Flexible performance prediction of data center networks using automatically generated simulation models
Flexible performance prediction of data center networks using automatically generated simulation models
复制标题
使用自动生成的仿真模型灵活预测数据中心网络的性能
DOI：
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复制
发表时间：
2015
期刊：
影响因子：
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通讯作者：
P. Tran
中科院分区：
文献类型：
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作者：
Piotr Rygielski;Samuel Kounev;P. Tran
使用不同的建模和仿真方法来预测网络性能，需要丰富的经验，并涉及每种建模形式主义的许多耗时的手动步骤。在本文中，我们提出了一种通用方法来建模数据中心网络的性能。该方法提供了多种性能模型，但只需要使用单个建模语言。我们提出了一种两步建模方法，其中在第一步中构建了网络的高级描述模型，并且在第二步模型到模型转换中被用来自动将描述模型转换为不同的网络模拟型号。我们会自动生成在不同级别的抽象级别定义的三个性能模型，以分析网络吞吐量。通过并行提供多个模拟模型，我们在建模准确性和仿真开销之间提供了灵活性。我们通过比较模拟持续时间的预测准确性来分析模拟模型。我们观察到，在调查的情况下，更粗的仿真模型的解决方案持续时间最高300倍，而平均预测准确性仅降低4％。
Using different modeling and simulation approaches for predicting network performance requires extensive experience and involves a number of time consuming manual steps regarding each of the modeling formalisms. In this paper, we propose a generic approach to modeling the performance of data center networks. The approach offers multiple performance models but requires to use only a single modeling language. We propose a two-step modeling methodology, in which a high-level descriptive model of the network is built in the first step, and in the second step model-to-model transformations are used to automatically transform the descriptive model to different network simulation models. We automatically generate three performance models defined at different levels of abstraction to analyze network throughput. By offering multiple simulation models in parallel, we provide flexibility in trading-off between the modeling accuracy and the simulation overhead. We analyze the simulation models by comparing the prediction accuracy with respect to the simulation duration. We observe, that in the investigated scenarios the solution duration of coarser simulation models is up to 300 times shorter, whereas the average prediction accuracy decreases only by 4 percent.
用于在线性能预测的架构级软件性能抽象
DOI：
10.1016/j.scico.2013.06.004
发表时间：
2014
期刊：
Sci. Comput. Program.
影响因子：
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作者：
Fabian Brosig;Nikolaus Huber;Samuel Kounev
通讯作者：
Samuel Kounev