SIMULATION current issue

Guest Editorial: Special Issue on Multi-paradigm Modeling

de Lara, J., Levendovszky, T., Mosterman, P. J. — Wed, 14 Oct 2009 03:03:38 PDT

Exploring Multi-Paradigm Modeling Techniques

Hardebolle, C., Boulanger, F. — Wed, 14 Oct 2009 03:03:38 PDT

Multi-Paradigm Modeling (MPM) addresses the necessity of using multiple modeling paradigms when designing complex systems. Because of its multidisciplinary nature, the MPM field involves research teams with technical backgrounds as different as control science, model checking, modeling language engineering or system-on-chip development. In this paper, we propose to explore the MPM domain through a survey of existing techniques from different horizons. Since the heterogeneity of models is at the heart of MPM, we first identify the sources of this heterogeneity and introduce the problems it raises. Then we show how the different existing techniques address these problems.

Patterns for Automatic Generation of Soft Real-time System Models

Florescu, O., Voeten, J., Theelen, B., Corporaal, H. — Wed, 14 Oct 2009 03:03:38 PDT

Worst-case assumptions about the timing of systems are often too conservative when analyzing distributed soft real-time systems as they lead to over-dimensioned and expensive products. For these systems, a certain percentage of deadline misses is often affordable. Instead of a binary answer regarding the schedulability of such a system, a more interesting metric is the degree to which the system meets the timing requirements. For this, an appropriate model that realistically expresses the behavior of a soft real-time system when deployed on a multiprocessor platform should be built and analyzed. In this article, we present such a modeling approach based on the formal modeling language POOSL (parallel object-oriented specification language). Moreover, to alleviate the process of modeling, we present a pattern-based description language that allows an application, together with the multiprocessor platform and the deployment to be described in a concise way. Such a pattern-based description can be translated automatically into an executable POOSL model through which performance properties can be analyzed based on simulations. The suitability of our approach is demonstrated by exploring the design space of a distributed in-car radio navigation system.

Composable Cellular Automata

Mayer, G. R., Sarjoughian, H. S. — Wed, 14 Oct 2009 03:03:38 PDT

Cellular automata (CA) provide a convenient approach to modeling a system comprised of homogeneous entities that, generally, have a spatial relationship with one another. CA are used to model systems that can be appropriately represented as a collection of interconnected automata. These networked automata may act as either a model representation of the entire system, or used to model a sub-system within a hybrid system. As the sub-systems within a hybrid system are disparate, so too can the models representing them be disparate using a multi-model approach. However, to take advantage of multi-modeling, CA and other models used to represent the sub-systems must be founded on system-theoretical principles. Furthermore, each model’s formalism must account for input and output data exchange with other modeling formalisms. Therefore, to support modular synthesis of distinct CA models with non-CA models, a composable cellular automata (CCA) formalism is proposed. This formalism is provided as a domain-neutral, mathematical specification. The CCA is then exemplified as part of a multi-model, and the GRASS development environment is used to describe one possible implementation approach.

eUDEVS: Executable UML with DEVS Theory of Modeling and Simulation

Risco-Martin, J. L., de la Cruz, J. M., Mittal, S., Zeigler, B. P. — Wed, 14 Oct 2009 03:03:38 PDT

Modeling and simulation (M&S) for system design and prototyping is practiced today both in industry and academia. M&S are two different areas altogether and have specific objectives. However, most of the time these two separate areas are taken together. The developed code is woven tightly around both the model and the underlying simulator that executes it. This constrains both the model development and the simulation engine that has an impact on the scalability of the developed code. Furthermore, a lot of time is spent in developing a model because it needs both domain knowledge and simulation techniques, which also requires communication among users and developers. The Unified Modeling Language (UML) is widely accepted in industry, whereas discrete event specification (DEVS)-based modeling that separates the model and the simulator, provides a cleaner methodology to develop models and is much used in academia. DEVS today is used by engineers who understand discrete event modeling at a highly detailed level and are able to translate requirements to DEVS modeling code. There have been earlier efforts to integrate UML and DEVS but they have not succeeded in providing a transformation mechanism owing to inherent differences in these two modeling paradigms. In this paper we present an integrated approach to cross-transformations between UML and DEVS using the proposed eUDEVS, which stands for executable UML based on DEVS. Further, we also show that the obtained DEVS models belong to a specific class of DEVS models called finite deterministic DEVS (FD-DEVS) that is available as a W3C XML schema in XFD-DEVS. We also put the proposed eUDEVS in a much larger unifying framework called the DEVS unified process that allows bifurcated model-continuity-based lifecycle methodology for systems M&S. Finally, we demonstrate the concepts with a complete example.

Formal Specification and Analysis of Domain Specific Models Using Maude

Rivera, J. E., Duran, F., Vallecillo, A. — Wed, 14 Oct 2009 03:03:38 PDT

Modeling languages play a cornerstone role in model-driven software development for representing models and metamodels. Modeling languages are usually defined in terms of their abstract and concrete syntax. This allows the rapid development of languages and some associated tools (e.g. editors), but does not allow the representation of their behavioral semantics, something especially important in certain industrial environments in which simulation and verification are critical issues. In this paper we explore the use of Maude as a formal notation for describing models, metamodels, and their dynamic behavior, making models amenable to formal analysis, reasoning, and simulation.

Engineering the Dynamic Behavior of Metamodeled Languages

Meszaros, T., Mezei, G., Charaf, H. — Wed, 14 Oct 2009 03:03:38 PDT

Language engineering is a key factor in Multi-Paradigm Modeling (MPM). Since MPM strongly builds on metamodeling, the applied language engineering methods must also be generic enough to support various metamodels. Besides the generic methods to build the abstract and concrete syntax of a visual language, only a few solutions are available to describe the dynamic behavior (‘animation’) of the models. The aim of this paper is to contribute (i) an event-based conceptual architecture to support animation, (ii) a set of visual languages to describe the animation of the models and their execution. These concepts were used to implement the animation support in our tool called Visual Modeling and Transformation System (VMTS). The VMTS animation framework introduces novel languages to describe certain aspects of animation, while integrating the benefits of the existing approaches. Our solution clearly separates the domain knowledge and the animation description both on a conceptual and implementation level. Thus, the VMTS offers a concise and systematic solution to provide a highly customizable animation framework for metamodeled languages with strong integration support to external systems such as simulation engines. The efficiency of the approach is illustrated with a rather complex animation case study implementing a model transformation debugger.