Dynamic Co-Simulation of Internet-of-Things-Components using a Multi-Agent-System
Open accessAbstract
The heterogeneity and dynamic of IoT-systems pose new challenges for their simulation, which can be met by a modular co-simulation. Therefore several existing co-simulation approaches are presented and evaluated. A new concept for a dynamic co-simulation of IoT-systems utilizing a multi-agent-system is presented, wherein each IoT-component is simulated in a separate simulation tool. Each separate simulation is represented by an agent, and therefore able to enter a running co-simulation dynamically during runtime, which allows for a “Plug-and-Simulate” behavior. The connection between agents and simulation tools is realized by an interface concept. The presented concept is evaluated by a prototypical implementation.
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Simulation theory and agent-based simulation technologies play a key role in representing the behavior of a large system composed of different Digital Twins.
“Simulation theory [155] and agent-based simulation technologies [74] [156] for large systems also play a key role in representing the behavior of a large system composed of different Digital Twins.”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [156]
The Introduction links simulation of heterogeneous IoT systems to the Digital Twin, and §3.1 describes agents connecting separate component simulations to represent their interactions. The paper does not establish that the system is large or composed of different Digital Twins; its distinct simulations represent IoT components. (LLM, conf=0.84)
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Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models
Minerva, R., Lee, G. M., & Crespi, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.2998530 · Cited by 812 · see citing works
An architecture of an intelligent digital twin in a cyber-physical production system
Ashtari Talkhestani, B., Jung, T., Lindemann, B., Sahlab, N., Jazdi, N., Schloegl, W., & Weyrich, M. (2019) · at - Automatisierungstechnik · doi:10.1515/auto-2019-0039 · Cited by 300 · see citing works
Self-citationDigital Twin-Based Optimization for Ultraprecision Motion Systems With Backlash and Friction
Guerra, R. H., Quiza, R., Villalonga, A., Arenas, J., & Castano, F. (2019) · IEEE Access · doi:10.1109/access.2019.2928141 · Cited by 89 · see citing works
- Authors
- Jung, T., Shah, P., & Weyrich, M.
- Affiliations
- University of Stuttgart (DE)
- Corresponding author
- Jung, Tobias
- ORCID
- Weyrich, Michael
- Venue
- Procedia CIRP
- Publisher
- Elsevier BV
- Published
- 2018
- Volume
- 72
- Pages
- 874-879
- ISSN
- 2212-8271 (ISSN-L)
- OpenAlex
- W2809837923
- Cited by
- 26
- References
- 0
- Citations by year
- 2024: 2 · 2023: 4 · 2022: 4 · 2021: 6 · 2020: 4 · 2019: 5 · 2018: 1
- FWCI
- 2.99
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Procedia CIRP (publishedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Modeling and Simulation Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Keywords
- Internet of Things, co-simulation, multi-agent systems, modular simulation, dynamic simulation, heterogeneous systems
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