For inducting the security threats damaging server virtualization system from cloud computing security threats, we analyze and suggest the relations between security threats and security issue of server virtualization system.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.467-475
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• 2012

Cloud computing services are known that they have many advantages from the point of view in economic saving, scalability, security, sharing and accessibility. So their applications are extending from simple office systems to the expert system for scientific computing. However, research or computing technology development in the geo-spatial fields including remote sensing applications are the beginning stage. In this work, the previously implemented smartphone app for image processing was first migrated to mobile cloud computing linked to Amazon web services. As well, parallel programming was applied for improving operation performance. Industrial needs and technology development cases in terms of mobile cloud computing services are being increased. Thus, a performance testing on a satellite image processing module was carried out as the main purpose of this study. Types of implementation or services for mobile cloud varies. As the result of this testing study in a given condition, the performance of cloud computing server was higher than that of the single server without cloud service. This work is a preliminary case study for the further linkage approach for mobile cloud and satellite image processing.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1349-1365
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• 2020

In recent years, in the fields of smart cities and digital twins, research on model generation is increasing due to the advantage of acquiring actual 3D coordinates by using point clouds. In addition, there is an increasing demand for a solid model that can easily modify the shape and texture of the building. In this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. Accordingly, in this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. In the first step, the ground points were removed through the planarity analysis of the point cloud. In the second step, building area was extracted from the ground removed point cloud. In the third step, detailed structural area of the buildings was extracted. In the fourth step, the shape of 3D building models with 3D coordinate information added to the extracted area was created. In the last step, a 3D building solid model was created by giving texture to the building model shape. In order to verify the proposed method, we experimented using point clouds extracted from unmanned aerial vehicle images using commercial software. As a result, 3D building shapes with a position error of about 1m compared to the point cloud was created for all buildings with a certain height or higher. In addition, it was confirmed that 3D models on which texturing was performed having a resolution of less than twice the resolution of the original image was generated.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.347-357
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• 2019

The usefulness of processing and analysis systems of GIS-based agricultural climate data is affected by the reliability and availability of computing infrastructures such as cloud, on-premises, and hybrid. Cloud technology has grown in popularity. However, various reference cases accumulated over the years of operational experiences point out important features that make on-premises technology compatible with cloud technology. Both cloud and on-premises technologies have their advantages and disadvantages in terms of operational time and cost, reliability, and security depending on cases of applications. In this study, we have described characteristics of four general computing platforms including cloud, on-premises with hardware-level virtualization, on-premises with operating system-level virtualization and hybrid environments, and compared them in terms of advantages and disadvantages when a huge amount of GIS-based agricultural climate data were stored and processed to provide public services of agro-meteorological and climate information at high spatial and temporal resolutions. It was found that migrating high-resolution agricultural climate data to public cloud would not be reasonable due to high cost for storing a large amount data that may be of no use in the future. Therefore, we recommended hybrid systems that the on-premises and the cloud environments are combined for data storage and backup systems that incur a major cost, and data analysis, processing and presentation that need operational flexibility, respectively.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.308-315
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• 2016

With the advancement in the area of cloud storage services as well as a tremendous growth of social networking sites, permission for one web service to act on the behalf of another has become increasingly vital as social Internet services such as blogs, photo sharing, and social networks. With this increased cross-site media sharing, there is a upscale of security implications and hence the need to formulate security protocols and considerations. Recently, OAuth, a new protocol for establishing identity management standards across services, is provided as an alternative way to share the user names and passwords, and expose personal information to attacks against on-line data and identities. Moreover, OwnCloud provides an enterprise file synchronizing and sharing that is hosted on user's data center, on user's servers, using user's storage. We propose a secure Social Networking Site (SSN) access based on OAuth implementation by combining two novel concepts of OAuth and OwnCloud. Security analysis and performance evaluation are given to validate the proposed scheme.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.25-32
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• 2017

In this paper, we propose the softwareization of broadcasting system. Recently, the topic of industry is the fourth industrial revolution. The fourth industrial revolution is evolving from physical to virtualization. The Industrial Revolution is based on IT technology. Artificial Intelligence (AI), Big Data, and the Internet of Things, which are famous for Alpha Go, are based on software. Among IT, software is the main driver of industrial terrain change. The systemization of software on the basis of cloud environment is proceeding rapidly. System development through softwarization can reduce time to market lead time, hardware cost reduction and manual operation compared to existing hardware system. By developing and implementing broadcasting system such as IPTV based on cloud, lead time for opening service compared to existing hardware system can be shortened by more than 90% and investment cost can be saved by about 40%. In addition, the area of the system can be reduced by 50%. In addition, efficiency can be improved between infrastructures, shortening of trouble handling and ease of maintenance. Finally, we can improve customer experience through rapid service opening.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.476-490
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• 2017

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down, the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service. To maintain threshold, the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.