Hide Your Model! Layer Abstractions for Data-Driven Co-Simulations

Gütlein M, German R, Djanatliev A (2021)


Publication Type: Conference contribution, Conference Contribution

Publication year: 2021

Conference Proceedings Title: Proceedings of the 2021 Winter Simulation Conference

Event location: Phoenix US

DOI: 10.1109/WSC52266.2021.9715317

Abstract

Modeling and simulating of problems that span across multiple domains can be tricky. Often, the need for a co-simulation arises, for example because the modeling cannot be done with a single tool. Domain experts may face a barrier when it comes to the implementation of such a co-simulation. In addition, the demand for integrating data from various sources into simulation models seems to be growing. Therefore, we propose an abstraction concept that hides simulators and models behind generalized interfaces that are derived from prototypical classes. The data-driven abstraction concept facilitates having an assembly kit with predefined simulator building blocks that can be easily plugged together. Furthermore, data streams can be seamlessly ingested into such a composed model. Likewise, the co-simulation can be accessed via the resulting interfaces for further processing and interactions.

Authors with CRIS profile

Related research project(s)

How to cite

APA:

Gütlein, M., German, R., & Djanatliev, A. (2021). Hide Your Model! Layer Abstractions for Data-Driven Co-Simulations. In Proceedings of the 2021 Winter Simulation Conference. Phoenix, US.

MLA:

Gütlein, Moritz, Reinhard German, and Anatoli Djanatliev. "Hide Your Model! Layer Abstractions for Data-Driven Co-Simulations." Proceedings of the 2021 Winter Simulation Conference (WSC), Phoenix 2021.

BibTeX: Download