• Journal of Information Processing Systems
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• v.7 no.4
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• The Journal of Korean Association of Computer Education
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• v.12 no.4
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• pp.65-75
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• 2009

The result verification is necessary to support a guarantee for the correctness of the task results be executed by any unspecified resources in desktop grid environments. Typically, voting-based and trust-based result verification schemes have been used in the environments. However, these suffer from two potential problems: waste of resources due to redundant replicas of each task and increase in turnaround time due to the inability to deal with a dynamic changeable execution environment. To overcome these problems, we propose a fuzzy inference-based replication scheme which can adaptively determine the number of replicas per task by using both trusty degree and result return probability of resources. Therefore our proposal can reduce waste of resources by determining the number of replicas meeting with a dynamic execution environment of desktop grids, not to mention an enhancement of turnaround time for entire asks. Simulation results show that our scheme is superior to other ones in terms of turnaround time, the waste of resources, and the number of re-replications per task.

• 한국전산유체공학회:학술대회논문집
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• 2006.10a
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• pp.210-210
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• 2006

IT technologies(Chips, Grid and e-Science) are rapidly changed from 1965. In 1965, Intel co-founder Gordon Mooresaq the future. His prediction popularly known as Moore's law, state that the computer chips double in power every 18 months Grid computing offers a model for solving massive computational problems by making use of the unused resources of large numbers of disparate, often desktop, computers treated as a virtual cluster embedded in a distributed telecommunications infrastructure. In this paper, I will discuss current status of supercomputing technology and haw we can use these on CFD. Functionally, one can classify Grids into several types:

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.429-439
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• 2006

A desktop grid, which is a computing grid composed of idle computing resources in a large network of desktop computers, is a promising platform for compute-intensive distributed computing applications. However, due to reliability and unpredictability of computing resources, effective scheduling of parallel computing applications on such a platform is a difficult problem. This paper proposes a new scheduling method aimed at reducing the total execution time of a parallel application on a desktop grid. The proposed method is based on utilizing the histories of execution behavior of individual computing nodes in the scheduling algorithm. In order to test out the feasibility of this idea, execution trace data were collected from a set of 40 desktop workstations over a period of seven weeks. Then, based on this data, the execution of several representative parallel applications were simulated using trace-driven simulation. The simulation results showed that the proposed method improves the execution time of the target applications significantly when compared to previous desktop grid scheduling methods. In addition, there were fewer instances of application suspension and failure.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.176-178
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• 2015

데스크톱 그리드에서는 휘발성과 이질성과 같은 동적 특성을 갖는 자원의 자율적인 수행에 의해 얻어진 작업 결과의 검증이 중요하다. 이를 위해, 본 논문에서는 자원의 동적 특성을 신뢰도와 결과반환확률로 정의하고 k-means 클러스터링 알고리즘을 적용하여 자원들을 자원 그룹으로 분류하고, 분류된 자원 그룹에 따라 작업의 복제수를 결정하는 자원 클러스터링 기반의 컬과 검증 기법을 제안한다.