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Realistic Modeling of Resources for a Large-Scale Computational Grid System

机译:大型计算网格系统的资源现实建模

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To build a large-scale computational grid resource model with realistic characteristics, this paper proposes a statistical remedy to approximate the distributions of computational and communicational abilities of resources. After fetching the source data of resources including computing devices and networks from the real world, the gamma and normal distributions are employed to approximate probabilities for the ability distribution of grid resources. With this method, researchers can supply the computational grid simulators with required parameters relating to computational and communicational abilities. The experiment result shows that proposed methodology can lead to a better precision according to the error measurement of the simulated data and its source. The proposed method can support existing modern grid simulators with a high-precision resource model which can consider the characteristics of distribution for its computational and communicational abilities in the grid computing environment.
机译:为了建立具有现实特征的大规模计算网格资源模型,本文提出了一种统计方法来近似计算资源的计算能力和通信能力。从现实世界中获取包括计算设备和网络在内的资源的源数据之后,可以使用伽马分布和正态分布来近似估计网格资源的能力分布的概率。使用这种方法,研究人员可以为计算网格模拟器提供与计算和通信能力有关的所需参数。实验结果表明,根据仿真数据及其来源的误差测量结果,所提出的方法可以提高精度。所提出的方法可以使用高精度资源模型支持现有的现代网格模拟器,该资源模型可以考虑其在网格计算环境中的计算和通信能力的分布特征。

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