DEVSim++ Toolset for Defense Modeling and Simulation and Interoperation

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.

DISCRETE EVENT BASED APPROACH TO THE SIMULATION OF A CONTINUOUS NAVAL SYSTEM

DEVS-C++, a high-performance environment for modeling large-scale systems at high resolution, uses the DEVS (Discrete-EVent system Specification) formalism to represent both continuous and discrete processes. A prototype suggests that the DEVS formalism can be combined with genetic algorithms running in parallel to serve as the basis of a very general, very fast class of simulation environments.

Employing 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.

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.

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.

Performance analyses of naval ships based on engineering level of simulation at the initial design stage

The 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.

The Routed Discrete Event System Specification (RDEVS) is a modular and hierarchical Modeling and Simulation (M&S) formalism based on the Discrete Event System Specification (DEVS) formalism that provides a set of design models for dealing with routing problems over DEVS. At the formal level, RDEVS models (as DEVS models themselves) are defined mathematically. However, software implementations of both formalisms are based on an object-oriented paradigm. Furthermore, at the implementation design level, the RDEVS formalism is represented by a conceptual model that uses DEVS simulators as execution engines. Even when RDEVS models can be executed with DEVS simulators, the resulting data (obtained as execution outputs) remains DEVS-based, restricting the study of event flows between models influenced by routing policies. This paper shows how the RDEVS formalism design was enhanced to include event tracking in the models without altering their expected behavior during simulation. Such an improvement is based on adding new features to existing RDEVS components. These features are defined as trackers, which are responsible for getting structured data from events exchanged during RDEVS executions. The proposed solution employs the Decorator pattern as a software engineering option to achieve the required goal. It was deployed as a Java package attached to the RDEVS library, devoted to collecting structured event flow data using JavaScript Object Notation (JSON). The results highlight the modeling benefits of adding event tracking to the original capabilities of the RDEVS formalism. For the M&S community, the novel contribution is an advance in understanding how best modeling practices of software engineering can be used to enhance their software tools in general and the RDEVS formalism in particular.

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.

The industry has experienced significant advancements in recent years, primarily focusing on smart manufacturing, culminating in the Industry 4.0 (I4.0) revolution I4.0 emphasizes interconnectivity, real time data capture and transmission among machines, autonomy, and machine learning, providing manufacturing companies numerous growth opportunities. The Industrial Internet of Things (IIoT) is a core component of this revolution, becoming integral to each system and increasing complexity due to the vast number of interconnected devices and diverse physical components. The variety of virtual services distributed across the architectural layers of industrial systems (cloud, fog, edge) and the various connection types between IIoT devices introduce security and privacy challenges, which are critical issues for any system incorporating IIoT. To fully leverage IIoT’s potential, addressing these security and privacy concerns is essential. Research and design in this domain are challenging, particularly when creating a simulation environment to study a system’s behavior over time. Despite the extensive research in IoT and the significant benefits of simulation based approaches, there remains a challenge in creating detailed representations from the underlying IoT nodes to the application layer in the cloud, along with the underlying networking infrastructure. To assist researchers and practitioners in overcoming these challenges, we propose the Discrete Event System Specification (DEVS) formalism. DEVS provides a mathematical framework for modeling systems, whether discrete or continuous events, allowing for the simulation of these systems within the DEVS environment. Every system, whether real or conceptual, has a time base, inputs, outputs, and functions to determine the next state, as well as outputs that reflect the current state and inputs. Simulating the system within the DEVS environment allows one to study its behavior to predict and optimize performance patterns.

We introduce a generic method based on the Discrete Event System Specification (DEVS) formalism to model and simulate a Controller Area Network (CAN) port connected to a network with other nodes. The models are tested in software and then implemented in hardware. We show a streamlined development process to model, simulate, and test the use of the CAN network for any general application using the Cadmium simulation environment for software simulations and executing the models on hardware using Real-Time (RT-) DEVS. With this method, different scenarios can be tested in the modeling and simulation phase before the models are ported onto embedded hardware.

선박에 현대화된 다양한 항해장비들이 설치됨에도 불구하고 여전히 해양사고가 자주 일어나는데, 이런 사고의 주요 형태 중 하나가 충돌 사고이다. 우리나라 해양사고의 약 1/4이 충돌에 의한 사고이고, 이 중 대부분이 인적오류가 원인인 것으로 알려져 있다. 따라서, 항해사의 의사결정을 도울 수 있는 지능적인 지원 도구가 필요한데, 이와 관련하여 충돌위험을 추정하는 다양한 방식들이 꾸준히 소개되어 왔으며 충돌위험 상황에 대해 사람에게 친숙한 언어적 표현을 반영하여 추론하기 위해 퍼지를 활용한 연구 결과들이 많다. 이런 기존 연구들의 충돌위험도는 현재시점에서 선박들의 속도나 방향 상태가 유지되는 것을 기준으로 충돌위험도를 추정한다. 그러나, 실제 선박에서는 충분히 피항 가능 상황임에도 불구하고 충돌 위험으로 판단되어 잦은 경고를 울리는 시스템들에 대해 항해사들이 느끼는 불편함이 적지 않아 보조 장치들의 알람 기능을 꺼놓은 경우도 많은 것으로 알려져 있다. 이 연구는 선박들의 일반적인 피항 패턴을 반영한 가까운 미래 시점의 충돌위험도 예측에 관한 것으로서, 퍼지추론과 DEVS 형식론에 기반한 충돌 위험 예측 모델을 제안한다. Even thought modernized marine navigation devices help navigators, marine accidents has been often occurred and ship collision is one of the main types of the accidents. Various studies on the assessment method of collision risk have been reported, and studies using fuzzy theory are remarkable for the reason that reflect linguistic and ambiguous criteria for real situations. In these studies, collision risks were assessed on the assumption that the current state of navigation ship would be maintained. However, navigators ignore or turn off frequent alarms caused by the devices predicting collision risk, because they think that they can avoid the collisions in the most of situations. This paper proposes a model of predicting ship collision risk considering the general patterns of collision avoidance, and the approach is based on fuzzy inference and discrete event system specification (DEVS) formalism.

Proposed in this paper is the architecture of a PLC programming environment that enables a visual verification of PLC programs. The proposed architecture integrates a PLC program with a corresponding plant model, so that users can intuitively verify the PLC program in a 3D graphic environment. The plant model includes all manufacturing devices of a production system as well as corresponding device programs to perform their tasks in the production system, and a PLC program contains the control logic for the plant model. For the implementation of the proposed PLC programming environment, it is essential to develop an efficient methodology to construct a virtual device model as well as a virtual plant model. The proposed PLC programming environment provides an efficient construction method for a plant model based on the DEVS (Discrete Event Systems Specifications) formalism, which supports the specification of discrete event models in a hierarchical, modular manner.