Researchers from the Center for Computational Simulation (CCS) will participate in the Annual Modeling and Simulation Conference (ANNSIM 2026), to be held from May 4 to 7 this year in Orlando, Florida, with the acceptance of two papers and a PhD Colloquium focused on the use of the DEVS formalism for advanced co-simulation environments.

The works, framed within the WATER-SUSTAIN project, feature the authorship of Daniel Muñiz Zurrunero, Román Cárdenas Rodríguez, and Patricia Arroba García, reinforcing the department’s international presence in the field of modeling and simulation of complex systems.

Advances in the xDEVS ecosystem: asynchronous co-simulation and visual modeling

The first of the accepted articles, titled “EXTENDING XDEVS NO_STD: REAL-TIME ASYNCHRONOUS DEVS FOR EMBEDDED CO-SIMULATION”, addresses the extension of the xDEVS no_std simulator to support real-time asynchronous co-simulation on embedded systems. The work proposes mechanisms that allow for a more efficient and sustainable integration of cloud-edge infrastructures with strict temporal and resource constraints.

The second paper, “DEVSFORGE: A VISUAL MODELING ENVIRONMENT FOR XDEVS”, presents DEVSFORGE, a visual modeling environment aimed at facilitating the design of DEVS models. This tool seeks to lower the barrier to entry for the DEVS formalism, promoting its adoption in both academic and industrial contexts through a graphical and intuitive approach.

Doctoral research on IoT early warning systems

In addition to these two works, Daniel Muñiz Zurrunero will participate in the ANNSIM 2026 PhD Colloquium with the contribution “A DEVS-BASED CO-SIMULATION METHODOLOGY FOR IOT EARLY WARNING SYSTEMS”. This presentation will showcase the DEVS-based co-simulation methodology being developed as part of his doctoral thesis, which is oriented toward the design and evaluation of IoT early warning systems for bio-pollutants in freshwater.

The presence of the WATER-SUSTAIN project at ANNSIM 2026 highlights the consolidation of its research lines in modeling, simulation, and optimization of complex systems, as well as its commitment to doctoral training and knowledge transfer in top-tier scientific forums.

This work is part of the R&D&I Project PID2024-156033OA-C33 funded by MICIU/AEI/10.13039/501100011033 and by “ERDF/EU”.