Mathias Röhl

Composing simulations from XML-specified model components

This paper is about the flexible composition of efficient simulation models. It presents the realization of a component framework that can be added as an additional layer on top of simulation systems. It builds upon platform independent specifications of components in XML to evaluate dependency relationships and parameters during composition. The process of composition is split up into four stages. Starting from XML documents component instances are created. These can be customized and arranged to form a composition. Finally, a composition is transformed to an executable simulation model. The first three stages are general applicable to simulation systems; the last one depends on the parallel DEVS formalism and the simulation system James II

Introducing variable ports and multi-couplings for cell biological modeling in DEVS

Motivated by the requirements of molecular biological applications, we are suggesting an extension of the DEVS formalism. Starting with DYNDEVS a reflective variant of DEVS which supports dynamic behavior, composition, and interaction pattern, we develop rho-DEVS. Dynamic ports and multi-couplings are introduced whose combination allows models to reflect significant state changes to the outside world and enabling or disabling certain interactions at the same time. An abstract simulator describes the operational semantics of the developed formalism, and the Tryptophan operon model illustrates the developed ideas and concepts

Flexible integration of XML into modeling and simulation systems

As the effort towards standardization of formalism representations increases so does the need for verifying whether models do or do not follow a standard. Data binding allows to systematically exploit XML and its associated technologies for modeling and simulation purposes. Based on the schema definition of a formalism, a binding compiler generates model classes that support the user in constructing models according to the formalism. Most constraints can be checked automatically, few require separate efforts by the designer of the simulation system. Although simulators could be build for these declarative model descriptions, they would be hardly efficient. To this end, a separate transformation component is required. In this overall process, both model specifications that are consistent with a formalism definition and models that can be executed efficiently are supported equally.

Definition and analysis of composition structures for discrete-event models

The re-use of a model by someone else than the original developer is still an open challenge. This paper presents composition structures and interface descriptions for discrete-event models. Interfaces are introduced as separate units of description that complement model definitions. As XML documents, interfaces may be stored in databases to search, select, and analyze composition candidates based on public visible property descriptions. A meta model formalizes interfaces, components, and compositions, such that the refinement of interfaces into model implementations and the compatibility of interfaces can be analyzed. The composition approach combines different hierarchical relations (type hierarchies, refinement hierarchies, and composition hierarchies) to simplify the modeling process.

Controlled Experimentation with Agents — Models and Implementations

The deployment of multi-agent systems demands for justified confidence into their functioning, both with respect to correctness of behaviour and with respect to timeliness thereof. Depending on the stage of the development process different mechanisms and abstractions are needed to facilitate the evaluation of interacting agents. We propose a modelling and simulation framework based on a discrete-event formalism for supporting the development process of multi-agent systems; from specification to implementation. The framework allows for the incremental refinement of agents and experimental set-ups while providing rigorous observation facilities. The benefit of using discrete-event modelling and simulation techniques for evaluating agents is illustrated using a simple example based on the Contract Net Protocol.

Hierarchical modeling for computational biology

Diverse hierarchies play a role in modeling and simulation for computational biology, e.g. categories, abstraction hierarchies, and composition hierarchies. Composition hierarchies seem a natural and straightforward focus for our exploration. What are model components and the requirements for a composite approach? How far do they support the quest for building blocks in computational biology? Modeling formalisms provide different means for composing a model. We will illuminate this with DEVS (Discrete event systems specification) and the π calculus. Whereas in DEVS distinctions are emphasized, e.g. between a system and its environment, between properties attributed to a system and the system itself, these distinctions become fluent in the compact description of the π calculus. However, both share the problem that in order to support a comfortable modeling, a series of extensions have been developed which also influence their possibility to support a hierarchical modeling. Thus, not individual formalisms but two families of formalisms and how they support a composite modeling will be presented. In computational biology one type of composite model deserves a closer inspection, as it brings together the wish to compose models and the need to describe a system at different levels in a unique manner, i.e. multi-level models.

Composing simulation models using interface definitions based on web service descriptions

Using models in different contexts poses major integration challenges, ranging from technical to conceptual levels. Independently of each other developed model components cannot be expected to coincide in all description details, even if based on the same abstractions and assumptions. Variations in interface descriptions of model components have to be resolved. XML-based description languages from the area of web services provide standardized means for bridging diversities of implementations. This paper presents an adaption of the Web Services Description Language (WSDL) combined with XML Schema Definitions (XSD) to the specific requirements of model components in the area of discrete-event simulation. XML-based interface descriptions are integrated into a general model component architecture. Schema matching approaches provide the basis for syntactical compatibility checking of interfaces at the time of composition.

Platform Independent Specification Of Simulation Model Components

Simulation model composability is a highly debated issue, especially the specific requirements of model components as compared to software components. Selected software component techniques are reviewed and adapted according to simulation models needs. Standard technologies like UML and XML are exploited to form the basis for a specification layer that wraps model definitions. This layer accounts for explicit dependencies, compositions, and parametrization of simulation models. Thereby, the specification of model components can be done in a platform and simulation system independent manner. For the purpose of simulation a mapping to a concrete modeling formalism becomes necessary. This is here done on the example of the Parallel DEVS formalism. Keywords—Model Components, XML, UML, Parallel DEVS

Test derivation from timed automata

A real-time system is a discrete system whose state changes occur in real-numbered time [AH97]. For testing real-time systems, specification languages must be extended with constructs for expressing real-time constraints, the implementation relation must be generalized to consider the temporal dimension, and the data structures and algorithms used to generate tests must be revised to operate on a potentially infinite set of states.

One Modelling Formalism & Simulator Is Not Enough! A Perspective for Computational Biology Based on James II

Diverse modelling formalisms are applied in Computational Biology. Some describe the biological system in a continuous manner, others focus on discrete-event systems, or on a combination of continuous and discrete descriptions. Similarly, there are many simulators that support different formalisms and execution types (e.g. sequential, parallel-distributed) of one and the same model. The latter is often done to increase efficiency, sometimes at the cost of accuracy and level of detail. James II has been developed to support different modelling formalisms and different simulators and their combinations. It is based on a plug-in concept which enables developers to integrate spatial and non-spatial modelling formalisms (e.g. stochastic i¾? calculus , Beta binders , Devs , space- i¾?), simulation algorithms (e.g. variants of Gillespies algorithms (including Tau Leaping and Next Subvolume Method ), space- i¾?simulator, parallel Beta binders simulator) and supporting technologies (e.g. partitioning algorithms, data collection mechanisms, data structures, random number generators) into an existing framework. This eases method development and result evaluation in applied modelling and simulation as well as in modelling and simulation research.