Discrete Event System Specification Research Articles

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.

Practical Formalism-Based Approaches for Multi-Resolution Modeling and Simulation

Multi-resolution modeling (MRM) has been considered as an ideal form of simulation to acquire low-resolution scalability as well as high-resolution modeled details. Although both practical and theoretical interests exist in MRM, actual implementations were quite different in terms of cases and methods. Specifically, MRM implementations range from parameter-based interoperation to model exchanges with different resolutions, yet it is difficult to observe a method that focuses on both of these aspects. To this end, this paper introduces a formalism or multi-resolution translational Discrete Event System Specification (MRT-DEVS). Focusing on the practical perspective, MRT-DEVS intends to ease the implementation’s difficulty and reduce the simulation’s execution costs. Specifically, MRT-DEVS embeds state and event translation functions into the model’s specifications so that it enables MRM with less complex mechanisms in terms of operations. Using the provided case study and a reduction to other MRM methods, the theoretical soundness of the proposed method is supported. Moreover, we discussed the pros and the cons of the proposed method from various MRM perspectives. We expect that with all the provided information, MRMS users would consider the proposed method as a practical option to implement their models.

A holistic digital twin simulation framework for industrial facilities: BIM-based data acquisition for building energy modeling

Energy and resource efficiency as well as reduction of emissions are nowadays significant objectives for production companies. Industry 4.0, through extensive digitalization along the value chain, enables the achievement of these objectives not only in the construction of new facilities but also in existing facilities as well. This requires an interdisciplinary approach, extending over production and logistic processes as well as the building, technical building services, and energy supply systems, consolidated through integrated modeling and simulation-based optimization. The research question this study addresses is how to digitally couple these subsystems and optimize the overall system’s performance in terms of energy and resource efficiency, by distancing from silo-field thinking while using an integrated analysis approach. The article briefly presents a holistic modeling and simulation framework, utilizing modular digital twins (DTs) of all elements that may constitute a given industrial unit. The integration of multiple DTs of these subsystems in a hybrid (continuous and discrete) simulation forms a holistic DT ecosystem of an existing facility. The particular focus of the study is the building representation in this DT ecosystem for energy-efficient production. Based on a methodology including hybrid simulation, building information modeling (BIM), and visual programming, a semi-automated data acquisition workflow was proposed. The hybrid simulation is based on Discrete Event System Specification (DEVS) formalism, where the building is incorporated as a building energy model (BEM). Within the abstracted representation of the overall system, the article explores the possibilities of parametrizing the DT of the building, interconnected with the rest of the factory elements, by acquiring information directly from existing BIM models. Through a comparative case study, the proposed workflow is compared to a manual one in terms of integrity and benefits. The study’s contribution lies in: 1) the detection of the required building level of abstraction for a holistic DT ecosystem, 2) the definition of the interconnections between the building-related counterparts and the rest of the virtual environment as well as the data required for their parameterization, and 3) proposing a semi-automated workflow via virtual programming, for BIM-based creation of the building model within a holistic DT ecosystem.

ST-DEVS: A Methodology Using Time-Dependent-Variable-Based Spatiotemporal Computation

Various real systems are being replicated in cyberspace to solve complex and difficult problems, as exemplified by the digital twin. Once such a software system is implemented, an effective computational method should be applied to the system so that the corresponding real system, connected by networks or sensors, can be indirectly controlled. Considering that all behaviors in real systems occur in space−time, the behavior-related computation in the corresponding software system should adopt both time and space as essential elements to ensure a valid representation of the real system and to effectively perform subsequent computations. Therefore, applying a spatiotemporal computation consisting of time-dependent variables and temporal statements that use such variables is a natural approach to solving problems encountered in the target real system. In this study, the ST-DEVS (spatiotemporal computation DEVS) formalism is proposed to define time-dependent variables and an execution algorithm on temporal logic statements whose arguments are the time-dependent variables; the ST-DEVS is an extension of the discrete event system specification (DEVS). To control real systems with a certain level of autonomy, at least two basic capabilities must be ensured: monitoring and action execution. In this study, action-type temporal logic with time-dependent variables and an action execution algorithm are proposed to illustrate the effectiveness of the spatiotemporal computation process. The previously defined monitoring capability is integrated into ST-DEVS so that monitoring and action execution can be processed uniformly. The proposed approach is designed considering the symmetry between the real world and the cyber world, in that both worlds are influenced by time and space.

XDEVS: A hybrid system modeling framework

When Discrete Event System Specification (DEVS) is used as a modeling tool, there is a semantic gap between a DEVS model and the mathematical representation, which may result in understanding difficulties. To provide a more intuitive form of modeling, XDEVS expands the concept of states in DEVS. The continuous state is introduced in XDEVS, which enhances the ability to model hybrid systems. Based on the DEVS simulation framework, a simulation engine is developed to drive the XDEVS model safely and efficiently and avoid the wrong location of state events during the simulation of the continuous model. A hybrid model is constructed and simulated using XDEVS. A comparison between the XDEVS model and models described by DEV&DESS and GDEVS shows that XDEVS can clearly express the structure of the model and reduce the burden on modelers.

DEVS and MBSE: A review

We review Discrete-Event system Specification (DEVS) in the context of Model-based Systems Engineering (MBSE) and discuss an application of DEVS methodology to MBSE. We outline support for an envisioned MBSE development cycle of DEVS top-to-bottom MBSE capability and offer an example of mapping UML activity diagrams into executable activity-based DEVS models. We close with conclusions and future research directions.

Using Model-to-Model Transformations for Web Software Architecture Simulation

The development of evaluation methods that allow improving the capture of quality data regarding software architectures is a topic of interest in Software Engineering. However, the dynamic of the traditional methods used for architecture evaluation is not enough to deal with the architectural complexity exhibit in new types of software products (such as cloud and web applications). In this paper, we present a model-to-model mapping based on modeling and simulation techniques that can be used as a complement of the traditional evaluation methods to improve the architecture design of complex systems. Using the set of elements that compose the architecture design of web applications, an abstraction model is designed with the aim to define the basic structure for the equivalent simulation model. Such a simulation model is detailed using two discrete-event formalisms: Discrete Event System Specification and Routed DEVS. In each case, a mapping is proposed to capture the full structure of the architecture with all its complexity. We compare both solutions to judge their applicability. Hence, the main advantages and disadvantages of both approaches are analyzed with the aim to evaluate their use in the architecture design stage of Software Engineering projects related to web applications.

A unified cloud-enabled discrete event parallel and distributed simulation architecture

Cloud infrastructure provides rapid resource provision for on-demand computational requirements. Cloud simulation environments today are largely employed to model and simulate complex systems for remote accessibility and variable capacity requirements. In this regard, scalability issues in Modeling and Simulation (M&S) computational requirements can be tackled through the elasticity of on-demand Cloud deployment. However, implementing a high performance cloud M&S framework following these elastic principles is not a trivial task as parallelizing and distributing existing architectures is challenging. Indeed, both the parallel and distributed M&S developments have evolved following separate ways. Parallel solutions has always been focused on ad-hoc solutions, while distributed approaches, on the other hand, have led to the definition of standard distributed frameworks like the High Level Architecture (HLA) or influenced the use of distributed technologies like the Message Passing Interface (MPI). Only a few developments have been able to evolve with the current resilience of computing hardware resources deployment, largely focused on the implementation of Simulation as a Service (SaaS), albeit independently of the parallel ad-hoc methods branch. In this paper, we present a unified parallel and distributed M&S architecture with enough flexibility to deploy parallel and distributed simulations in the Cloud with a low effort, without modifying the underlying model source code, and reaching important speedups against the sequential simulation, especially in the parallel implementation. Our framework is based on the Discrete Event System Specification (DEVS) formalism. The performance of the parallel and distributed framework is tested using the xDEVS M&S tool, Application Programming Interface (API) and the DEVStone benchmark with up to eight computing nodes, obtaining maximum speedups of 15.95× and 1.84×, respectively.

A Simulation Approach to Solve Power System Transmission Problems

The cost of electricity is an indicator of a country's level of development. This industry involves billions of dollars. Hence, the operation of Electric Power Systems constitutes a real problem that consists of a set of stages related to distinct components. In this paper, we propose a novel simulation model to study the state of transmission line systems due to scheduled and unscheduled maintenances. The simulation model is founded in an extension of the Discrete Event System Specification formalism called Routed DEVS. The transmission line system is modeled with a set of discrete-event simulation models that provide a complete state description of components. Such a simulation model can be adapted to describe any transmission line system through a network topology. A case study is presented with aims to show who the simulation works. Our proposal is the starting point to study real-life operations of Electric Power Systems from generation to transmission stages.

Discrete Event Modeling and Simulation for Reinforcement Learning System Design

Discrete event modeling and simulation and reinforcement learning are two frameworks suited for cyberphysical system design, which, when combined, can give powerful tools for system optimization or decision making process for example. This paper describes how discrete event modeling and simulation could be integrated into reinforcement learning concepts and tools in order to assist in the realization of reinforcement learning systems, more specially considering the temporal, hierarchical, and multi-agent aspects. An overview of these different improvements are given based on the implementation of the Q-Learning reinforcement learning algorithm in the framework of the Discrete Event system Specification (DEVS) and System Entity Structure (SES) formalisms.

A methodology to characterise simulation models for discovery and composition: a system theory-based approach to model curation for integration and reuse

We make a strong assumption that we can extract the necessary and sufficient information needed to decide whether a simulation model is suitable to an analyst's problem and that it contains information on how to be configured, integrated, and executed. This assumption allows us to review an approach that is founded on the theory of modelling and simulation and employs tools to develop, simulate, and apply models expressed in the discrete event system specification (DEVS) formalism, a sound systems theory-based computational methodology for system-of-systems model development and deployment. This foundation allows us to discuss how to apply the well-developed theory to curate simulation models so that they can more easily be discovered from a model repository given analytical objectives. After outlining the methodology, we place it in a broader context in which web and cloud-based technologies are employed for integration and to enable modelling and simulation as a service. Significant technical challenges are described that require continued research and development.

Modeling and Simulation of Abnormal Behavior Detection Through History Trajectory Monitoring in Wireless Sensor Networks

Data security is becoming increasingly important with the growing popularity of smart management systems combining wireless sensor networks (WSNs) and intelligent systems in industrial, agricultural, and construction fields. Traditional security methods for WSN have focused on data integrity and the identification of outliers in sensor data and are therefore vulnerable to attacks such as false positive attacks (FPAs) and false negative attack (FNAs) using massively compromised nodes. these attacks significantly compromise the sensor nodes because the correlation between node verification behaviors is not considered in the communication process until the intercepted sensor data are used as input into the system. This study introduces an FPA and FNA detection method using a spatiotemporal historical data-based knowledge base. The main contribution of the present study is the recognition of abnormal correlations using behavior monitoring through the discrete event system specification model. By recognizing abnormal correlations, the proposed method prevents the inflow of false data generated as a result of widespread damage. Furthermore, a new strategy is proposed to maximize the lifetime of the network by blocking any compromised nodes. The proposed spatiotemporal data-based detection approach is applicable to a wide variety of fields owing to its use of a shared security model. The proposed method was shown to reduce the energy consumption by 46.737% and 41.927% in comparison to statistical en-route filtering and cluster-based false-data filtering, respectively.

DEVS-based modular modelling method of dry bulk terminals

ABSTRACT Considering the diversification of dry bulk terminal types and the complexity of terminal loading and unloading operations, a modular modelling method based on discrete event system specification (DEVS) modelling theory is proposed in this paper. First, we introduced the DEVS into the dry bulk terminal and explained the ideas and main steps of the DEVS-based modular modelling method. Second, a module library and model framework library for dry bulk terminals were developed, and the DEVS expression of the modules and model framework was given. Studies have shown that the production performance of a coal export terminal is generally positively correlated with ship loading and ship arrival density. Terminal operators can improve their ability to respond to future scenarios in two ways: upgrading berth levels and improving ship berthing strategies. The case verifies that the model framework and module library are effective, and the modelling method based on DEVS is feasible.

Uncertainty on Discrete-Event System Simulation

Uncertainty Propagation methods are well-established when used in modeling and simulation formalisms like differential equations. Nevertheless, until now there are no methods for Discrete-Dynamic Systems. Uncertainty-Aware Discrete-Event System Specification (UA-DEVS) is a formalism for modeling Discrete-Event Dynamic Systems that include uncertainty quantification in messages, states, and event times. UA-DEVS models provide a theoretical framework to describe the models’ uncertainty and their properties. As UA-DEVS models can include continuous variables and non-computable functions, their simulation could be non-computable. For this reason, we also introduce Interval-Approximated Discrete-Event System Specification (IA-DEVS), a formalism that approximates UA-DEVS models using a set of order and bounding functions to obtain a computable model. The computable model approximation produces a tree of all trajectories that can be traversed from the original model and some erroneous ones introduced by the approximation process. We also introduce abstract simulation algorithms for IA-DEVS, present a case study of UA-DEVS, its IA-DEVS approximation and, its simulation results using the algorithms defined.

Metamodel-based formalization of DEVS atomic models

The Discrete-Event System Specification (DEVS) formalism is a modeling formalism based on systems theory that provides a general methodology for hierarchical construction of reusable models in a modular way. When concrete DEVS models are developed using programming languages, it is difficult to ensure they conform to their formal model. Hence, building an implementation of formal models in a way that ensures DEVS formalism correctness is not easy. In this paper, we improve the interplay of abstraction (i.e., formal specification) and concreteness (i.e., programming code implementation) in advancing the theory and practice of DEVS using a specific-designed metamodel. The main contribution is a novel conceptualization of classic DEVS with ports founded on existing approaches but that also includes new improved elements related to the definition of atomic models. That is, our metamodel includes all the concepts and relationships needed to define the formal specification of DEVS atomic models. This allows us to define instances of our conceptualization that comply with the DEVS formal specification. To instantiate our metamodel, we propose a computer-aided environment that has been developed using the Eclipse Modeling Project. As an example, we show how our metamodel can be used to define the classic “switch” model. As a conclusion, we discuss how the final metamodel can be used to support interoperability with DEVS simulation tools.

Simulation of a Fine Dust Value-Based False Data Detection System to Improve Security In WSN-Based Air Purification IoT

Fine dust refers to harmful substances floating in the air. It is divided into PM 2.5 and PM 10, and has the characteristic that the particles are small enough to be invisible to the naked eye. When fine dust enters a room, it can enter the human body through the bronchi and cause lung or respiratory diseases. To solve the health problems caused by fine dust, research and development about various air purification systems are progressing. In this paper, we introduce a Wireless Sensor Networks (WSNs)-based Internet of Things (IoT) air purification system. This WSNs-based IoT air purification system refers to a system in which an IoT air purifier and a window are automatically controlled based on fine dust values detected by sensor nodes. Therefore, because it is important to maintain the integrity of the fine dust values, SSL/TLS, an encryption protocol, is applied to this system. However, the existing SSL/TLS has a problem in which, if an attacker attempts a false data injection attack, the symmetric key itself used to encrypt and decrypt the data is stolen, so it cannot be detected. To solve this problem, in this paper we propose a Discrete Event System Specification (DEVS) model based on Data Calibration that verifies whether the fine dust values detected by sensor nodes and an IoT air purifier is within a preset error range. If the fine dust value is not within the preset error range, it is detected as false data, filtered, and not stored in the database. Because this proposed scheme verifies the integrity of the fine dust values, it not only raises the accuracy of collected sensing data, but also prevents abnormal operation of an IoT air purifier and a window in advance. Therefore, the security of the WSNs-based IoT air purification system is improved.

A simulation-driven online scheduling algorithm for the maintenance and operation of wind farm systems

Wind turbines experience stochastic loading due to seasonal variations in wind speed and direction. These harsh operational conditions lead to failures of wind turbines, which are difficult to predict. Consequently, it is challenging to schedule maintenance actions that will avoid failures. In this article, a simulation-driven online maintenance scheduling algorithm for wind farm operational planning is derived. Online scheduling is a suitable framework for this problem since it integrates data that evolve over time into the maintenance scheduling decisions. The computational study presented in this article compares the performance of the simulation-driven online scheduling algorithm against two benchmark algorithms commonly used in practice: scheduled maintenance and condition-based monitoring maintenance. An existing discrete event system specification simulation model was used to test and study the benefits of the proposed algorithm. The computational study demonstrates the importance of avoiding over-simplistic assumptions when making maintenance decisions for wind farms. For instance, most literature assumes maintenance lead times are constant. The computational results show that allowing lead times to be adjusted in an online fashion improves the performance of wind farm operations in terms of the number of turbine failures, availability capacity, and power generation.

Computational challenges to test and revitalize Claude Lévi-Strauss transformational methodology

The ambition and proposal for data modeling of myths presented in this paper is to link contemporary technical affordances to some canonical projects developed in structural anthropology. To articulate the theoretical promise and innovation of this proposal, we present a discrete-event system specification modeling and simulation approach in order to perform a generative analysis and a dynamic visualization of selected narratives, aimed at validating and revitalizing the transformational and morphodynamic theory and methodology proposed by Claude Lévi-Strauss in his structural analysis of myth. After an analysis of Lévi-Strauss’s transformational methodology, we describe in detail how discrete-event system specification models are implemented and developed in the framework of a DEVSimPy software environment. The validation of the method involves a discrete-event system specification simulation based on the extension of discrete-event system specification models dedicated to provide a dynamic Google Earth visualization of the selected myth. Future work around the discrete-event system specification formalism in anthropology is described as well as future applications regarding the impact of computational models (discrete-event system specification formalism, Bayesian inferences, and object-oriented features) to new contemporary anthropological domains.

Conjoining Wymore’s Systems Theoretic Framework and the DEVS Modeling Formalism: Toward Scientific Foundations for MBSE

The objective of this research article is to re-introduce some of the concepts provided by A. Wayne Wymore in his mathematical theory of Model-Based Systems Engineering, discuss why his framework might have not been adopted, and define a potential path to modernize the framework for practical application in the digital age. The dense mathematical theory has never been converted to a practical form. We propose a path to modernization by creating a metamodel of Wymore’s mathematical theory of MBSE. This enables explaining the concepts in simple to understand terms and shows the internal consistency provided by the theory. Furthermore, the metamodel allows for conversion of the theory into software application, for which we show some initial results that open the research to the art of the possible. In recognition of limitation of the theory, we make the case for a merger of the theoretical framework with the enhanced formalism of Discrete Event System Specification (DEVS). This will establish a path toward the scientific foundations for MBSE to enable future implementations of the complementary pairing and their empirical results.

Method for Detecting Modification of Transmitted Message in C/C++ Based Discrete Event System Specification Simulation

Method for Detecting Modification of Transmitted Message in C/C++ Based Discrete Event System Specification Simulation