• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.11-21
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• 2015

If the cloud computing environment is not sufficiently provide the required resources due to the number of virtual server to process the request, may cause a problem that the load applied to the specific server. Migration administrator receive the resources of each physical server for improving the efficiency of the virtual server that exists in the physical servers, and determines the migration destination based on the simulation results. But, there is more overhead predicting the future resource consumption of all the physical server to decide the migration destination through the simulation process in large and complex cloud computing environments. To solve this problem, we propose an improved prediction method with the simulation-based approach. The proposed method is a fuzzy-logic based priority model for VM migration. We design a proposed model with the DEVS formalism. And we also measure and compare a performance and migration count with existing simulation-based migration method. FPLM shows high utilization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.91-97
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• 2021

A microserver is a type of a computing server, in which two or more CPU nodes are implemented on a separate computing board, and a plurality of computing boards are integrated on a main board. In building a cluster system, the microserver has advantages in several points such as energy efficiency, area occupied, and ease of management compared to the existing method of mounting legacy servers in multiple racks. In addition, since the microserver uses a fast interconnection network between CPU nodes, performance improvement for data transfers is expected. The proposed microserver can mount a total of 16 computing boards with 4 CPU nodes on the main board, and uses Serial-RapidIO (SRIO) as an interconnection network. In order to analyze the performance of the proposed microserver in terms of the interconnection network which is a core performance issue of the microserver, we compare and quantify the performance of commercial microservers. As a result of the test, it showed up to about 7 times higher bandwidth improvement when transmitting data using the interconnection network. In addition, with CloudSuite benchmark programs used in actual cloud computing, maximum 60% reduction in execution time was obtained compared to commercial microservers with similar CPU performance specification.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.108-122
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• 2021

With the development of 3D graphics software and the speed of computer hardware, it is an era that can be realistically expressed not only in movie visual effects but also in console games. In the production of such realistic 3D models, 3D scans are increasingly used because they can obtain hyper-realistic results with relatively little effort. Among the various 3D scanning methods, photogrammetry can be used only with a camera. Therefore, no additional hardware is required, so its demand is rapidly increasing. Most 3D artists shoot as many images as possible with a video camera, etc., and then calculate using all of those images. Therefore, the photogrammetry method is recognized as a task that requires a lot of memory and long hardware operation. However, research on how to obtain precise results with 3D photogrammetry scans is insufficient, and a large number of photos is being utilized, which leads to increased production time and data capacity and decreased productivity. In this study, point cloud data generated according to changes in the number and resolution of photographic images were produced, and an experiment was conducted to compare them with original data. Then, the precision was measured using the average distance value and standard deviation of each vertex of the point cloud. By comparing and analyzing the difference in the precision of the 3D photogrammetry scans according to the number and resolution of images, this paper presents a direction for obtaining the most precise and effective results to 3D artists.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.518-535
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• 2010

Cloud Computing is emerged as an effective reuse paradigm, where service providers operate hardware and software and as a service, and service consumers invoke the service through Internet. Software-as-a-Service (SaaS) is a type of cloud services, where the whole software is designed as a service so that several consumers can reuse the SaaS. While tradition software applications are developed for a specific organization, SaaS is developed for multiple users in the various organizations. Hence, reusability is very essential characteristic of SaaS. Reusability is defined as a metric of how effective and efficient software functionalities can be used by various users. Reusability in SaaS is evaluated by considering three sub-characteristics; applicability, adaptability, and scalability. Since such a SaaS has considerable differences and characteristics from traditional software applications, conventional methods including object-oriented modeling, component-based development method, and service-oriented architecture (SOA) service development method would be limited in developing services which can fulfill these three sub-characteristics related to reusability as well as SaaS-intrinsic characteristics. Hence, there is a great demand for effective processes for developing SaaS cloud services. In this paper, we present a practical process for developing SaaS, which focuses on ensuring reusability. And by performing a case study with our proposed SaaS development process, we evaluate applicability of our proposed process and explain how the process is used in a real domain. Then, we compare our proposed process with others for verifying our study. Through the proposed process, cloud services with high quality can be more effectively developed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.911-931
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• 2021

Recently, most cloud services use Docker container environment to provide their services. However, there are no researches to evaluate the performance of communication libraries for multi-GPU based distributed deep learning in a Docker container environment. In this paper, we propose an efficient communication architecture for multi-GPU based deep learning in a Docker container environment by evaluating the performances of various communication libraries. We compare the performances of the parameter server architecture and the All-reduce architecture, which are typical distributed deep learning architectures. Further, we analyze the performances of two separate multi-GPU resource allocation policies - allocating a single GPU to each Docker container and allocating multiple GPUs to each Docker container. We also experiment with the scalability of collective communication by increasing the number of GPUs from one to four. Through experiments, we compare OpenMPI and MPICH, which are representative open source MPI libraries, and NCCL, which is NVIDIA's collective communication library for the multi-GPU setting. In the parameter server architecture, we show that using CUDA-aware OpenMPI with multi-GPU per Docker container environment reduces communication latency by up to 75%. Also, we show that using NCCL in All-reduce architecture reduces communication latency by up to 93% compared to other libraries.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.169-185
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• 2016

Recently mean stand height has been added as new attribute to forest type maps, but it is often too costly and time consuming to manually measure 9,100,000 points from countrywide stereo aerial photos. In addition, tree heights are frequently measured around tombs and forest edges, which are poor representations of the interior tree stand. This work proposes an estimation of mean stand height using an image-based point cloud, which was extracted from stereo aerial photo with FUSION S/W. Then, a digital terrain model was created by filtering the DSM point cloud and subtracting the DTM from DSM, resulting in nDSM, which represents object heights (buildings, trees, etc.). The RMSE was calculated to compare differences in tree heights between those observed and extracted from the nDSM. The resulting RMSE of average total plot height was 0.96 m. Individual tree heights of the whole study site area were extracted using the USDA Forest Service's FUSION S/W. Finally, mean stand height was produced by averaging individual tree heights in a stand polygon of the forest type map. In order to automate the mean stand height extraction using photogrammetric methods, a module was developed as an ArcGIS add-in toolbox.

• Journal of The Korean Astronomical Society
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• v.36 no.4
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• pp.271-282
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• 2003

We present results of a $H^{13}CN$ J=1-0 mapping survey of molecular clouds toward the Galactic Center (GC) region of $-1.6^{\circ}{\le}{\iota}{\le}2^{\circ}$ and $-0.23^{\circ}{\le}b{\le}0.30^{\circ}$ with 2' grid resolution. The $H^{13}CN$ emissions show similar distribution and velocity structures to those of the $H^{12}CN$ emissions, but are found to better trace the feature saturated with $H^{12}CN$ (1-0). The bright components among multi-components of $H^{12}CN$ line profiles usually appear in the $H^{13}CN$ line while most of the dynamically forbidden, weak $H^{12}CN$ components are seldom detected in the $H^{13}CN$ line. We also present results of other complementary observations in $^{12}CO$ (J=1-0) and $^{13}CO$ (J=1-0) lines to estimate physical quantities of the GC clouds, such as fractional abundance of HCN isotopes and mass of the GC cloud complexes. We confirm that the GC has very rich chemistry. The overall fractional abundance of $H^{12}CN$ and $H^{13}CN$ relative to $H_2$ in the GC region is found to be significantly higher than those of any other regions, such as star forming region and dark cloud. Especially cloud complexes nearer to the GC tend to have various higher abundance of HCN. Total mass of the HCN molecular clouds within $[{\iota}]{\le}6^{\circ}$ is estimated to be ${\~}2 {\times}10^7\;M_{\bigodot}$ using the abundances of HCN isotopes, which is fairly consistent with previous other estimates. Masses of four main complexes in the GC range from a few $10^5$ to ${\~}10^7\;M_{\bigodot}$ All the HCN spectra with multi-components for the four main cloud complexes were investigated to compare the line widths of the complexes. The largest mode (45 km $s^{-1}$) of the FWHM distributions among the complexes is in the Clump 2. The value of the mode tends to be smaller at the farther complexes from the GC.

• Publications of The Korean Astronomical Society
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• v.23 no.2
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• pp.31-35
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• 2008

We present analytical approximations for calculating the scattering and escape of non-ionizing photons from a plane-parallel medium with uniformly illuminated by external sources. We compare the results with the case of a spherical dust cloud. It is found that more scattering and absorption occur in the plane-parallel geometry than in the spherical geometry when the optical depth perpendicular to the plane and the radial optical depth of the sphere are the same. The results can provide an approximate way to estimate radiative transfer in a variety interstellar conditions and can be applied to the dust-scattered diffuse Galactic light.

• Proceedings of the Korean Association for Survey Research Conference
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• 2006.12a
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• pp.67-83
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• 2006

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.543-556
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• 2007

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.