@article{pecker2025hybrid,

title = {Hybrid resource allocation control in cyber-physical systems: a novel simulation-driven methodology with applications to UAVs},

author = {Ezequiel Pecker-Marcosig and Juan I. Giribet and Rodrigo Castro},

url = {https://doi.org/10.1177/00375497241313404},

doi = {10.1177/00375497241313404},

year  = {2025},

date = {2025-01-01},

journal = {SIMULATION},

volume = {101},

number = {5},

pages = {597–619},

abstract = {Designing hybrid controllers for cyber-physical systems (CPSs) where computational and physical components influence each other is a challenging task, as it requires considering the performance of very different types of dynamics simultaneously. Meanwhile, controlling each of these dynamics separately can lead to unacceptable results. Common approaches to controller design rely on the use of analytical methods. Although this approach can provide formal guarantees of stability and performance, the analytical design of hybrid controllers can become quite cumbersome. Alternatively, modeling and simulation (M&S)-based design techniques have proven successful for hybrid controllers, providing robust results based on Monte Carlo techniques. This requires simulation models and platforms capable of seamlessly composing the underlying hybrid domains. Unmanned Aerial Vehicles (UAVs) are CPSs with sensitive physical–computational couplings. We address the development of a hybrid model and simulation platform for a data collection application involving UAVs with onboard data processing. The quality of control (QoC) of the physical dynamics must be ensured together with the quality of service (QoS) of the onboard software competing for scarce processing resources. In this scenario, it is imperative to find safe trade-offs between flight stability and processing throughput that can adapt to uncertain environments. The goal is to design a hybrid supervisory controller that dynamically adapts the use of resources to balance the performance of both aspects in a CPS, while ensuring system-level QoS. We present the end-to-end M&S-based design methodology, which can be regarded as a design template for a broader class of CPSs.},

keywords = {Cyber-Physical Systems, DEVS, QSS, UAVs},

pubstate = {published},

tppubtype = {article}

}

@article{lanzarotti_multi-scale_2025,

title = {A multi-scale agent-based model of aerosol-mediated indoor infections in heterogeneous scenarios},

author = {Esteban Lanzarotti and Andrea Pineda Rojas and Francisco Roslan and Leandro Groisman and Lucio Santi and Rodrigo Castro},

url = {https://doi.org/10.1080/17477778.2025.2476456},

doi = {10.1080/17477778.2025.2476456},

issn = {1747-7778},

year  = {2025},

date = {2025-01-01},

urldate = {2025-07-01},

journal = {Journal of Simulation},

volume = {0},

number = {0},

pages = {1–19},

abstract = {We present a hybrid agent-based and equation-based simulation model to study airborne infection transmission events in heterogeneous indoor spaces. Agents move between different rooms, generating evolving networked social interactions. Suspended aerosols enable both direct and indirect transmission, shaping multi-scale contagion at local (room) and global (building layout) levels within a SEIR process. This approach provides a very flexible platform for dealing with environmental and population heterogeneities. Our model reproduces well-documented real-world contagion events and analytical models in the literature over a wide range of environments (hospitals, offices, restaurants, and classrooms). The model is applied to study transmission patterns in a typical school day, exploring three heterogeneity-driven scenarios: (i) varying break-time activity intensity, (ii) localized ventilation reductions, and (iii) flexible class/break durations, uncovering emerging nonlinear system-level dynamics. Our results show that neglecting heterogeneities can lead to considerable underestimation of attack rates. Such scenarios cannot be modeled with previous agent-based frameworks.},

note = {Publisher: Taylor & Francis 

_eprint: https://doi.org/10.1080/17477778.2025.2476456},

keywords = {Agent-based model, Airborne transmission, DEVS, Multi-scale simulation, QSS, Viral infection},

pubstate = {published},

tppubtype = {article}

}

@article{castro_discrete-event_2024,

title = {Discrete-event simulation of continuous-time systems: evolution and state of the art of quantized state system methods},

author = {Rodrigo Castro and Mariana Bergonzi and Ezequiel Pecker-Marcosig and Joaquín Fernández and Ernesto Kofman},

url = {https://journals.sagepub.com/doi/10.1177/00375497241230985},

doi = {10.1177/00375497241230985},

issn = {0037-5497, 1741-3133},

year  = {2024},

date = {2024-01-01},

urldate = {2025-07-01},

journal = {SIMULATION},

volume = {100},

number = {6},

pages = {613–638},

abstract = {In this work, we attempt to bring together the origins, main results, and recent advances on discrete-event simulation of continuous-time systems. Starting from the early approaches that aimed to represent continuous-time dynamics within the discrete-event system specification (DEVS) formalism framework, the work shows how these ideas gave place to the formalization of the quantized state system (QSS) family of numerical integration algorithms. Then, we describe the QSS algorithms, their properties, their extensions, and the main practical software tools implementing them. We also present a selection of simulation examples illustrating the main features and advantages through comparisons with state-of-the-art continuous-time simulation solvers.},

keywords = {DEVS, QSS},

pubstate = {published},

tppubtype = {article}

}

@article{santi_retqss_2022,

title = {retQSS: A novel methodology for efficient modeling and simulation of particle systems in reticulated geometries},

author = {Lucio Santi and Joaquín Fernández and Ernesto Kofman and Rodrigo Castro},

doi = {10.1016/J.CPC.2021.108157},

issn = {0010-4655},

year  = {2022},

date = {2022-01-01},

journal = {Computer Physics Communications},

volume = {270},

pages = {108157},

abstract = {This work presents retQSS, a novel methodology for efficient modeling and simulation of particle systems in reticulated meshed geometries. On the simulation side, retQSS profits from the discrete-event nature of Quantized State System (QSS) methods, which enable efficient particle tracking algorithms that are agnostic of the application domain. On the modeling side, retQSS relies on the standardized Modelica modeling language, yielding compact and elegant specifications of hybrid (continuous/discrete) dynamic systems. Combined together, these features offer a sound, general-purpose framework for modeling and simulation of particle systems. We show how the state-events that arise when particles interact with a reticulated mesh are seamlessly translated into easily tractable time-events. The latter can substantially improve simulation performance in scenarios where discontinuities dominate the computational demand. We showcase the flexibility of our approach by addressing four case studies arising from different application domains. Performance studies revealed that retQSS can perform similarly to, and even outperform, well-known domain-specific particle simulation toolkits while offering a clear and sound accuracy control interface.},

note = {Publisher: North-Holland},

keywords = {DEVS, Modelica, Particle simulation, QSS},

pubstate = {published},

tppubtype = {article}

}

@article{santi_efficient_2021,

title = {Efficient discrete-event based particle tracking simulation for high energy physics},

author = {Lucio Santi and Lucas Rossi and Rodrigo Castro},

doi = {10.1016/j.cpc.2020.107619},

issn = {00104655},

year  = {2021},

date = {2021-01-01},

journal = {Computer Physics Communications},

volume = {258},

abstract = {This work presents novel discrete event-based simulation algorithms based on the Quantized State System (QSS) numerical methods. QSS provides attractive features for particle transportation processes, in particular a very efficient handling of discontinuities in the simulation of continuous systems. We focus on High Energy Physics (HEP) particle tracking applications that typically rely on discrete time-based methods, and study the advantages of adopting a discrete event-based numerical approach that resolves efficiently the crossing of geometry boundaries by a traveling particle. For this purpose we follow two complementary strategies. First, a new co-simulation technique connects the Geant4 simulation toolkit with a standalone QSS solver. Second, a new native QSS numerical stepper is embedded into Geant4. We compare both approaches against the latest Geant4 default steppers in different HEP setups, including a complex realistic scenario (the CMS particle detector at CERN). Our techniques achieve relevant simulation speedups in a wide range of scenarios, particularly when the intensity of discrete-event handling dominates performance in the solving of the continuous laws of particle motion.},

note = {Publisher: Elsevier B.V.},

keywords = {DEVS, Geant4, High energy physics, Particle tracking, QSS},

pubstate = {published},

tppubtype = {article}

}

@article{pecker-marcosig_hybrid_2017,

title = {Hybrid adaptive control for UAV data collection: A simulation-based design to trade-off resources between stability and communication},

author = {Ezequiel Pecker-Marcosig and Juan I. Giribet and Rodrigo Castro},

doi = {10.1109/WSC.2017.8247909},

issn = {08917736},

year  = {2017},

date = {2017-01-01},

journal = {Proceedings - Winter Simulation Conference},

pages = {1704–1715},

abstract = {We present the design of a hybrid control system for an Unmanned Aerial Vehicle (UAV) used for data collection from wireless sensors. We postulate a restrictive scenario where a low-cost processor is in charge of both flying the UAV and resolving data communication. This raises the need for safe trade-off of computing resources between stability and throughput, adapting to unpredictable environment changes. We present a strategy where a supervisory controller implements an adaptive relaxation of the sampling period of the UAV regulation controller to favor communication tasks. To guarantee stability under period switching we update the discrete-time control law with suitable gains. The resulting system comprises continuous, discrete-time and discrete-event dynamics, including event-based adaptation of the discrete-time controller. We show how the DEVS modeling and simulation framework can support a full simulation-based design, verification and validation process, featuring a seamless composition of the underlying hybrid domains.},

note = {ISBN: 9781538634288 

Publisher: Institute of Electrical and Electronics Engineers Inc.},

keywords = {DEVS, Hybrid systems, QSS, UAV},

pubstate = {published},

tppubtype = {article}

}