Automated Parameterization of Performance Models from Measurements
Automated Parameterization of Performance Models from Measurements
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DOI：
10.1145/2851553.2858666
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发表时间：
2016-03
期刊：
影响因子：
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通讯作者：
G. Casale;Simon Spinner;Weikun Wang
中科院分区：
文献类型：
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作者：
G. Casale;Simon Spinner;Weikun Wang
Estimating parameters of performance models from empirical measurements is a critical task, which often has a major influence on the predictive accuracy of a model. This tutorial presents the problem of parameter estimation in queueing systems and queueing networks. The focus is on reliable estimation of the arrival rates of the requests and of the service demands they place at the servers. The tutorial covers common estimation techniques such as regression methods, maximum-likelihood estimation, and moment-matching, discussing their sensitivity with respect to data and model characteristics. The tutorial also demonstrates the automated estimation of model parameters using new open source tools.
