Enhancing Routed DEVS Models with Event Tracking

Artificial neural networks (ANNs), a branch of artificial intelligence, has become a very interesting domain since the eighties when back-propagation (BP) learning algorithm for multilayer feed-forward architecture was introduced to solve nonlinear problems. It is used extensively to solve complex nonalgorithmic problems such as prediction, pattern recognition and clustering. However, in the context of a holistic study, there may be a need to integrate ANN with other models developed in various paradigms to solve a problem. In this paper, we suggest discrete event system specification (DEVS) be used as a model of computation (MoC) to make ANN models interoperable with other models (since all discrete event models can be expressed in DEVS, and continuous models can be approximated by DEVS). By combining ANN and DEVS, we can model the complex configuration of ANNs and express its internal workings. Therefore, we are extending the DEVS-based ANN proposed by Toma et al. [A new DEVS-based generic artficial neural network modeling approach, The 23rd European Modeling and Simulation Symp. (Simulation in Industry), Rome, Italy, 2011] for comparing multiple configuration parameters and learning algorithms and also to do prediction. The DEVS models are described using the high level language for system specification (HiLLS), [Maïga et al., A new approach to modeling dynamic structure systems, The 29th European Modeling and Simulation Symp. (Simulation in Industry), Leicester, United Kingdom, 2015] a graphical modeling language for clarity. The developed platform is a tool to transform ANN models into DEVS computational models, making them more reusable and more interoperable in the context of larger multi-perspective modeling and simulation (MAS).

Discrete event models are widely used to replicate, analyze, and understand complex systems. DEVS (Discrete Event System Specification) formalism enables hierarchical modeling, so it provides an efficiency in the model development of complex models. However, the hierarchical modeling incurs prolonged simulation executions due to indirect event exchanges through the model hierarchy. Although direct event paths are applied to mitigate this overhead, the situation becomes even worse when a model changes its structures during simulation execution, called a dynamic structure model. This article suggests Coupling Relation Graph (CRG) and Strongly Coupled Component (SCC) concepts to improve hierarchical and dynamic structure DEVS simulation execution. CRG is a directed graph representing DEVS model structure, and SCC is a group of connected components in a CRG. Using CRG and SCC, this article presents (1) how to develop CRG from a DEVS model and (2) how to construct and update direct event paths with respect to dynamic structural changes. In particular, compared to the previous works, the proposed method focuses on the reduction of the updating costs for the direct event paths. Through theoretical and empirical analyses, this article shows that the proposed method significantly reduces the simulation execution time, especially when a simulation model contains lots of components and changes its model structures frequently. We expect that the proposed method would support the faster simulation executions of complex hierarchical and dynamic structure models.

Real-time systems modeling and verification is a complex task. In many cases, formal methods have been employed to deal with the complexity of these systems, but checking those models is usually unfeasible. Modeling and simulation methods introduce a means of validating these model’s specifications. In particular, Discrete Event System Specification (DEVS) models can be used for this purpose. Here, we introduce a new extension to the DEVS formalism, called the Rational Time-Advance DEVS (RTA-DEVS), which permits modeling the behavior of real-time systems that can be modeled by the classical DEVS; however, RTA-DEVS models can be formally checked with standard model-checking algorithms and tools. In order to do so, we introduce a procedure to create timed automata (TA) models that are behaviorally equivalent to the original RTA-DEVS models. This enables the use of the available TA tools and theories for formal model checking. Further, we introduce a methodology to transform classic DEVS models to RTA-DEVS models, thus enabling formal verification of classic DEVS with an acceptable accuracy.

Discrete Event Systems Specification (DEVS) formalism supports the specification of discrete event models in a hierarchical and modular manner. Efforts have been made to develop the simulation environments for the modeling and simulation (M&S) of systems using DEVS formalism, particularly in defense M&S domains. This paper introduces the DEVSim++ toolset and its applications. The Object-Analysis Index (OAI) matrix is a tabular form of objects and analysis indices for requirements analysis. DEVSim++ is a realization of DEVS formalism in C++ for M&S. VeriTool is a DEVS model verification tool. DEVSimHLA is a library to support High-level Architecture (HLA) in DEVSim++. Other tools, including KComLib, FOM2CPPClass, and KHLAAdaptor, are used to develop a smart adaptor that allows for the interoperation of simulators of any kind. PlugSim is a distributed simulation framework using plug-in methods. These tools are utilized in every stage of the M&S development process, as well as in every application of the M&S missions to the military domain. Accordingly, the applications implemented by the toolset are used in the training, analytic, and acquisition missions of the Republic of Korea military branches. We expect the DEVS applications to become more prolific as M&S demands grow, and our toolset is already proven as complete and efficient in the domain of defense M&S.

System models are constructed to design, study, and understand complex systems. According to the systems modeling language (SysML) that is a standard for model-based system engineering, all engineering activities should be performed using a common model. To validate complex system models defined in SysML, simulation is usually employed. There are numerous efforts to simulate SysML models using different simulation methods and tools. However, the efficient support of automated generation of executable simulation code is still an issue tangled by the research community. This paper introduces DEVSys, an integrated framework for utilizing existing SysML models and automatically producing executable discrete event simulation code, according to model driven architecture (MDA) concepts. Although this approach is not simulation-specific, discrete event system specification (DEVS) was employed, due to the similarities between SysML and DEVS, mainly in system structure description, and the mature, yet ongoing research on expressing executable DEVS models in a simulator-neutral manner. DEVSys framework elements include (a) a SysML profile for DEVS, enabling integration of simulation capabilities into SysML models, (b) a meta-model for DEVS, allowing the utilization of MDA concepts and tools, (c) a transformation of SysML models to DEVS models, using a standard model transformation language as query/view/transform (QVT), and (d) the generation of DEVS executable code for a DEVS simulation environment with an extensible markup language (XML) interface. The definition and implementation of DEVSys elements, as well as the process for its application are demonstrated and discussed, with the aid of a simple working example.

In this paper, we introduce a novel parallelization technique for Discrete Event System Specification (DEVS) simulation of continuous and hybrid systems. Here, like in most parallel discrete event simulation methodologies, the models are first split into several sub-models which are then concurrently simulated on different processors. In order to avoid the cost of the global synchronization of all processes, the simulation time of each sub-model is locally synchronized in a real-time fashion with a scaled version of physical time, which implicitly synchronizes all sub-models. The new methodology, coined Scaled Real-Time Synchronization (SRTS), does not ensure a perfect synchronization in its implementation. However, under certain conditions, the synchronization error introduced only provokes bounded numerical errors in the simulation results. SRTS uses the same physical time-scaling parameter throughout the entire simulation. We also developed an adaptive version of the methodology (Adaptive-SRTS) where this parameter automatically evolves during the simulation according to the workload. We implemented the SRTS and Adaptive-SRTS techniques in PowerDEVS, a DEVS simulation tool, under a real-time operating system called the Real-Time Application Interface. We tested their performance by simulating three large-scale models, obtaining in all cases a considerable speedup.

Discrete event system specification (DEVS), a formalism for modeling and simulation, has been recently applied to the engineering of CPS, which also makes the necessity of model checking for DEVS arisen. Model-transformation-based approaches were first proposed; timed or linear hybrid automata are obtained from DEVS models, and then verified using model checkers. But, due to the different semantics in state transitions, the transformation often involves manual tasks, such as abstraction and approximation. To eliminate such manual tasks, we have proposed a DEVS subclass that is less expressive, but verifiable. For reachability analysis, its models can be interpreted as transition systems and region automata (RA). Although our DEVS subclass and RA have different semantics with respect to model execution, they are equivalent in terms of reachability analysis. Thus, the reachability could be analyzed based on model checking techniques of timed automata. In many DEVS-based environments, models should be developed by programming languages. To enables the modelers to specify CPS in a visual way, we have proposed a visual modeling language based on our subclass. In our language, the behavior and structure of CPS are graphically specified by basic model diagrams and coupled model diagrams, respectively. Based on our subclass and languages, we have implemented a proof-of-concept environment that supports visual modeling of CPS as well as simulation and reachability analysis of the models. To enable the consideration of the hybrid nature and heterogeneity in CPS, DEVS subclasses, languages, verification techniques and environments will be further investigated.

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.

시뮬레이션 프레임워크는 시뮬레이션 응용 프로그램의 개발을 지원하는 기반 소프트웨어이다. 본 논문은 공학용 프로그래밍 언어로 광범위하게 사용되는 매트랩을 이용하여 개발된 이산사건시뮬레이션 프레임워크의 개발 과정을 기술하고 있다. 매트랩 객체지향프로그래밍을 토대로 새롭게 개발된 프레임워크는 매트랩 언어의 편리성과 이산사건시뮬레이션 형식론(DEVS: Discrete EVent System Specification Formalism)이 가지는 뛰어난 개발 방법론을 결합시킴으로써 무기체계 교전 시뮬레이션 프로그램 개발에서 요구되는 생산성, 유연성, 확장성을 제공한다. 더불어 매트랩의 병렬컴퓨팅 기술을 적용한 배치(Batch) 시뮬레이션 기능을 제공함으로써 몬테카를로 시뮬레이션 수행시 컴퓨터 환경에서 지원되는 CPU 코어의 수에 비례하여 응용 프로그램의 연산성능을 향상시킨다. Simulation Framework is a basic software tool used to develop simulation applications. This paper describes the development of a discrete event simulation framework based on DEVS(Discrete EVent System Specification) formalism, using MATLAB language which is widely used in technical computing and engineering disciplines. The newly developed framework utilizing MATLAB object oriented programming combines the convenience of MATLAB language and the sophisticated architecture of the DEVS formalism. Hence, it supports the productivity, flexibility, extensibility that are required for the simulation application software development of the weapon systems engagement. Moreover, it promises a simulation application the increased the computation speed proportional to the number of CPU of a multi-core processor, providing the batch simulation functionality based on MATLAB parallel computing technology.

This paper deals with dynamic visualization of folktales on a map. The visualization is performed using a coupling of dynamic simulation with the google earth API. The simulation is based on the DEVS (Discrete EVent system Specification) formalism. We have defined a set of basic models to perform visualization of folktales using a software framework called DEVSimPy. DEVSimPy is a framework dedicated to DEVS modeling and simulation of complex systems. We also present in this paper a validation of the developed basic models based on folktales coming from the Corsican mythology.

This paper presents a composable cognitive agent meta-model for multi-agent simulation based on the DEVS (Discrete Event System Specification) framework. We describe an attempt to compose a PRS-based cognitive agent by merely combining plug and play DEVS components, show how this DEVS-based cognitive agent meta-model is extensible to serve as a higher-level component for M&S of multi-agent systems, and how the agent meta-model components are reusable to ease cognitive agent modelling development. In addition to an overview of our agent meta-model, we also describe the components of the model specification and services in detail. To test the feasibility of our design, we constructed a simulation based on a Rock-Paper-Scissors game scenario. We also give out comparisons between this agent meta-model and other cognitive agent models. Our agent meta-model is novel in terms of both agent and agent components as these are all abstracted using the DEVS formalism. As different implementations of agent model components are based on the same meta-model components, all the developed agent model components can be reused in the development of other agent models which increases the composability of the agent model, and the whole cognitive agent model can be considered as a coupled model in the DEVS model hierarchy which supports multi-hierarchy modelling.

In this chapter, we formalize the multi-perspective architecture framework using the system-theoretic paradigm provided by the discrete event system specification (DEVS) formalism. The developed integration approach that allows linking up the isolated perspectives has been formalized through a concept based upon DEVS formalism called parameterized DEVS, whereby concurrent simulation processes cause live update through output-to-parameter integration. This sets up the basis for development of DEVS-based holistic models for efficient management of healthcare systems. Results of real case-based simulations are presented to show how holistic models provide new insights not heretofore attainable with unit and facility specific models.

A hybrid model is a combination of models developed in various simulation development environments. A war game model is a kind of hybrid model and consists of multiple level models. Engineering level models are interested in the change of values via time and process mathematical equations, and most of them are developed in MALTAB/Simulink. Engagement level models are concerned about state transitions by events and modeled using the Discrete Event Systems Specification (DEVS) formalism. This paper proposes a framework for interoperation of simulation tools for engineering and engagement level models simulation. The framework employs the High Level Architecture (HLA) to reuse existing models and suggests specific interfaces for MATLAB/Simulink. The proposed framework is demonstrated through simulation of a simple war game model including heterogenous models.

Discrete Event System Specification (DEVS) 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 (or internal timeouts) cause instantaneous changes to the state of the system. Main advantages of DEVS are its rigorous formal definition 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, for example in performance analysis of queueing systems. All examples are presented with the tool PythonPDEVS, though this introduction is equally applicable to other DEVS tools. We conclude with further reading on DEVS theory, DEVS variants, and DEVS tools.

It is shown how systems can be advantageously represented as discrete event models by using DEVS (discrete event system specification), set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based control paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems. >