• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.77-83
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• 2015

The storage and retrieval of multimedia data is becoming increasingly important in many application areas including record management, video(CCTV) management and Internet of Things (IoT). In these applications, the files containing multimedia that need to be stored and managed is tremendous and constantly scaling. In this paper, we propose a technique to retrieve a very large number of files, in multimedia format, using the Hadoop Framework. Our strategy is based on the management of metadata that describes the characteristic of files that are stored in Hadoop Distributed File System (HDFS). The metadata schema is represented in Hbase and looked up using SQL On Hadoop (Hive, Tajo). Both the Hbase, Hive and Tajo are part of the Hadoop Ecosystem. Preliminary experiment on multimedia data files stored in HDFS shows the viability of the proposed strategy.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.68-70
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• 2013

대량의 데이터를 효과적으로 저장하고 관리하기 위해서 클라우드 스토리지 시스템에서는 분산 파일 시스템 기술이 이용되고 있다. 그러나 데이터가 증가함에 따라 분산 파일 시스템을 이용함에도 스토리지 확장 비용이 증가하게 된다. 본 논문에서는 분산 파일 시스템의 스토리지 확장 비용을 줄이기 위해서 우리는 중복제거 파일 시스템을 적용한 분산 파일 시스템에서의 청크 배치 기법을 제안한다. 오픈 소스 기반의 분산 파일 시스템인 MooseFS 에 중복제거 파일 시스템인 lessfs 를 적용함으로써 스토리지의 가용공간을 늘릴 수 있으며, 이는 스토리지 확장 비용을 줄이는 효과를 가져온다. 또한, 동일한 청크는 같은 청크 서버에 배치 시킴으로써 중복제거 기회를 높인다. 실험을 통해서 제안 시스템의 중복제거량과 성능에 대해서 평가한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.115-117
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• 2013

빅데이터 시대가 도래하고 네트워크가 발달함에 따라 다수의 클라이언트와 서버가 통신하며 사용하는 데이터량이 급증하고 있다. 과도한 데이터 부하를 해결하는 방법 중 여러 서버로 부하를 분산하는 기법을 로드밸런싱이라고 하며 이 기법에 따라 데이터가 서버에 분산되는 방식이 달라진다. 본 논문에서는 현재 사용중인 다양한 로드밸런싱 기법에 대해 분석하고 보다 효율적인 기법을 제안한다. 그리고 오픈소스 기반의 분산 파일 시스템 중 하나인 Moose File System에 제안한 기법을 적용한 경우의 효과에 대해 논의한다.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.49-56
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• 2006

A special feature of P2P distributed system isn't always the guarantee of online status for peers. In other words we want to download the file from the peer when we use the P2P system but it sometimes caused this system to fail the download. Many studies to resolve this problem depend on re-transmission method. It caused to lower performance so we have to resolve this problem. In this study, we analysis the average usage time of P2P application user and raise the resource transmission guarantee to apply the selection criteria of resource supplier. Moreover the combinations of distributed object replication techniques, the role to enhance the data transmission opportunity of high popularity resource. will cause this search algorithm to advance.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.975-982
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• 2004

In current P2P concept, pure P2P and Hybrid P2P structures are used commonly. Gnutella and Ktella are forms of pure P2P. and forms of Hybrid P2P are innumerable. File searching models exist in these models. These models provide group management for file sharing, searching and indexing. The general file sharing model is good at maintaining connectivity. However, it is defective in group management. Therefore, this study approaches hierarchical structure in file sharing models through routing technique and backup system. This system was designed so that the user was able to maintain group efficiency and connection reliability in large-scale network.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.233-239
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• 2014

Ultra high-resolution content, the file size is very large, therefore existing encoding techniques, it is not possible to transmit via the network. Efficient use of the network encoder HEVC corporation can be transferred. Compression requires a lot of time because it requires a distributed transcoding system. Distributed transcoding system is a distributed data store, and then encoded using a large number of nodes. The disadvantage of distributed transcoding system for distributed information is exposed or vulnerable to attack by internal managers. In this paper, when the super high definition content transcoding, distributed transcoding system does not guarantee the confidentiality of the problem to solve. We are using SNA, HEVC encoded content data encrypted using the secret distributing scheme was. Consequently, secure shared transcoding is possible, the internal administrator could prevent the attack.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.70-75
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• 2018

Smart Factory is an intelligent factory that can enhance productivity, quality, customer satisfaction, etc. by applying information and communications technology to the entire production process including design & development, manufacture, and distribution & logistics. The precise amount of data generated in a smart factory varies depending on the factory's size and state of facilities. Regardless, it would be difficult to apply traditional production management systems to a smart factory environment, as it generates vast amounts of data. For this reason, the need for a distributed big-data processing system has risen, which can process a large amount of data. Therefore, this article has designed a Gluster File System (GlusterFS)-based distributed big-data processing system that can be used in a smart factory environment. Compared to existing distributed processing systems, the proposed distributed big-data processing system reduces the system load and the risk of data loss through the distribution and management of network traffic.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.76-87
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• 2009

Most distributed models have been developed for data interchange between model for hydrological analysis and GIS(Geographic Information System). And some interface systems between them have been developed to operate the model conveniently. This study is about developing integrated system between model and GIS not coupled system based on file interchange or interface system. In this study, HyGIS-GRM which is integrated system between GRM(Grid based Rainfall-runoff Model) which is physically based distributed rainfall-runoff model and HyGIS(Hydro Geographic Information System) have been developed. HyGIS-GRM can carry out all the processes from preparing input data to appling them to model in the same system, and this operation environment can improve the efficiency of running the model and analyzing modeling results. HyGIS-GRM can provide objective modeling environment through establishing the process of integrated operation of GIS and distributed model, and we can obtain fundamental technologies for developing integrated system between GIS and water resources model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.718-723
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• 2005

In this paper, we propose the collaborative design system with which we can simultaneously modify the actual 3D CAD model by the remote control and have interaction on it. It enables instantaneous decision making among the multiple disciplines in distributed locations using the function of simultaneous access and video conference. It also provides the method of managing the consistency between design entities. This system consists of Collaborative Management Server, File Server, Solid Modeler Client, Remote Control Module and Client Module.

• Journal of Multimedia Information System
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• v.7 no.2
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• pp.125-136
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• 2020

Nowadays, cloud computing is becoming more popular among companies. However, the characteristics of cloud computing such as a virtualized environment, constantly changing, possible to modify easily and multi-tenancy with a distributed nature, it is difficult to perform attack detection with traditional tools. This work proposes a solution which aims to collect traffic packets data by using Flume and filter them with Spark Streaming so it is possible to only consider suspicious data related to HTTP Slow Rate Denial-of-Service attacks and reduce the data that will be stored in Hadoop Distributed File System for analysis with the FP-Growth algorithm. With the proposed system, we also aim to address the difficulties in attack detection in cloud environment, facilitating the data collection, reducing detection time and enabling an almost real-time attack detection.