• Journal of Digital Contents Society
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• v.12 no.3
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• pp.319-327
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• 2011

Cloud computing is the probated transmission-platform that provide the enterprise or individual with efficient and cost-effective IT service on internet. Cloud computing serve as data or computing is moved from desktop or portable PC to the massive data center. Searching for the services offered by cloud computing indicates that their current service feature needs to be improved to satisfy current and future customers. This study attempted to satisfy this need by identifying the service's features for the cloud computing service environment through qualitative approaches. Finally, we classify into seven features(Security, Reliability, Availability, Inter-operating, Economic, Intellectual Property) of cloud computing service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2764-2783
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• 2012

Network virtualization supports future Internet environments and cloud computing. Virtualization can mitigate many hardware restrictions and provide variable network topologies to support variable cloud services. Owing to several advantages such as low cost, high flexibility, and better manageability, virtualization has been widely adopted for use in network virtualization platforms. Among the many issues related to cloud computing, to achieve a suitable cloud service quality we specifically focus on network and performance isolation schemes, which ensure the integrity and QoS of each virtual cloud network. In this study, we suggest a virtual network platform that uses Xen-based virtualization, and implement multiple virtualized networks to provide variable cloud services on a physical network. In addition, we describe the isolation of virtual networks by assigning a different virtualized network ID (VLAN ID) to each network to ensure the integrity of the service contents. We also provide a method for efficiently isolating the performance of each virtual network in terms of network bandwidth. Our performance isolation method supports multiple virtual networks with different levels of service quality.

• Smart Structures and Systems
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• v.29 no.1
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• pp.141-151
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• 2022

In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.775-783
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• 2017

As interest in cloud computing grows, the number of users using cloud computing services is increasing. However, cloud computing technology has been steadily challenged by security concerns. Therefore, various security breaches are springing up to enhance the system security for cloud services users. In particular, research on detection of malicious VM (Virtual Machine) is actively underway through the introspecting virtual machines on the cloud platform. However, memory analysis technology is not used as a monitoring tool in the environments where multiple virtual machines are run on a single server platform due to obstructive monitoring overhead. As a remedy to the challenging issue, we proposes a computationally efficient instance memory introspection scheme to minimize the overhead that occurs in memory dump and monitor it through a partial memory monitoring based on the well-defined kernel memory map library.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.351-359
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• 2009

Recently with increase of data in the Internet, platform technologies that can process huge data effectively such as Google platform and Hadoop are regarded as worthy of notice. In this kind of platform, there exist network I/O overheads to send task outputs due to the MapReduce operation which is a programming model to support parallel computation in the large cluster system. In this paper, we suggest applying of TIPC (Transparent Inter-Process Communication) protocol for reducing network I/O overheads and increasing network performance in the distributed computing environments. TIPC has a lightweight protocol stack and it spends relatively less CPU time than TCP because of its simple connection establishment and logical addressing. In this paper, we analyze main features of the Hadoop-based distributed computing system, and we build an experimental model which can be used for experiments to compare the performance of various protocols. In the experimental result, TIPC has a higher bandwidth and lower CPU overheads than other protocols.

• Spatial Information Research
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• v.22 no.5
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• pp.1-8
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• 2014

Globally, mobile, cloud computing or big data are the recent marketable key terms. These trend technologies or paradigm in the ICT (Information Communication Technology) fields exert large influence on the most application fields including geo-spatial applications. Among them, cloud computing, though the early stage in Korea now, plays a important role as a platform for other trend technologies uses. Especially, mobile cloud, an integrated platform with mobile device and cloud computing can be considered as a good solution to overcome well known limitations of mobile applications and to provide more information processing functionalities to mobile users. This work is a case study to design and implement the mobile application system for geo-spatial image filtering processing operated on mobile cloud platform built using OpenStack and various open sources. Filtering processing is carried out using R environment, recently being recognized as one of big data analysis technologies. This approach is expected to be an element linking geo-spatial information for new service model development and the geo-spatial analysis service development using R.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.190-192
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• 2019

Not only learners majoring in computer science, but also non-engineered learners want to implement their ideas as apps through real-life problems. In response, first-year university students with little experience in creating apps studied how to develop mobile platform apps to improve computing thinking skills. We applied the teaching and learning procedures of the Discovery-Design-Development among the software teaching and learning models, and used Android Studio Unified Development Environment (IDE) as a development tool to design mobile platform app development projects and assess whether they helped improve computing thinking skills. The application of the designed teaching and learning method found that the project output was implemented as an app through emulator, which gave students high interest in class and satisfaction, and was effective in improving their computing thinking ability.

• KNOM Review
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• v.23 no.1
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• pp.51-62
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• 2020

Open IoT platform that shares communication infrastructure and provides cloud resources can flexibly reduce development period and cost of smart service. In this paper, as an open IoT platform, we propose a virtual IoT system based on edge computing that implements a virtual IoT device for a physical IoT device and allows service developers to interact with the virtual device. A management server in the edge cloud, near the IoT physical device, manages the creation, movement, and removal of virtual IoT devices corresponding to the physical IoT devices. This paper define the operations of the management server, the physical IoT device, and the virtual IoT device, which are major components of the virtual IoT system, and design the communication protocol required to perform the operations. Finally, through simulations, this paper evaluate the performance of the edge computing based virtual IoT system by confirming that each component performs the defined states and operations as designed.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.181-186
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• 2014

Web data mining aims at discovering useful knowledge from various Web resources. There is a growing trend among companies, organizations, and individuals alike of gathering information through Web data mining to utilize that information in their best interest. In science, cloud computing is a synonym for distributed computing over a network; cloud computing relies on the sharing of resources to achieve coherence and economies of scale, similar to a utility over a network, and means the ability to run a program or application on many connected computers at the same time. In this paper, we propose a new system framework based on the Hadoop platform to realize the collection of useful information of Web resources. The system framework is based on the Map/Reduce programming model of cloud computing. We propose a new data mining algorithm to be used in this system framework. Finally, we prove the feasibility of this approach by simulation experiment.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.5-7
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• 2014

일반적인 가상화 플랫폼에서는 가상화 소프트웨어가 소프트웨어적으로 에뮬레이션하여 제공하는 가상 I/O 장치들을 가상 플랫폼에서 사용한다. 소프트웨어 에뮬레이션 기반 I/O 장치들을 사용하는 가상 플랫폼들은 성능이 떨어지고 고사양의 응용 프로그램을 지원할 수 없는 문제점을 가지고 있다. 본 논문에서는 해당 문제점을 극복하기 위해 PCI 기반 하드웨어 장치들을 가상 플랫폼에 직접 할당하여 고품질의 가상 플랫폼을 제공하는 기술을 설계 및 구현한다.