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IMPROVING PERFORMANCE PREDICTION OF PARALLEL AND DISTRIBUTED DISCRETE EVENT SIMULATION: A ROUGH SETS-BASED APPROACH

机译:改进的并行和分布式离散事件模拟的性能预测:一种基于粗糙集的方法

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The rapid growth of complexity of communication networks - including grids, cloud systems and services - increases the need for the use and performance prediction of parallel and distributed discrete event simulation. The paper aims at the decreasing the overall cost of simulation by improving the performance prediction of simulation particularly for the phases with uncertain and vague information. Involving rough sets-based methods, the paper introduces how the efficiency of the well known coupling factor method of the performance prediction of parallel and distributed simulation can be improved. According to the presented results, the prediction can merely be based on the maintainable lookahead feature of the designed simulation model. Using the rough set analysis, the paper also describes how the number of simulation experiments necessary for prediction can be limited without the decrease of accuracy of prediction.
机译:通信网络(包括网格,云系统和服务)复杂性的快速增长,增加了对并行和分布式离散事件模拟的使用和性能预测的需求。本文旨在通过改善仿真的性能预测来降低仿真的总体成本,特别是对于信息不确定和模糊的阶段。本文涉及基于粗糙集的方法,介绍了如何提高并行和分布式仿真的性能预测中众所周知的耦合因子方法的效率。根据给出的结果,预测只能基于所设计仿真模型的可维护超前特征。使用粗糙集分析,本文还描述了如何在不降低预测准确性的情况下限制预测所需的模拟实验的数量。

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