System entity structure extension to integrate abstraction hierarchies and time granularity into DEVS modeling and simulation

Santucci, Jean-François; Capocchi, Laurent; Zeigler, Bernard P.

doi:10.1177/0037549716657168

Cited by 22 publications

(21 citation statements)

References 29 publications

(49 reference statements)

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“…Santucci et al [19] propose an extension of SES in order to integrate the concepts of abstraction hierarchy into DEVS. Cheon et al [20] propose a method and an example to generate an experimental frame by using SES from the source data.…”

Section: Relationships Identificationmentioning

confidence: 99%

An integrative approach to simulation model discovery: Combining system theory, process mining and fuzzy logic

Wang

Zacharewicz

Traoré

et al. 2018

IFS

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Relationships Identificationmentioning

confidence: 99%

An integrative approach to simulation model discovery: Combining system theory, process mining and fuzzy logic

Wang

Zacharewicz

Traoré

et al. 2018

IFS

View full text Add to dashboard Cite

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“…The SES extension to integrate abstraction hierarchies and time granularity, as proposed by Santucci et al, 64 provides a convenient ontological framework that will allow us to extend the multi-perspective modeling approach beyond healthcare systems toward a more generic framework.…”

Section: Related Workmentioning

confidence: 99%

Modeling and simulation framework for value-based healthcare systems

et al. 2018

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Regardless of the coordination of its activities, a healthcare system is composed of a large number of distributed components that are interrelated by complex processes. Understanding the behavior of the overall system is becoming a major concern among healthcare managers and decision-makers. This paper presents a modeling and simulation framework to support a holistic analysis of healthcare systems through a stratification of the levels of abstraction into multiple perspectives and their integration in a common simulation framework. In each of the perspectives, models of different components of a healthcare system can be developed and coupled together. Concerns from other perspectives are abstracted as parameters, that is, we reflect the parameter values of other perspectives through explicit assumptions and simplifications in such models. Consequently, the resulting top model within each perspective can be coupled with its experimental frame to run simulations and derive results. Components of the various perspectives are integrated to provide a holistic view of the healthcare problem and system under study. The resulting global model can be coupled with a holistic experimental frame to derive results that cannot be accurately addressed in any of the perspectives taken alone. Furthermore, as we endeavored to allow perspective-specific experts to contribute to the modeling process, we took benefit of results originating from research efforts that Norbert Giambiasi initiated in the 2000s, which his PhD students further developed with their own PhD students.

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“…Time resolution pertains to nonzero time durations that separate consecutive events. Related to this is the challenge of how to integrate models with different levels of resolution (Guo, Hu, andWang 2012, Santucci, Capocchi, andZeigler 2016). Time precision pertains to the time durations that separate consecutive points at which events are permitted to occur.…”

Section: Time Granularitymentioning

confidence: 99%

A Taxonomy of Event Time Representations

2017

TMS/DEVS Symposium on Theory of Modeling &Amp; Simulation (TMS/DEVS 2017)

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Terms such as "simulated time", "simulation time", "virtual time", "logical time", and "real time" appear throughout the modeling and simulation literature as a means of describing the timing, ordering, and/or processing of events. Unfortunately, this vocabulary can become a source of confusion due to subtle inconsistencies in how the terms are interpreted. Here we categorize mathematical representations of event times, review their formal properties such as causal consistency and causal characterization, identify formal relationships among the representations, and present a taxonomy to clarify the proper meanings of the most common notions of time in a simulation context. A thorough look at the various event time representations suggests new research opportunities, such as the repurposing of distributed computing techniques for debugging both parallel and sequential discrete event simulations.

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System entity structure extension to integrate abstraction hierarchies and time granularity into DEVS modeling and simulation

Cited by 22 publications

References 29 publications

An integrative approach to simulation model discovery: Combining system theory, process mining and fuzzy logic

An integrative approach to simulation model discovery: Combining system theory, process mining and fuzzy logic

Modeling and simulation framework for value-based healthcare systems

A Taxonomy of Event Time Representations

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