Comparing the Complexity and Efficiency of Composable Modeling Techniques for Multi-Scale and Multi-Domain Complex System Modeling and Simulation Applications: A Probabilistic Analysis

Modeling and simulation of complex systems frequently requires capturing probabilistic dynamics across multiple scales and/or multiple domains. Cyber–physical, cyber–social, socio–technical, and cyber–physical–social systems are common examples. Modeling and simulating such systems via a single, all...

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Bibliographic Details
Published in:Systems (Basel) Vol. 12; no. 3; p. 96
Main Author: Wagner, Neal
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.03.2024
Subjects:
co-simulation
Comparative analysis
Complex systems
Complexity
Computational efficiency
Computing time
Data transfer (computers)
Efficiency
Human influences
Interoperability
Learning models (Stochastic processes)
Methods
modeling and simulation
multi-domain systems
multi-scale systems
Probabilistic analysis
Simulation
Simulation methods
Simulation models
Software
United States
ISSN:2079-8954, 2079-8954
Online Access:Get full text
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Summary:Modeling and simulation of complex systems frequently requires capturing probabilistic dynamics across multiple scales and/or multiple domains. Cyber–physical, cyber–social, socio–technical, and cyber–physical–social systems are common examples. Modeling and simulating such systems via a single, all-encompassing model is often infeasible, and thus composable modeling techniques are sought. Co-simulation and closure modeling are two prevalent composable modeling techniques that divide a multi-scale/multi-domain system into sub-systems, use smaller component models to capture each sub-system, and coordinate data transfer between component models. While the two techniques have similar goals, differences in their methods lead to differences in the complexity and computational efficiency of a simulation model built using one technique or the other. This paper presents a probabilistic analysis of the complexity and computational efficiency of these two composable modeling techniques for multi-scale/multi-domain complex system modeling and simulation applications. The aim is twofold: to promote awareness of these two composable modeling approaches and to facilitate complex system model design by identifying circumstances that are amenable to either approach.
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ISSN:2079-8954
2079-8954
DOI:10.3390/systems12030096