• International Journal of Contents
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• v.12 no.2
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• pp.6-11
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• 2016

We developed a pilot-job based large-scale distributed computing system to support HTC and MTC, called HTCaaS (High-Throughput Computing as a Service), which helps scientists solve large-scale scientific problems in areas such as pharmaceutical domains, high-energy physics, nuclear physics and bio science. Since most of these problems involve critical data that affect the national economy and activate basic industries, data privacy is a very important issue. In this paper, we implement a privacy enhanced data security mechanism to support HTC and MTC in a large-scale distributed computing system and show how this technique affects performance in our system. With this mechanism, users can securely store data in our system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.658-661
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• 2005

Internet-based client/server architecture of Contents Delivery System suffers from frequent disconnections and security treats caused by dependency of the server or overload. But, We reached the limit to the increase of the server because a contents quality enhance and Internet user explosively increase. Therefore, a P2P based computing methods are used for sloving these issues. In this paper, We implement and design the Education Content Delivery System for cyber education system using idle Computing Power in P2P computing to share computing resources. We implement not only Internet infrastructure but also satellite infrastructure system, and designed to transfer real-time or non real-time contents.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.81-87
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• 2010

This paper proposes a G-BLAST(BLAST using Grid Computing) system, an integrated software package for BLAST searches operated in heterogeneous distributed environment. G-BLAST employed 'database splicing' method to improve the performance of BLAST searches using exists computing resources. G-BLAST is a basic local alignment search tool of DNA Sequence using grid computing in heterogeneous distributed environment. The G-BLAST improved the existing BLAST search performance in gene sequence analysis. Also G-BLAST implemented the pipeline and data management method for users to easily manage and analyze the BLAST search results. The proposed G-BLAST system has been confirmed the speed and efficiency of BLAST search performance in heterogeneous distributed computing.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.171-178
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• 2013

Desktop grid computing is the computing paradigm that can execute large-scale computing jobs using the desktop resources with heterogeneity and volatility. However, such the computing environment can not guarantee the stability and reliability of task execution because the desktop resources with different performance can freely participate and leave in task execution. Therefore, in this paper, we design resource grouping scheme using k-means clustering algorithm with an aim to provide desktop grid computing with the stability and reliability of task execution. Moreover, we conduct resource grouping using the execution log data of actual desktop grid systems and present application methods of desktop resource groups to fault-tolerance.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.214-223
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• 2019

This study was to review the research trends in domestic computing thinking and to suggest future research direction by analyzing 138 papers related to computing thinking published in domestic academic journals from 2015 to 2018. As a result, domestic research on computing thinking has been steadily increasing since 2015, and quantitative research, development research and experimental research were mainly used. Most research were conducted for elementary school students and university students. Research topics are oriented to the curriculum and program as well as the relationship among the variables related with computational thinking. It is necessary to explore empirical studies such as teaching methods, teaching tools, media utilization, and evaluation methods in order to promote learner's computing thinking. Also, it is needed to explore various variables related to enhance computing thinking and the relationship among the variables.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.8-17
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• 2014

Petascale systems(so called supercomputers) have been mainly used for supporting communication-intensive and tightly-coupled parallel computations based on message passing interfaces such as MPI(HPC: High-Performance Computing). On the other hand, computing paradigms such as High-Throughput Computing(HTC) mainly target compute-intensive (relatively low I/O requirements) applications consisting of many loosely-coupled tasks(there is no communication needed between them). In Korea, recently emerging applications from various scientific fields such as pharmaceutical domain, high-energy physics, and nuclear physics require a very large amount of computing power that cannot be supported by a single type of computing resources. In this paper, we present our HTCaaS(High-Throughput Computing as a Service) which can leverage national distributed computing resources in Korea to support these challenging HTC applications and describe the details of our system architecture, job execution scenario and case studies of various scientific applications.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1205-1214
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• 2021

Edge Computing is used as a solution to the cost problem and transmission delay problem caused by network bandwidth consumption that occurs when IoT/CPS devices are integrated into the cloud by performing artificial intelligence (AI) in an environment close to the data source. Since edge computing runs on devices that provide high-performance computation and network connectivity located in the real world, it is necessary to consider application integrity so that it is not exploited by cyber terrorism that can cause human and material damage. In this paper, we propose a technique to protect the integrity of edge computing applications implemented in a script language that is vulnerable to tampering, such as Python, which is used for implementing artificial intelligence, as container images and then digitally signed. The proposed method is based on the integrity protection technology (Docker Contents Trust) provided by the open source container technology. The Docker Client was modified and used to utilize the whitelist for container signature information so that only containers allowed on edge computing devices can be operated.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.667-680
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• 2016

As distributed computing platforms like Hadoop MapReduce have been developed, it is necessary to perform the conventional query processing techniques, which have been executed in a single computing machine, in distributed computing environments efficiently. Especially, studies on similarity join query processing in distributed computing environments have been done where similarity join means retrieving all data pairs with high similarity between given two data sets. But the existing similarity join query processing schemes for distributed computing environments have a problem of skewed computing load balance between clusters because they consider only the data transmission cost. In this paper, we propose Matrix-based Load-balancing Algorithm for efficient similarity join query processing in distributed computing environment. In order to uniform load balancing of clusters, the proposed algorithm estimates expected computing cost by using matrix and generates partitions based on the estimated cost. In addition, it can reduce computing loads by filtering out data which are not used in query processing in clusters. Finally, it is shown from our performance evaluation that the proposed algorithm is better on query processing performance than the existing one.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.10
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• pp.32-39
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• 2009

Most mobile devices provide limited input interfaces in order to maximize the mobility and the portability. In this paper, the author proposes a small cubic-shaped tangible input interface which tracks the location, the direction, and the velocity using MEMS sensor technology to overcome the physical limitations of the poor input devices in mobile computing environments. As the preliminary phase for implementing the proposed tangible input interface, the prototype design and implementation methods are described in this paper. Various experiments such as menu manipulation, 3-dimensional contents control, and sensor data visualization have been performed in order to verify the validity of the proposed interface. The proposed tangible device enables direct and intuitive manipulation. It is obvious that the mobile computing will be more widespread and various kinds of new contents will emerge in near future. The proposed interface can be successfully employed for the new contents services that cannot be easily implemented because of the limitation of current input devices. It is also obvious that this kind of interface will be a critical component for future mobile communication environments. The proposed tangible interface will be further improved to be applied to various contents manipulation including 2D/3D games.