• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.79-85
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• 2009

A sink node and its neighbor nodes spend more energy than other nodes since a stationary sink node collects data from wireless sensor networks(WSNs). For larger WSNs, the unbalanced energy of nodes causes the operation of WSNs to stop rapidly. This paper proposes a data gathering method by adapting the mobile sink to prolong the life time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient algorithm is proposed to improve the energy efficiency by delivering the message from the mobile sink to the cluster head as well as to reduce the data gathering delay, which is the disadvantage of the mobile sink. Also, The algorithm is analyzed for the energy consumption and the data gathering delay. The validity of the ananlysis result is confirmed by the simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1549-1555
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• 2009

The Relay node placement problem is one of the most important requirements for many wireless sensor networks because the lifetime of sensor networks is closely related with the placement of relay nodes which receive sensed data from sensor nodes and forward them to the base station. Relay node placement problem has focused at minimization of dissipated total energy of the sensor nodes in whole networks. However, minimum total energy causes the unbalance of consumed energy in sensor nodes due to different distances between relay nodes and sensor nodes. This paper proposes the concept of energy balance ratio and finds the locations of relay nodes using objective functions which maximize the energy balance ratio. Maximizing this ratio results in maximizing the network lifetime by minimizing the energy consumption of large-scale sensor networks. However, finding a solution to relay node placement problem is NP-hard and it is very difficult to get exact solutions. Therefore, we get approximate solutions to EBR-RNP problem which considers both energy balance ratio and relay node placement using constraint programming.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.114-121
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• 2022

In this paper, we consider a user centric clustering in order to guarantee the performance of the users in cell free multiple-input multiple-output (MIMO) network. In the user centric clustering scheme, by using large scale fading coefficients of the connected access points (APs), each user decides own cluster with the APs having the higher the large scale fading coefficients than threshold value compared to the highest large scale fading coefficient. In the determined user centric clusters, the APs design the beamformers and power allocations in the distributed manner and the APs cooperatively transmit data to users by using beamformers and power allocations. In the simulation results, we verify the performance of user centric clustering in terms of the spectral efficiency and we also find the optimal threshold value in the given configuration.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.913-916
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• 2010

Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors send data from CH (Cluster Head) and then to BS (Base Station). BCDCP works well in small-scale network but in large scale network it is not appropriated since it uses much energy for long distance wireless communication. We propose a routing protocol - Triangular Clustering Routing Protocol (TCRP) - to prolong network life time through the balanced energy consumption. TCRP selects cluster head of triangular shape. The sensor field is divided into energy level and in every level we choose one node as a gate node. This gate node collects data and sends it to the leader node. Finally the leader node sends the aggregated data to the BS. We show TCRP outperforms BCDCP with several experiments.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.89-96
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• 2015

Location-based social media data have high potential to be used in various area such as big data, location based services and so on. In this study, we applied a series of analysis methodology to figure out how the important keywords in location-based social media are spatially distributed by analyzing text information. For this purpose, we collected tweet data with geo-tag in Gangnam district and its environs in Seoul for a month of August 2013. From this tweet data, principle keywords are extracted. Among these, keywords of three categories such as food, entertainment and work and study are selected and classified by category. The spatial clustering is conducted to the tweet data which contains keywords in each category. Clusters of each category are compared with buildings and benchmark POIs in the same position. As a result of comparison, clusters of food category showed high consistency with commercial areas of large scale. Clusters of entertainment category corresponded with theaters and sports complex. Clusters of work and study showed high consistency with areas where private institutes and office buildings are concentrated.

• Journal of KIISE
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• v.43 no.1
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• pp.61-70
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• 2016

In recent years, there has been a need for techniques for large-scale ontology inference in order to infer new knowledge from existing knowledge at a high speed, and for a diversity of semantic services. With the recent advances in distributed computing, developments of ontology inference engines have mostly been studied based on Hadoop or Spark frameworks on large clusters. Parallel programming techniques using GPGPU, which utilizes many cores when compared with CPU, is also used for ontology inference. In this paper, by combining the advantages of both techniques, we propose a new method for reasoning large RDFS ontology data using a Spark in-memory framework and inferencing distributed data at a high speed using GPGPU. Using GPGPU, ontology reasoning over high-capacity data can be performed as a low cost with higher efficiency over conventional inference methods. In addition, we show that GPGPU can reduce the data workload on each node through the Spark cluster. In order to evaluate our approach, we used LUBM ranging from 10 to 120. Our experimental results showed that our proposed reasoning engine performs 7 times faster than a conventional approach which uses a Spark in-memory inference engine.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.367-374
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• 2001

Recently, LINUX cluster file systems based on the storage area network (SAN) have been developed. In those systems, without using a central file server, multiple clients sharing the whole disk storage through Fibre Channel can freely access disk storage and act as file servers. Accordingly, they can offer advantages such as availability, load balancing, and scalability. In this paper, we describe metadata management schemes designed for a new SAN-based LINUX cluster file system. First, we present a new inode structure which is better than previous ones in disk block access time. Second, a new directory structure which uses extendible hashing is described. Third, we describe a novel scheme to manage free disk blocks, which is suitable for very large file systems. Finally, we present how we handle metadata journaling. Through performance evaluation, we show that our proposed schemes have better performance than previous ones.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.268-270
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• 2006

본 논문에서는 ZigBee Alliance에서 다루어지고 있는 IEEE 802.15.4틀 기반으로 하는 USN을 위한 라우팅 프로토콜을 연구한다. 현재 ZigBee Specification v1.0의 표준에서는 AODV라우팅 프로토콜과 Hierarchical 라우팅 프로토콜을 사용하고 있다. 하지만 ZigBee Specification v1.0의 표준에서 사용하고 있는 이 두 가지 라우팅 프로토콜은 대규모의 센서네트워크에 적용하였을 때, 많은 단점들이 존재한다. 이러한 단점들은 센서네트워크가 가지고 있는 여러 가지 특성들을 고려하지 않은 일반적인 Adhoc 네트워크에서 사용하는 라우팅 프로토콜을 사용했기 때문이다. 따라서 본 논문에서는 이러한 단점들을 해결 할 수 있는 클러스터 기반의 라우팅 프로토콜을 제안한다.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.559-563
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• 2010

황해경제자유구역은 환황해권 첨단기술의 국제협력 거점 조성이라는 비전과 국제수준의 첨단기술산업 클러스터 육성, 대 중국 수출입 전진기지 및 부가가치물류 육성을 목적으로 2007년 지정되어 사업이 추진 중에 있다. 황해경제자유구역 반경 15km 이내에 7개의 산업단지가 입지하고 있어 충남 서북부지역의 산업집적도는 날로 증가하고 있는 추세이다. 그러나 이를 지원할 주요 인프라 중 하나인 물류단지 시설은 전무한 실정이며 황해경제자유구역을 포함한 충남 서부지역의 물류거점 개발은 매우 미약하다. 본 연구의 목적은 첫째, 서해안 지역 물류거점 단지 조성의 필요성을 검토하고, 둘째, 물류단지 규모 및 성격을 부여하며, 셋째, 물류단지 도입기능을 설정하고자 한다. 연구목적을 달성하기 위해 물동량 수요예측과 주변지역 연계방안을 토대로 황해경제자유구역의 배후물류단지의 필요성과 조성방안을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.455-458
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• 2003

최근 데이터가 대용량화됨에 따라 이를 저장할 파일시스템이 필요하게 되었다. 이에 별도의 서버를 두 지 않고 분산된 클라이언트가 메타데이터를 직접 관리하면서 모든 저장 장치들에 접근할 수 있는 SAN 기반 리녹스 클러스터 파일시스템의 연구가 활발히 진행 중에 있다. 그러나, 이와 같은 대규모의 파일 시스템에서 일반 UNIX 시스템과 같은 디렉토리 구조를 갖게 되면, 파일 탐색 시 순차검색으로 인하여 많은 시간이 걸리게 된다. 그리므로, 이러한 문제를 해결하고자, 본 논문에서는 SAN 기반 리녹스 클라스터 파일 시스템을 위한 확장 해싱 디렉토리와 B+ 트리 디렉토리 구조를 설계 및 구현하고, 실행 환경에 따라 적합한 구조를 선택할 수 있도록 하기 위하여 성능평가를 통해 두 디렉토리 구조를 비교 분석한다.