• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.31-40
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• 2012

u-GIS DSMSs have been researched to deal with various sensor data from GeoSensors in ubiquitous environment. Also, they has been more important for high availability. The data from GeoSensors have some characteristics that increase explosively. This characteristic could lead memory overflow and data loss. To solve the problem, various load shedding methods have been researched. Traditional methods drop the overloaded tuples according to a particular criteria in a single server. Tuple deletion sensitive queries such as aggregation is hard to satisfy accuracy. In this paper a dual processing load shedding method is suggested to improve the accuracy of aggregation in clustering environment. In this method two nodes use replicated stream data for high availability. They process a stream in two nodes by using a characteristic they share stream data. Stream data are synchronized between them with a window as a unit. Then, processed results are merged. We gain improved query accuracy without data loss.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.45-50
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• 2019

With the gradual advancement of IT, passive work processes are automated and the overall quality of life has greatly improved. This is made possible by the formation of an organic topology between a wide variety of real-life smart devices. To serve these diverse smart devices, businesses or users are using the cloud. The services in the cloud are divided into Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). SaaS runs on PaaS, and PaaS runs on IaaS. Since IaaS is the basis of all services, an algorithm is required to operate virtualization resources efficiently. Among them, desktop resource virtualization is used for resource high availability of unused state time of existing desktop PC. Clustering of hierarchical structures is important for high availability of these resources. In addition, it is very important to select a suitable algorithm because many clustering algorithms are mainly used depending on the distribution ratio and environment of the desktop PC. If various attempts are made to find an algorithm suitable for desktop resource virtualization in an operating environment, a great deal of power, time, and manpower will be incurred. Therefore, this paper proposes a resource clustering simulator for cluster selection of desktop virtualization. This provides a clustering simulation to properly select clustering algorithms and apply elements in different environments of desktop PCs.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.30-39
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• 2012

In these day, some of IT venders already were going to cloud computing market, as well they are going to expand their territory for the cloud computing market through that based on their hardware and software technology, making collaboration between hardware and software vender. Distributed file system is very mainly technology for the cloud computing that must be protect performance and safety for high levels service requests as well data store. This paper introduced distributed file system for cloud computing and how to use this theory such as memory database, Hadoop file system, high availability database system. now In the market, this paper define a very large distributed processing architect as a reference by kind of distributed file systems through using technology in cloud computing market.

• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.41-53
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• 2001

Multi-distributed web cluster model built for high availability E-Business model exposes internal system nodes on its structural characteristics and has a potential that normal job performance is impossible due to the intentional prevention and attack by an illegal third party. Therefore, the security system which protects the structured system nodes and can correspond to the outflow of information from illegal users and unfair service requirements effectively is needed. Therefore the suggested distributed invasion detection system is the technology which detects the illegal requirement or resource access of system node distributed on open network through organic control between SC-Agents based on the shared memory of SC-Server. Distributed invasion detection system performs the examination of job requirement packet using Detection Agent primarily for detecting illegal invasion, observes the job process through monitoring agent when job is progressed and then judges the invasion through close cooperative works with other system nodes when there is access or demand of resource not permitted.

• Database Research
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• v.34 no.3
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• pp.58-68
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• 2018

Distributed computing helps to efficiently store and process large data on a cluster of multiple machines. The performance of distributed computing is greatly influenced depending on the state of the servers constituting the distributed system. In this paper, we propose a self-diagnosis system that collects log data in a distributed system, detects anomalies and visualizes the results in real time. First, we divide the self-diagnosis process into five stages: collecting, delivering, analyzing, storing, and visualizing stages. Next, we design a real-time self-diagnosis system that meets the goals of real-time, scalability, and high availability. The proposed system is based on Apache Flume, Apache Kafka, and Apache Storm, which are representative real-time distributed techniques. In addition, we use simple but effective moving average and 3-sigma based anomaly detection technique to minimize the delay of log data processing during the self-diagnosis process. Through the results of this paper, we can construct a distributed real-time self-diagnosis solution that can diagnose server status in real time in a complicated distributed system.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.1
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• pp.27-38
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• 2011

The distributions of phytoplankton assemblages and environmental factors in Jinhae Bay and their relationships were investigated to estimate the potential limiting nutrient for phytoplankton growth and community structure. In situ algal bioassay experiments were also conducted to assess the species-specific characteristics in phytoplankton responses under different nutrient conditions (control, N(+) and P(+) treatment). During the study periods, bacillariophyceae and cryptophyceae occupied more than 90% of total phytoplankton assemblages. Phytoplankton standing crops in the inner part of Masan Bay were higher than that of Jinhae Bay. The DIN:DIP ratio, pH and transparency showed the significant positive correlation with phytoplankton biomass. According to cluster and multidimensiolnal scaling (MDS) analysis based on phytoplankton community data from each station, the bay was divided into three groups. The first group included stations from the south-western part of Jinhae bay where cryptophyta species were dominated. The second group was distinguished from inner stations in Masan Bay. These stations showed low transpancy and high DIN:DIP ratio. The other cluster included the stations from the eastern part and central part of Jinhae Bay, which was characterized by the high DSi:DIP ratio and dominant of diatom species. Phosphorous (P) was limited in Masan Bay due to significantly increases in the phytoplankton abundances. Based on stoichiometric limitation and algal bio-assay in Jinhae Bay, nitrogen (N) was a major limiting factor for phytoplankton production. However, silicate (Si) was not considered as limiting factor, since Si/DIN and Si/P ratio and absolute concentration of nutrient did not create any potential stoichiometric limitation in the bay. This implies that high Si availability in winter season contributes favorably to the maintenances of diatom species.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.79-91
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• 2008

Recently, with highly Interest In Location-Based Service(LBS) utilizing location data of moving objects, the GALIS(Gracefully Aging Location Information System) which is a cluster-based distributed computing architecture was proposed as a more efficient location management system of moving objects. In the SLDS(Short-term location Data Subsystem) which Is a subsystem of the GALIS, since the SDP(Short-term Data Processor) Master transmits current location data and queries to every SDP Worker, the SDP Master reassembles and sends query results produced by SDP Workers to the client. However, the services are suspended during the SDP Master under failure and the response time to the client is increased if the load is concentrated on the SDP Master. Therefore, in this paper, the extended SLDS was designed and implemented to solve these problems. Though one SDP Master is under failure, the other can provide the services continually, and so the extended SLDS can guarantee the high reliability of the SLDS. The extended SLDS also can reduce the response time to the client by enabling two SDP Masters to perform the distributed query processing. Finally, we proved high reliability and high availability of the extended SLDS by implementing the current location data storage, query processing, and failure takeover scenarios. We also verified that the extended SLDS is more efficient than the original SLDS through the query processing performance evaluation.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.211-219
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• 2013

The analysis method using Big Data has evolved based on the Big data Management Technology. There are quite a few researching institutions anticipating new era in data analysis using Big Data and IT vendors has been sided with them launching standardized technologies for Big Data management technologies. Big Data is also affected by improvements of IT gadgets IT environment. Foreran by social media, analyzing method of unstructured data is being developed focusing on diversity of analyzing method, anticipation and optimization. In the past, data analyzing methods were confined to the optimization of structured data through data mining, OLAP, statics analysis. This data analysis was solely used for decision making for Chief Officers. In the new era of data analysis, however, are evolutions in various aspects of technologies; the diversity in analyzing method using new paradigm and the new data analysis experts and so forth. In addition, new patterns of data analysis will be found with the development of high performance computing environment and Big Data management techniques. Accordingly, this paper is dedicated to define the possible analyzing method of social media using Big Data. this paper is proposed practical use analysis for social media analysis through data mining analysis methodology.

• Journal of the Korean Regional Science Association
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• v.6 no.2
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• pp.123-147
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• 1990

This paper examines the changing geography of producer service industries in the 1980s. The foci of this study are to analyze the regional distribution of each producer services, and to reveal the spatial linkage of producer services. Further this paper asserts the potential role of producer services for reducing the potential endogenous development in the periphery. During the 1981-86 period, producer service industries grew more rapidly than other service sectors and manufacturing sector. The main reason of the raid growth of producer services is attributable to an increase in demand for intermediate services from manufacturing firms. In order to compete an increasingly complex business environment, firms have expanded the amount of effort devoted to activities such as planning, coordination and control, and consequently have increased their use of producer services. The most distinctive feature of the location of producer services is spatial concentration into Seoul and surrounding region. Especially the degree of the concentration o business services into the Capital Region has been accelerating during the 1990s. The pattern of employment growth and regional distribution of producer services show a clear core / periphery disparity. Much of the regional inequality in producer services is largely due to variation in demand associated with the pattern of corporation headquarters with the pattern of corporation headquarters and branch plants location with large manufacturing firms. The analysis of spatial division of labor reflects that producer services are related to the location of headquarters in manufacturing industry. Headquarters in manufacturing firms and business service firms tend to cluster each other. Most of the headquarters spatially separated from branch offices are clustered heavily in Seoul. Especially headquarters of business services and insurance services are overwhelmingly concentrated into Seoul. The firms whose headquarters are located in Seoul have a linkage pattern on a nationwide scale. It is viewed have little potential for generating local multiplier effects and regional development. In the light of the result of this study, producer services are not likely to disperse soon to peripheral regions. Consequently the absence of policies directed at enhancing producer sevice in the periphery, concentration tendency would continue to reinforce the core's dominance at the expense of peripheral regions. From a regional perspective, the quality of a region's producer service sector is a key determinant of economic growth, since manu industrial location decisions are influenced by the differential availability of producer services among regions. Poor performance of producer services in peripheral regions seemed to be linked to the region's manufacturing base. Low-wage, standardized branch plants are not likely to induce the growth in knowledge intensive services associated with high-technology corporate headquarters. Producer services may help to create and attract new business including manufacturing firms, and also to enhance the productivity and competitiveness of local firms. Therefore the provision of service producing activities would be lead not only to generate and retain endogenous development but also to attract external firms, especially small and medium sized firms which have a lower propensity of internalized services. Hence, it may be more efficient to create and expanse new locally owned producer services rather than to attract branch plants of mult-locational firms in order to make indigenous economic development.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1529-1532
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• 2003

최근 인터넷과 모바일 시스템이 급속히 발달함에 따라 이를 통하여 지리정보와 같은 공간데이터를 제공하는 서비스가 증가하였다. 이는 대용량 데이터에 대한 관리 및 빠른 처리와 급증하는 사용자에 대한 높은 동시처리량 및 높은 안정성을 요구하였고, 이를 해결하기 위하여 비공유 공간 데이터베이스 클러스터가 개발되었다. 비공유 공간 데이터베이스 클러스터는 고가용성을 위한 구조로서 문제가 발생할 경우 다른 백업노드가 대신하여 서비스를 지속시킨다. 그러나 기존의 비공유 공간 데이터베이스 클러스터는 클러스터 구성에 대한 회복을 위하여 로그를 계속 유지하므로 로그를 남기기 위해 보통의 질의처리 성능이 저하되었으며 로그 유지를 위한 비용이 증가하였다. 또한 노드단위의 로그를 갖기 때문에 클러스터 구성에 대한 회복이 직렬적으로 이루어져 고가용성을 위한 빠른 회복이 불가능 하였다. 따라서 본 논문에서는 비공유 공간 데이터베이스 클러스터에서 고가용성을 위한 병렬 회복 기법을 제안한다. 이를 위해 클러스터 구성에 대한 회복을 위한 클러스터 로그를 정의한다. 정의된 클러스터 로그는 마스터 테이블이 존재하는 노드에서 그룹내 다른 노드가 정지된 것을 감지할 때 남기기 시작한다. 정지된 노드는 자체회복을 마친 후 클러스터 구성에 대한 회복을 하는 단계에서 존재하는 복제본 테이블 각각에 대한 클러스터 로그를 병렬적으로 받아 회복을 한다. 따라서 정지된 노드가 발생할 경우에만 클러스터 로그를 남기므로 보통의 질의처리의 성능 저하가 없고 클러스터 로그 유지 비용이 적으며, 클러스터 구성에 대한 회복시 테이블단위의 병렬적인 회복으로 대용량 데이터인 공간데이터에 대해 빠르게 회복할 수 있어 가용성을 향상시킨다.들을 문법으로 작성하였으며, PGS를 통해 생성된 어휘 정보를 가지고 스캐너를 구성하였으며, 파싱테이블을 가지고 파서를 설계하였다. 파서의 출력으로 AST가 생성되면 번역기는 AST를 탐색하면서 의미적으로 동등한 MSIL 코드를 생성하도록 시스템을 컴파일러 기법을 이용하여 모듈별로 구성하였다.적용하였다.n rate compared with conventional face recognition algorithms. 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며 그 유의성이 움직임 보정 전에 비하여 낮음을 알 수 있었다. 결론: 뇌활성화 과제 수행시에 동반되는