• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.359-368
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• 2001

The prototype of forest fire management system on Web was studied. In the architecture of this system, one of the most important concerns is to handle load upcoming to Web Server so that it provides Web service without any delay or failure. In order to solve this problem, the agent is designed on dispatcher in a Web server cluster and implemented to distribute load dynamically by considering the information related to load coming to the Web Server such as the number of connection to the Map Server. The proposed forest fire management system has user-friendly interface with the GIS mapping functionality by selecting Map Objects Internet Map Server (MO IMS) as Map Server and is implemented using Java as programming language.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.593-596
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• 2010

본 논문에서는 선형적인 무선 센서 네트워크에서 지연 및 신뢰성을 고려한 클러스터 기반의 멀티홉 라우팅 알고리즘을 제안한다. 제안한 알고리즘은 선형적인 네트워크 환경에서 전송 지연시간 및 Single Point Of Failure 를 해결하기 위해 짝수 ID 노드일 경우 다음 짝수 ID 노드로 전송하고, 홀수 ID 노드일 경우 다음 ID 노드로 데이터를 전송하는 방법을 사용한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.2-4
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• 2024

한국과학기술정보연구원(이하 KISTI)의 국가슈퍼컴퓨팅센터에서는 슈퍼컴퓨터 5호기인 Nurion과 Neuron 시스템을 구축하여 국내 연구자들에게 서비스하고 있다. 이 중에서 Neuron 시스템은 GPU 클러스터 시스템으로 SLURM Batch Scheduler를 이용하여 공동활용서비스를 제공하고 있다. 본 논문에서는 Neuron에서 사용 중인 SLURM Batch Scheduler와 리눅스의 crontab 기능을 이용하여 소프트웨어 장애가 발생한 계산노드를 자동으로 복구시키는 기능을 구현하여 장애처리 대기시간을 단축시키는 기법에 대해서 소개한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.791-800
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• 2010

Recently wireless sensor networks as a field of ubiquitous computing technology was in the limelight. To use and collect the necessary information, Sink node mobility is essential. TTDD(Two-Tier Data Dissemination) proposed most common technique associated with Mobile sink node in wireless sensor networks, but issues exist that the use of many control packet falls into the energy efficiency. The technique for solving problems is Cluster-Based Energy-efficient Routing protocol (CBPER). But CBPER does not transmit the data correctly to sink node or source node. In this paper, we propose An Energy-Efficient Routing Protocol based on Static Grid using mobile sink nodes in order to solve the data transmission failure and reduce the energy consumption in Wireless Sensor Networks. We have evaluated it with the NS-2 simulator. Our results show that the proposed protocol saves the energy consumption up to 34% in comparison with CBPER. We also prove that the proposed protocol can transmit more accurate data to the sink de than CBPER.

• Journal of Global Scholars of Marketing Science
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• v.15 no.2
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• pp.123-140
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• 2005

Recently, one of the issues that are significantly considered is to keep Changwon F3 car racing. In most existing studies, however, there is shortage of opinions for understanding the reactions of the host community. The question addressed in this paper is what are the underlying factors that affect which inhibitors are likely to be discussed by the host community for car racing. Survey collected from 299 participants in Changwon city were analyzed to test their reactions. Through the empirical study, several research findings emerged. The results indicate that (1) the event seeker, the drive seeker, and the hard internal seeker were significant discriminant factors to separate inhibitors from the host community, (2) the significant differences between the recognition of demographic characteristics and that of negative effects, (3) the significant level between cluster groups(overcontrolled, resilient, undercontrolled) and negative effects is found. The findings also provide implications for practice on several fronts, which is to understand the reaction of the host community to F3 car racing, and for the event planner to reduce complaints.

• Convergence Security Journal
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• v.13 no.3
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• pp.17-23
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• 2013

Clustering is required to configure clustering interdependent structural technology. Clustering handles variable workloads or impede continuity of service to continue operating in the event of a failure. Long as high-availability clustering feature focuses on server operating systems. Active-standby state of two systems when the active server fails, all services are running on the standby server, it takes the service. This function switching or switchover is called failover. Long as high-availability clustering feature focuses on server operating systems. The cluster node that is running on multiple systems and services have to duplicate each other so you can keep track of. In the event of a node failure within a few seconds the second node, the node shall perform the duties broken. Structure for high-availability clustering efficiency should be measured. System performance of infrastructure systems performance, latency, response time, CPU load factor(CPU utilization), CPU processes on the system (system process) channels are represented.

• Wind and Structures
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• v.39 no.1
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.314-317
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• 2004

With the advance of network and software infrastructure, Grid-computing technology on a cluster of heterogeneous computing resources becomes pervasive. Grid computing is required a coordinated use of an assembly of distributed computers, which are linked by WAN. As the number of grid system components increases, the probability of failure in the grid computing is higher than that in a traditional parallel computing. To provide the robustness of grid applications, fault detection is critical and is essential elements in design and implementation. In this paper, a OGSA based process fault-detection services presented to provide high reliability under low network traffic environment.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.136-145
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• 2009

Factors influencing shear behavior of granular material include particle size, shape, distribution, relative density, particle crushing, etc. In this study, these factors are characterized by viewpoint of shear behavior using numerical analysis based on DEM. Geometrical particle shape is represented by a combination of small circular particles and influence of particle shape on crushing is studied through relative comparisons between clump (uncrushable) and cluster (crushable) models which are modeled using DEM. Also, particle shape is quantified by the dimensionless parameters such as circularity and convexity. The results indicate that particle shape indexes have a negative association with internal friction angle. Also, internal friction angle becomes reduced and failure envelop curve becomes nonlinear due to the particle crushing. It is also found that numerical results are quite good agreement with the experimental test conducted in this study.

• Journal of the Korea Society for Simulation
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• v.12 no.3
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• pp.69-81
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• 2003

To manage a cluster of distributed server systems, a number of management aspects should be considered in terms of configuration management, fault management, performance management, and user management. System performance monitoring and reporting take an important role for performance and fault management. In this paper, we present distributed system architecture modeling of a performance monitoring and reporting tool. Modeling architecture of four subsystems are introduced: node agent, data collection, performance management & report, and DB schema. The performance-related information collected from distributed servers are categorized into performance counters, event data for system status changes, service quality, and system configuration data. In order to analyze those performance information, we use a number of ways to evaluate data corelation. By using some results from a real site of a company and from simulation of artificial workload, we show the example of performance collection and analysis. Since our report tool detects system fault or node component failure and analyzes performances through resource usage and service quality, we are able to provide information for server load balancing, in short term view, and the cause of system faults and decision for system scale-out and scale-up, in long term view.