• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.379-394
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• 2013

Cloud computing is an evolving computing paradigm that has influenced every other entity in the globalized industry, whether it is in the public sector or the private sector. Considering the growing importance of cloud, finding new ways to improve cloud services is an area of concern and research focus. The limitation of the available Virtual Machine Load balancing policies for cloud is that they do not save the state of the previous allocation of a virtual machine to a request from a Userbase and the algorithm requires execution each time a new request for Virtual Machine allocation is received from the Userbase. This problem can be resolved by developing an efficient virtual machine load balancing algorithm for the cloud and by doing a comparative analysis of the proposed algorithm with the existing algorithms.

• ETRI Journal
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• v.36 no.6
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• pp.1008-1015
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• 2014

In this paper, we present a method for reconstructing a surface mesh animation sequence from point cloud animation data. We mainly focus on the articulated body of a subject - the motion of which can be roughly described by its internal skeletal structure. The point cloud data is assumed to be captured independently without any inter-frame correspondence information. Using a template model that resembles the given subject, our basic idea for reconstructing the mesh animation is to deform the template model to fit to the point cloud (on a frame-by-frame basis) while maintaining inter-frame coherence. We first estimate the skeletal motion from the point cloud data. After applying the skeletal motion to the template surface, we refine it to fit to the point cloud data. We demonstrate the viability of the method by applying it to reconstruct a fast dancing motion.

• 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.

• International Journal of Contents
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• v.14 no.1
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• pp.34-38
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• 2018

With the rapid growth of genomic data, new requirements have emerged that are difficult to handle with big data storage and analysis techniques. Regardless of the size of an organization performing genomic data analysis, it is becoming increasingly difficult for an institution to build a computing environment for storing and analyzing genomic data. Recently, cloud computing has emerged as a computing environment that meets these new requirements. In this paper, we analyze and compare existing distributed and parallel NGS (Next Generation Sequencing) analysis based on cloud computing environment for future research.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.183-191
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• 2020

Today, taking photos using smartphones has become an essential element of modern people. According to these social changes, modern people need a larger storage capacity, and the number of unnecessary photos has increased. To support the storage, cloud-based photo storage services from various platforms have appeared, and many people are using the services. As the number of photos increases, it is difficult for users to find the photos they want, and it takes a lot of time to organize. In this paper, we propose a cloud-based photo management service that facilitates photo management by classifying photos and recommending unnecessary photos using deep learning. The service provides the function of tagging photos by identifying what the subject is, the function of checking for wrongly taken photos, and the function of recommending similar photos. By using the proposed service, users can easily manage photos and use storage capacity efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.436-453
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• 2018

Storage cloud scheme, pushing data to the storage cloud poses much attention regarding data confidentiality. With encryption concept, data accessibility is limited because of encrypted data. To secure storage system with high access power is complicated due to dispersed storage environment. In this paper, we propose a hardware-based security scheme such that a secure dispersed storage system using erasure code is articulated. We designed a hardware-based security scheme with data encoding operations and migration capabilities. Using TPM (Trusted Platform Module), the data integrity and security is evaluated and achieved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.305-306
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• 2013

In this paper, we proposes a document summarization method using the weighting based on cloud. The proposed method can minimize the user intervention to use the relevance feedback. It also can improve the quality of document summaries because the inherent semantic of the sentence set are well reflected by term weighting derived from semantic feature using nonnegative matrix factorizaitno based cloud.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.968-969
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• 2013

In this paper, we proposes a document summarization method using the weighting based on cloud. The proposed method can minimize the user intervention to use the relevance feedback. It also can improve the quality of document summaries because the inherent semantic of the sentence set are well reflected by term weighting derived from semantic feature using nonnegative matrix factorizaitno based cloud.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.197-205
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• 2022

The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.