Discrete Event System Specification Research Articles

Modeling- and Simulation-Driven Methodology for the Deployment of an Inland Water Monitoring System

In response to the challenges introduced by global warming and increased eutrophication, this paper presents an innovative modeling and simulation (M&S)-driven model for developing an automated inland water monitoring system. This system is grounded in a layered Internet of Things (IoT) architecture and seamlessly integrates cloud, fog, and edge computing to enable sophisticated, real-time environmental surveillance and prediction of harmful algal and cyanobacterial blooms (HACBs). Utilizing autonomous boats as mobile data collection units within the edge layer, the system efficiently tracks algae and cyanobacteria proliferation and relays critical data upward through the architecture. These data feed into advanced inference models within the cloud layer, which inform predictive algorithms in the fog layer, orchestrating subsequent data-gathering missions. This paper also details a complete development environment that facilitates the system lifecycle from concept to deployment. The modular design is powered by Discrete Event System Specification (DEVS) and offers unparalleled adaptability, allowing developers to simulate, validate, and deploy modules incrementally and cutting across traditional developmental phases.

Modeling and Simulation of Unmanned Swarm System Based on Dynamic Structure DEVS

As a complex system with collaborative cooperation and capability emergence, the unmanned swarm system plays an important role in military, agriculture, aerospace and other fields. With the increasing complexity of unmanned swarm systems, traditional modeling methods cannot effectively describe the dynamics of swarm systems. In order to effectively design, use and evaluate unmanned swarm systems, this article conducts modeling and simulation of unmanned swarm systems based on DSDEVS(Dynamic Structure Discrete Event System Specification). Describe the unmanned swarm system from both behavioral and structural aspects. Based on component modeling, the microscopic behaviors of the unmanned platforms that constitute the unmanned swarm are described, and coupling relationships are established to describe the collaborative structure between unmanned platforms. According to the state transfer and event interaction characteristics of the unmanned swarm system, a synchronization mechanism is added to support changes in the swarm structure. This enables the unmanned swarm system to make adaptive structural adjustments according to environmental changes and its own goals during simulation operation, so as to achieve a state of enhanced capabilities and structural stability to complete the task. Finally, the effectiveness and feasibility of this method were verified through a simulation experiment of joint reconnaissance by a UAV swarm.

Building Models in Pairs for Cross‐Verification Using SDL and DEVS

AbstractThe objective of the paper is to present a methodology that can be used to translate a model from one formalism to another allowing model reuse and cross‐verification. With the use of formal languages, the model specifications can be expressed in a rigorous and univocal way, and the model can be validated against the specifications or conceptual model. Expressing the same model in different formal languages opens the conceptual model validation to a varied number of specialists. Also, in the context of modeling a new system, where there is no data to perform validation against a real system, having pairs of models can be used to perform cross‐model verification to ensure that the model specifications or conceptual models are correctly implemented by comparing the results produced by both models. Specifically, a method is presented to translate a model conceptualized on specification and description language (SDL) to discrete event system specification (DEVS). The transformation mechanism between SDL and DEVS formalisms is described. The methodology is exemplified with a disease spread model for COVID‐19, and it is shown how the results obtained by the two models can be used for cross‐verification.

Mapping RDEVSNL-based Definitions of Constrained Network Models to Routed DEVS Simulation Models

The Routed DEVS (RDEVS) formalism has been introduced recently to provide a reasonable formalization for the simulation of routing processes over Discrete Event System Specification (DEVS) models. Due to its novelty, new software tools are required to improve the Modeling and Simulation (MS) tasks related to the RDEVS formalism. This paper presents the mapping between constrained network models obtained from textual specifications of routing processes and RDEVS simulation models implemented in Java. RDEVSNL context-free grammar (previously defined) is used to support the textual specification of a routing process as a constrained network model. Such grammar is based on a metamodel that defines the syntactical elements. This metamodel is used in this paper as a middleware that allows mapping constrained network model concepts with RDEVS simulation models. From such a constrained network model template, RDEVS Java implementations are obtained. The proposal is part of a work-in-progress intended to develop MS software tools for the RDEVS formalism using well-known abstractions to get the computational models through conceptual mapping. Using these tools, modelers can specify simulation models without needing to codify any routing implementation. The main benefits are i) reduction of implementation times and ii) satisfactory simulation model correctness regarding the RDEVS formalism.

Discrete-event simulation of continuous-time systems: evolution and state of the art of quantized state system methods

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.

A knowledge interchange broker composition modeling framework for simulating water, energy, and water-energy nexus systems

Understanding the dynamics of complex systems requires developing and combining different kinds of models that can be simulated separately and together. Modeling the interactions as separate models contributes to building flexible hybrid simulation frameworks. In this research, a Discrete Event System Specification–based Interaction Model (DEVS-IM) framework is developed based on the Knowledge Interchange Broker (KIB) approach. This KIB-based RESTful modeling composition framework is shown to enable systematic modeling and simulation of interactions between disparate simulatable models. It supports storing IMs developed for componentized Water Evaluation and Planning System (WEAP) and Low Emissions Analysis Platform (LEAP) tools. It generates the skeleton of DEVS-IMs stored in database for DEVS-Suite simulator. An exemplar model consisting of water, energy, and IMs demonstrates this methodology for developing nexus models of water–energy systems.

Discrete Event Systems Theory for Fast Stochastic Simulation via Tree Expansion

Discrete Event Systems Theory for Fast Stochastic Simulation via Tree Expansion

Modelling and simulation of energy management of power-split hybrid electric vehicles using the discrete event system specification

Modelling and simulation of energy management of power-split hybrid electric vehicles using the discrete event system specification

A framework for modeling, generating, simulating, and predicting carbon dioxide dispersion indoors using cell-DEVS and deep learning

Carbon dioxide concentration in enclosed spaces is an air quality indicator that affects occupants’ well-being. To maintain healthy carbon dioxide levels indoors, enclosed space settings must be adjusted to maximize air quality while minimizing energy consumption. Studying the effect of these settings on carbon dioxide concentration levels is not feasible through physical experimentation and data collection. This problem can be solved by using validated simulation models, generating indoor settings scenarios, simulating those scenarios, and studying results. In previous work, we presented a formal Cellular Discrete Event System Specifications simulation model for studying carbon dioxide dispersion in rooms with various settings. However, designers may need to predict the results of altering large combinations of settings on air quality. Generating and simulating multiple scenarios with different combinations of space settings to test their effect on indoor air quality is time-consuming. In this research, we solve the two problems of the lack of ground truth data and the inefficiency of producing and studying simulation results for many combinations of settings by proposing a novel framework. The framework utilizes a Cellular Discrete Event System Specifications model, simulates different scenarios of enclosed spaces with various settings, and collects simulation results to form a data set to train a deep neural network. Without needing to generate all possible scenarios, the trained deep neural network is used to predict unknown settings of the closed space when other settings are altered. The framework facilitates configuring enclosed spaces to enhance air quality. We illustrate the framework uses through a case study.

Decoupling visualisation for better DEVS-based simulation applications

ABSTRACT Simulation visualisation is an effective way of understanding and communicating complex systems and processes. Among other advantages, it increases model transparency and intelligibility for all categories of users including non-experts, and it can be used by modellers as a tool to debug models in development. However, simulation visualisation is often tightly coupled to specific simulators, and, therefore, there is no way to reuse visualisation tools efficiently. Here, we present a specification that can be used to decouple visualisation engines from simulators. The specification also considers storage optimisation to support web-based simulation applications. We also present an implementation that supports the web-based representation and animation of outputs issued from simulators based on the discrete event system specification (DEVS) and Petri Nets.

Combining DEVS simulation and ontological modeling for hierarchical analysis of the SARS-CoV-2 replication

This article presents an hybrid and hierarchical model in which two modeling and simulation approaches, discrete event system specification simulation (DEVS) and semantic technologies, were used together in order to help in the analysis of a major healthcare problem, the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). Indeed, the complexity of the SARS-CoV-2 replication process, and the range of hierarchical scales over which it interacts with cellular components (extending from genomic and transcriptomic to proteomic and metabolomic scales), and the intricate way in which they are interwoven, make its understanding very challenging. It is therefore crucial to model the different scales of the replication process, by taking into account all interactions with the infected cell. By combining the advantages of both DEVS simulation and ontological modeling, we propose a hierarchical ontology-based DEVS simulation model of the SARS-CoV-2 viral replication at both the micro-molecular (proteomic and metabolomic) and macro-molecular (genomic and transcriptomic) scales. First, we demonstrate the usefulness of combining DEVS simulation and semantic technologies in a common modeling framework to face the complexity of the SARS-CoV-2 viral replication at different scales. Second, the modeling and simulation of the SARS-CoV-2 replication process on different levels provide valuable information on the different stages of the virus’s life cycle and lays the foundation for a system to anticipate future mutations selected by the virus.

A Parallel Algorithm to Accelerate DEVS Simulations in Shared Memory Architectures

We propose a new algorithm for the execution of Discrete Event System Specification (DEVS) simulations on parallel shared memory architectures. Our approach executes parallel discrete-event simulations by executing all tasks in the PDEVS simulation protocol in parallel. The algorithm works by distributing the computations among different cores on shared memory architectures. To show the benefits of our algorithm, we present the results of a set of experiments using a synthetic benchmark and a real-world scenario using two independent computer architectures. The results obtained show how our algorithm accelerates simulations up to eight times, improving previous approaches. In addition, we show that our approach scales when we increase the number of CPU-cores used.

Towards a DEVS Model Management System for Decision-Making Web Applications

The discrete event system specification formalism introduced by Zeigler in the 1970s is ideally associated with new technological advances in the web to offer an almost quasi-automatic mechanism for exporting its simulation models associated with experimental frames into web apps. In this paper, we show how, thanks to the association of certain current web concepts (cloud computing, application virtualization, etc.), discrete event system specification formalism makes it easier to develop web apps that use simulation models to assist decision-making. We propose a simulation model management system used by teams of data scientists, modelers, and developers (engineers) capable of building and deploying web applications from simulation models with minimal web development knowledge.

Enriching UML Statecharts through a Metamodel: A Model Driven Approach for the Graphical Definition of DEVS Atomic Models

The Discrete Event System Specification (DEVS) formalism provides a set of mathematical elements for modeling time-varying systems. However, when DEVS models are implemented in an executable representation (i.e., using a general-purpose programming language), some deviation from the formalism is unavoidable. One way to bridge the gap between modeling and simulation theory and practice is to define new artifacts that support both views during the specification. When the specification is supported with a graphical representation, the formalization task is less complex and can be performed by non-expert modelers. For DEVS atomic models, most common graphical representation is through UML statecharts. In this paper, we present a theoretical and practical metamodel for the definition of atomic models structured following the Classic DEVS with Ports formalization. Such a metamodel is the core of a model-driven approach used to develop a modeling software tool that employs enriched UML statecharts for the graphical representation of the DEVS behavior. In here, the traditional UML statechart representation is enriched with a set of new components with the aim to provide a broad definition of DEVS atomic models. The final software tool is deployed as a plugin for Eclipse Platform.

Bridging the gap between business process and simulation: transformation from BPMN to DEVS

Organizations are constantly looking for ways to improve the performance of their business processes (BPs) by making them more understandable, coordinated, streamlined, and effective. As a result, stakeholders are invited to take part in BP's management and improvement projects, which make use of modeling and simulation technologies. The influence of resources (human, monetary, ...) and their allocation in a business process has a significant impact on the simulation results, thus they must be portrayed accurately from the analysts’ standpoint. By offering concepts, methodologies, and tools that combine business process modeling and simulation, this study bridges the gap between the two worlds. This paper presents perspectives on a metamodel-based transformation approach for Business Process Modeling and Notation (BPMN) models extended with Business Process Simulation Interchange Standard (BPSIM) into Discrete Event System Specification (DEVS) simulation models with an emphasis on resource allocation.

Simulation of IoT-oriented Fall Detection Systems Architectures for In-home Patients

Fall detection (FD) systems enable rapid detection and intervention for people who experience falls, a leading threat to the elderlys health and autonomy. Most of these systems conform to an IoT reference architecture which may include multiple sensing mechanisms to balance the advantages and drawbacks of each alternative. However, developing such a heterogeneous system may be costly and quite resource and time-demanding. This paper presents a Discrete Event System Specification (DEVS) simulation model for FD systems that compares the accuracy of nine different systems architectures that combine traditional wearable and non-wearable sensing devices in the acquisition layer. We perform simulations for each architectural arrangement using four public datasets of FD systems, totaling 36 simulations. Results reveal that an FD accuracy of 96.67% is possible with an investment of almost 6,000 US. Besides, spending 36 times less (around 150 US), designers and clients could acquire an FD system composed of wearable and non-wearable devices with an accuracy of 91%, i.e., only 5% less than the most expensive alternative.

RTL-DEVS: HDL Design and Simulation Methodology for DEVS Formalism-Based Simulation Tool

DEVS (Discrete Event System Specification) is widely used in modeling and simulation fields to design, validate, and implement complex response systems. DEVS provides a robust formalism for system design using event-driven, state-based models with explicitly defined temporal information. We extend the RTL-DEVS model based on DEVS formalism to enable part of Verilog simulation in DEVS-based simulation tools. The simulation based on RTL-DEVS methodology, which imitates Verilog’s testbench and behavioral module, confirmed through experiments that RTL simulation can be performed sufficiently through the code elaboration process. In multiple simulation results, Verilog simulation and RTL-DEVS-based simulation were able to output equivalent results under limited conditions. DEVS formalism-based modeling can be extended to other DEVS-based simulators when using model-type exchange tools, and this means that the advanced functions or classes of RTL simulation tools can be applied using higher-level language tools.

XDEVS: A toolkit for interoperable modeling and simulation of formal discrete event systems

AbstractEmploying Modeling and Simulation (M&S) extensively to analyze and develop complex systems is the norm today. The use of robust M&S formalisms and rigorous methodologies is essential to deal with complexity. Among them, the Discrete Event System Specification (DEVS) provides a solid framework for modeling structural, behavior and information aspects of any complex system. This gives several advantages to analyze and design complex systems: completeness, verifiability, extensibility, and maintainability. DEVS formalism has been implemented in many programming languages and executable on multiple platforms. In this paper, we describe the features of an M&S framework called xDEVS that builds upon the prevalent DEVS Application Programming Interface (API) for both modeling and simulation layers, promoting interoperability between the existing platform‐specific (C++, Java, Python) DEVS implementations. Additionally, the framework can simulate the same model using sequential, parallel, or distributed architectures. The M&S engine has been reinforced with several strategies to improve performance, as well as tools to perform model analysis and verification. Finally, xDEVS also facilitates systems engineers to apply the vision of model‐based systems engineering (MBSE), model‐driven engineering (MDE), and model‐driven systems engineering (MDSE) paradigms. We highlight the features of the proposed xDEVS framework with multiple examples and case studies illustrating the rigor and diversity of application domains it can support.

An Environment for Developing Simulatable AADL-DEVS Models

Reducing complexity in system architecture and design specifications, and more specifically from the software aspect, is essential. The architecture specifications focus on what the requirements and static aspects of systems are. The design specifications define dynamic aspects of computational components that sense and react to external stimuli. As the architecture and design specifications serve complementary roles in developing systems, the use of Architecture Analysis & Design Language (AADL) and Discrete Event System Specification (DEVS) is proposed for developing, in a step-wise fashion, combined architecture and design models. The proposed AADL-DEVS framework is grounded in the foundational modularity and hierarchy principles common to the AADL and DEVS modeling approaches. A realization of this framework capable of transforming and simulating the AADL-DEVS specifications is developed using the Open Source AADL Tool Environment (OSATE) and DEVS-Suite simulator. The scope of this paper is on the computational aspect of systems. The proposed AADL-DEVS framework is demonstrated using a model for the software part of an infant incubator, a time-sensitive and safety–critical system.

State of the art on the conceptual modeling of serious games through a systematic mapping of the literature

Serious games are those games whose objective is to stimulate learning or the acquisition of knowledge or a skill. Currently, there is a trend in the market towards the generation of this type of games. Given the importance of conceptualizing the domain of a problem and its solution, this paper presents the results of a systematic mapping of the literature, Systematic Mapping Study (SMS), with the purpose of identifying the state of the art and discovering the existing contributions regarding the conceptual modeling of serious games. A search was carried out in Scopus, IEEE Xplore and ACM digital libraries from January 2010 to June 2021. Of a total of 558 articles identified, 31 primary studies were analyzed. It was evidenced that the use of UML prevails for the modeling of serious games, mainly for class and activity diagrams, together with other languages ​​such as UP4EG, DSML, Deterministic Finite Automaton (DFA), Discrete Event System Specification (DEVS) and Fuzzy Inference Systems (FIS). Thirty percent of the primary studies propose a framework and another 30% propose a development methodology. Most of these frameworks do not specify how to perform conceptual modeling.