COOPERATION OF SIMULATION AND DATA MODEL FOR PERFORMANCE ANALYSIS OF COMPLEX SYSTEMS

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Modelling and simulation (M&S) is one of the fundamental methods of performance analysis. In other words, how well a modeller builds a model is a key point of a successful performance analysis. Before such a performance analysis, a model for prediction should be constructed. There are two types of models: data model and simulation model. Data model represents correlational relationships between one set of data and another. Conversely, simulation model represents causal relationships between a set of controlled inputs and corresponding outputs. This paper identifies the characteristics of each modelling method and presents a cooperative model development process for performance analysis of complex systems. The cooperative method contains conceptual modelling, model classification, and model integration/implementation. The model classification method effectively reflects and maximizes the features compared earlier. Then, they are modelled respectively and integrated. This paper also applies the proposed modelling to develop a model of Hadoop using artificial neural network (ANN) and discrete event systems specification (DEVS). To demonstrate the validity of the case study, it presents experiments to show the possibility of a proposed approach.
Publisher
DAAAM INTERNATIONAL VIENNA
Issue Date
2019-12
Language
English
Article Type
Article
Citation

INTERNATIONAL JOURNAL OF SIMULATION MODELLING, v.18, no.4, pp.608 - 619

ISSN
1726-4529
DOI
10.2507/IJSIMM18(4)491
URI
http://hdl.handle.net/10203/270279
Appears in Collection
EE-Journal Papers(저널논문)
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