A novel parallelization technique for DEVS simulation of continuous and hybrid systems

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.

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).

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.

The recent emerging trend to promote the harmonious interactions between human and smart objects in Internet of Things (IoT) applications has led to the rising demand for the comprehensive exploration of associated IoT design spaces, considering system-, network-, and human-level perspectives. The traditional design approach of networked smart objects tends to ignore the effects caused by human interactions so that the existing approach has the limited capability in joint system/network/human multi-level exploration. In this paper, we propose a high-level system modeling and multi-level simulation approach for microsystem models to interoperate with high-level models in the human-level perspective and to provide comprehensive co-exploration. The high-level system modeling enables one to abstract the detailed operations of hardware platforms using power and timing data obtained by the proposed high-level state-based profiling method and using the event-driven modeling concept. For the event-driven system modeling, we utilize the discrete-event system specification (DEVS) to support scalable model-driven prototyping. To represent the coupled relationship of network-level system activity and human-level interactions between node systems and humans, we employ a general-purpose network simulator to model the operation and communication of network modules in smart objects and developed agent-based human behavioral models. For the co-simulation of multi-level models, we designed a distributed simulation platform to enable the interoperation between the DEVS simulator and the network simulator using a runtime infrastructure. The proposed modeling and simulation approach is applied for the multi-level evaluation of a smart museum application to estimate the effect of energy-efficiency policies.

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.

본 논문은 홈 네트워크 기반에서 멀티미디어 공동 작업 공간을 위한 화이트보드에 대해서 제안하였다. 본 시스템은 공동 작업에 참여한 사용자들이 다른 참여자들에게 같은 뷰로써 공유된 미디어들을 참조할 수 있도록 구축한다. 본 논문에서는 화이트보드를 통하여 미디어 데이터의 신뢰성을 향상시키는 방법에 대해서 기술한다. 본 논문은 규칙-기반 DEVS(Discrete Event System Specification) 모델링과 시뮬레이션 기법을 사용하면서 분산 멀티미디어 상에서 화이트보드를 이용한 미디어 데이터 시스템의 성능 분석을 설명한다. This paper suggested a whiteboard for multimedia collaboration work. We implemented the whiteboard so that the users participated in collaborative work may refer shared media objects as the same view to others. In this paper, we discuss a method for increasing reliability of media data through whiteboard. This paper explains a performance analysis of a media data system running on distributed multimedia environment using the rule-based DEVS modeling and simulation techniques.

Fine-Grained Parallel and Distributed Spatial Stochastic Simulation of Biological Reactions

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.

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.

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.

Simulation models of continuous systems are in fact discrete computational models. This is the result of applying numerical methods for integrating the differential equations generally used as mathematical models of continuous systems. Under such conditions the values of all variables in the simulation model are computed for discrete values of the independent variable time , separated by a fixed or variable step , according to the integration method used. Each value of the independent variable time for which the simulation model state changes can be considered as the time point when an event takes place. Such point of view leads to an obvious conclusion: continuous systems simulation can be performed using a discrete event simulator. This approach is very important in those cases when the considered system has a combined (discrete event and continuous) model and the available simulation tool does not provide for continuous systems modeling.

The numerical simulation of non-smooth hybrid systems exhibiting chattering behavior requires high computational costs. In the worst case, the simulation appears to come to a halt, since infinitely many discrete transitions would need to be simulated. In this paper we present an FMI-based framework and prototypical implementation for robust and reliable detection and elimination “On the Fly” of chattering behavior in run-time simulation of non-smooth hybrid systems. The main benefit of the developed framework is that it establishes solvability requirements and theorems for simulating hybrid systems while performing the chattering path avoidance internally in the master algorithm of the interface. This increases the efficiency of the chattering-free simulation as no enumeration of modes is required during the chattering detection and elimination process. The developed FMI-based framework can generate a chattering-free simulation for any generic chattering Functional Mockup Unit (FMU) conforming to the FMI standard v2.0 Specification for model exchange.

Solid oxide fuel cell (SOFC)/ gas turbine (GT) hybrid systems possess the capacity for unprecedented performances, such as electric efficiencies nearly twice that of conventional heat engines at variable scale power ratings inclusive of distributed generation. Additionally, these hybrids can have excellent operational flexibility with turndowns possibly as great as 85%. There are, however, developmental needs such as turbomachinery characterization and re-design. A leading example is that of greater propensity to have occurrences of stall-surge given the significantly different operating environment in contrast to conventional heat engines. Additionally, dynamic variation in power generation has to be done with significant a priori insight to avoid thermomechanical threats to cell stack and turbomachinery. State-of-the-art approaches involving hardware-in-the-loop simulation and, ultimately, additive manufacturing are being pursued to enable such characterization and re-design considerations given variable and dynamic operability requirements. Compressor performance in hybrid systems has been characterized at the United States National Energy Technology Laboratory (NETL), inclusive of a capability of feed forward hardware-in-the-loop simulation of hybrid systems under dynamic conditions and a capability of replacing turbine and compressor components at a relatively low cost. This paper highlights some of the simulation results, and the net result is an approach that addresses hybrid system developmental needs for accommodating generation transients.

We consider the sharing of processors in parallel computer systems. In general, the main goal of the systems, better performance, decreases processor utilization. We model and simulate a multi-tasking parallel operating system, and estimate its performance degradation and overall system throughout in the case where threads share a processor. We formalize the system by using DEVS (Discrete Event System Specification), and implement it in the DEVS simulation environment. Simulation results show that the processor sharing between threads is acceptable in the sense of TPP (throughput per processor).