Building Devs Models with the Cadmium Tool

Belloli, Laouen; Vicino, Damian; Ruiz-Martín, Cristina; Wainer, Gabriel

doi:10.1109/wsc40007.2019.9004917

Cited by 30 publications

(17 citation statements)

References 6 publications

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“…ADEVS (Nutaro 2015) is a minimalistic, highly efficient, C++ implementation of the Parallel DEVS formalism. A recent C++-based addition is Cadmium (Belloli et al 2019), a C++17 header-only Parallel DEVS simulator. DEVS-Suite (Kim et al 2009) is a full modeling and simulation environment implemented in Java, with a visual simulation interface.…”

Section: Toolsmentioning

confidence: 99%

An Introduction to Modular Modeling and Simulation with PythonPDEVS and the Building-Block Library PythonPDEVS-BBL

Tendeloo

Paredis

Vangheluwe

2020

2020 Winter Simulation Conference (WSC)

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The Discrete Event System Specification (DEVS) is a popular formalism devised by Bernard Zeigler in the late 1970s for modeling complex dynamical systems using a discrete event abstraction. At this abstraction level, a timed sequence of pertinent "events" input to a system (or internal timeouts) causes instantaneous changes to the state of the system. Main advantages of DEVS are its precise, implementation independent specification, and its support for modular composition. This tutorial introduces the Classic DEVS formalism in a bottom-up fashion, using a simple traffic light example. The syntax and operational semantics of Atomic (i.e., non-hierarchical) models are introduced first. Coupled (i.e., hierarchical) models are introduced to structure and couple Atomic models. We continue to actual applications of DEVS, with an example in performance analysis of queueing systems. This uses generator, queue, etc. components from our PythonPDEVS Building Block Library. All examples in the paper are presented using the language PythonPDEVS and its simulator, though this introduction is equally applicable to other DEVS implementations. We conclude with further reading on DEVS theory, variants, and tools. INTRODUCTIONThe Discrete Event System Specification (DEVS) (Zeigler et al. 2000) first introduced by Bernard Zeigler in the late 1970s is a popular formalism for modeling complex dynamic systems using a discrete event abstraction. At this abstraction level, a timed sequence of pertinent "events" input to a system cause instantaneous changes to the state of the system. These events can be generated externally (i.e., by another model, of the system's environment) or internally (i.e., by the model itself due to timeouts). If a system has no (or does not react to) external events, it is called autonomous. The next state of the system is defined based on both the previous state of the system and the event. Between events, the state does not change, resulting in a piecewise constant state trajectory. Simulation kernels may thus only consider times at which events occur, skipping over all intermediate points in time. This is in contrast to discrete time models, where time is increased with a fixed increment, and only at those times the state is updated. Discrete event models have the advantage that their time granularity can, in theory, become arbitrarily small or large. However, only a finite number of events are allowed in any finite time span. Without this restriction, discrete event would become equivalent to continuous time. The added complexity of the discrete event abstraction makes it less appropriate for systems that naturally have a fixed time step.This tutorial provides an introduction to DEVS (often referred to as Classic DEVS) using a simple traffic light example. This paper is a revised and extended version of our tutorial paper at the 2019 Winter Simulation Conference (Van Tendeloo, Vangheluwe, and Franceschini 2019). We start from a simple autonomous traffic light, incrementally extended up to a trafficlight with...

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Section: Toolsmentioning

confidence: 99%

An Introduction to Modular Modeling and Simulation with PythonPDEVS and the Building-Block Library PythonPDEVS-BBL

Tendeloo

Paredis

Vangheluwe

2020

2020 Winter Simulation Conference (WSC)

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“…Cell-DEVS can be used to specify and implement cellular models and facilitates their simulation and integration with other models. In this research, we use the Cadmium tool, 34 which allows users to define model inputs using JSON, a data format to store and transmit large amounts of human readable data. JSON stores data in key-value pairs allowing for the simple representation of neighborhoods, their attributes, and their relationships.…”

Section: Introductionmentioning

confidence: 99%

A methodological approach for modeling the spread of disease using geographical discrete-event spatial models

et al. 2023

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The study of infectious disease models has become increasingly important during the COVID-19 pandemic. The forecasting of disease spread using mathematical models has become a common practice by public health authorities, assisting in creating policies to combat the spread of the virus. Common approaches to the modeling of infectious diseases include compartmental differential equations and cellular automata, both of which do not describe the spatial dynamics of disease spread over unique geographical regions. We introduce a new methodology for modeling disease spread within a pandemic using geographical models. We demonstrate how geography-based Cell-Discrete-Event Systems Specification (DEVS) and the Cadmium JavaScript Object Notation (JSON) library can be used to develop geographical cellular models. We exemplify the use of these methodologies by developing different versions of a compartmental model that considers geographical-level transmission dynamics (e.g. movement restriction or population disobedience to public health guidelines), the effect of asymptomatic population, and vaccination stages with a varying immunity rate. Our approach provides an easily adaptable framework that allows rapid prototyping and modifications. In addition, it offers deterministic predictions for any number of regions simulated simultaneously and can be easily adapted to unique geographical areas. While the baseline model has been calibrated using real data from Ontario, we can update and/or add different infection profiles as soon as new information about the spread of the disease become available.

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“…This is likely due to the resources involved in developing comprehensive visualization capability and the lack of interest from the research community regarding this topic [66]. For example, CD++ [67], Cadmium [68] [68], DEVSJAVA [69] and ADEVS [70] are all generic DEVS simulators that only offer basic visualization and analysis capabilities. Other simulators for formal models, such as OpenModelica [71] offer a more extensive capability (2D charts, 3D visualization and additional options to display analytical charts [72], [73]).…”

Section: The Role Of Visualization In Simulationmentioning

confidence: 99%

A Web Based Architecture to Operationalize Geospatial Simulation Environments

St-Aubin¹

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Simulation is inherently multi-disciplinary. It requires knowledge about the system under study, expertise in simulation theory to define models and programming skills to implement models. Geospatial simulation requires an additional layer of expertise in topology, geospatial data structures, spatial analysis, computational geometry, and other related topics. Commercial modeling and simulation software can be used to provide an environment to facilitate simulation studies for users. However, these software tend to be narrowly scoped to specific business applications and tightly couple model and simulator.I am first and foremost grateful to Professor Gabriel Wainer for giving me an opportunity to accomplish my research under his supervision. I would not have successfully completed it without your guidance, mentorship, and dedication. On several occasions in the past 5 years, you were able to express the words of encouragement I needed to keep going. I am also thankful for my colleagues and friends at the Advanced Real-Time

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Building Devs Models with the Cadmium Tool

Cited by 30 publications

References 6 publications

An Introduction to Modular Modeling and Simulation with PythonPDEVS and the Building-Block Library PythonPDEVS-BBL

An Introduction to Modular Modeling and Simulation with PythonPDEVS and the Building-Block Library PythonPDEVS-BBL

A methodological approach for modeling the spread of disease using geographical discrete-event spatial models

A Web Based Architecture to Operationalize Geospatial Simulation Environments

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