• Korea Multimedia Society
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• v.7 no.4
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• pp.103-108
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• 2003

• Korea Information Processing Society Review
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• v.10 no.1
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• pp.109-120
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• 2003

• The Journal of Korean Association of Computer Education
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• v.11 no.3
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• pp.81-89
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• 2008

The failure occurrence of resources in the grid computing is higher than in a tradition parallel computing. Since the failure of resources affects job execution fatally, fault tolerance service is essential in computational grids. And grid services are often expected to meet some minimum levels of quality of service (QoS) for desirable operation. However Globus toolkit does not provide fault tolerance service that supports fault detection service and management service and satisfies QoS requirement. Thus this paper proposes fault tolerance service to satisfy QoS requirement in computational grids. In order to provide fault tolerance service and satisfy QoS requirements, we expand the definition of failure, such as process failure, processor failure, and network failure. And we propose resource scheduling service, fault detection service and fault management service and show implement and experiment results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3134-3155
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• 2020

In this paper, we study the joint radio and computational resource allocation in the ultra-dense mobile-edge computing networks. In which, the scenario which including both computation offloading and communication service is discussed. That is, some mobile users ask for computation offloading, while the others ask for communication with the minimum communication rate requirements. We formulate the problem as a joint channel assignment, power control and computational resource allocation to minimize the offloading cost of computing offloading, with the precondition that the transmission rate of communication nodes are satisfied. Since the formulated problem is a mixed-integer nonlinear programming (MINLP), which is NP-hard. By leveraging the particular mathematical structure of the problem, i.e., the computational resource allocation variable is independent with other variables in the objective function and constraints, and then the original problem is decomposed into a computational resource allocation subproblem and a joint channel assignment and power allocation subproblem. Since the former is a convex programming, the KKT (Karush-Kuhn-Tucker) conditions can be used to find the closed optimal solution. For the latter, which is still NP-hard, is further decomposed into two subproblems, i.e., the power allocation and the channel assignment, to optimize alternatively. Finally, two heuristic algorithms are proposed, i.e., the Co-channel Equal Power allocation algorithm (CEP) and the Enhanced CEP (ECEP) algorithm to obtain the suboptimal solutions. Numerical results are presented at last to verify the performance of the proposed algorithms.

• 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.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.11-21
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• 2006

Importance of and need for grid resource management have accelerated in accordance with increasing development of grid computing. However, it is very complex to distribute and utilize resources efficiently in geographically dispersed environments. This is due to the different access policies and constraints of grid resource owners. Users request resources according to their needs. Operators of a grid computing system need to be able to monitor the system states for reflecting these demands. So, a grid computing system needs a resource management policy that monitors states of resources and then allocates resources. This paper proposes a user demand-based grid trade management model that provides an efficient resource management by the trade allocation based on a users' demand and providers' supply strategy. To evaluate performance, this paper measures increasing rate of resource trades, average response time of trades, and processing time utilization. Firstly, the average increasing rates of trade are 585.7% and 322.6% higher than an auction model and a double auction model. Secondly, the average response time of the user demand-based grid trade management model is maintained between 3 and 5 simulation time. Finally, it is found that the processing time utilization is an average of 145.4% and 118.0% higher than an auction model and a double auction model. These empirical results demonstrate the usefulness of the user demand-based grid trade management model.

• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.30-35
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• 2008

The present study has been conducted to examine the effect of grid resolution on the predicted results for electric cable fire using pyrolysis model in FDS(Fire Dynamics Simulator, version 5). The grid independent test for different grid resolutions has been performed for a PE coating cable and the grid resolution is defined by the non-dimensional characteristic length of fire and mean grid size. The calculated maximum heat release rate and mean flame spread rate were almost constant for higher grid resolution of 20${\sim}$25 and the computing time for the grid resolution takes approximately 20hours to solve flame propagation with pyrolysis model. The geometrical simplification of a electric cable dose not greatly affect on the maximum heat release rate and flame spread rate and the rectangular approximation of cable shape gives acceptable result comparing with the round cable with stepwise grid.

• 한국전산유체공학회:학술대회논문집
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• 1997.10a
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• pp.43-48
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• 1997

When computing the flow around complex three dimensional aircraft configurations, the generation of the grid is the most time consuming part. This paper presents a survey of the grid generation technique. The technique for treating problems arising in surface grid generation for complex geometries is addressed. Several example grids are shown, demonstrating the ability of the method to discretize complex geometries.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.578-584
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• 2003

본 논문에서는 인터넷 기반 P2P 네트워크를 이용한 Grid 컴퓨팅에서의 효율적인 보안 관리 모델을 제시한다. 하나는 P2P 네트워크를 이용한 에러 복구 과정과 다른 하나는 에이전트간 신뢰관계 구성 방안이다. 또한 P2P 네트워크에서 다양한 네트워크 간 보안 통신을 보장하기 위해 SOAP을 이용한 보안 메시지 프로토콜을 제안한다. 제안된 새로운 보안 관리 모델은 P2P 네트워크로 구성된 Grid 컴퓨팅 네트워크의 성능을 향상시킬 것으로 기대된다.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.21-26
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• 2008

A method for processing huge airborne laser scanned data using parallel computing and virtual grid is proposed and the method is tested by generating raster DSM(Digital Surface Model) with IDW(Inverse Distance Weighting). Parallelism is involved for fast interpolation of huge point data and virtual grid is adopted for enhancing searching efficiency of irregularly distributed point data. Processing time was checked for the method using cluster constituted of one master node and six slave nodes, resulting in efficiency near to 1 and load scalability property. Also large data which cannot be processed with a sole system was processed with cluster system.