849 research outputs found
Virtual Communication Stack: Towards Building Integrated Simulator of Mobile Ad Hoc Network-based Infrastructure for Disaster Response Scenarios
Responses to disastrous events are a challenging problem, because of possible
damages on communication infrastructures. For instance, after a natural
disaster, infrastructures might be entirely destroyed. Different network
paradigms were proposed in the literature in order to deploy adhoc network, and
allow dealing with the lack of communications. However, all these solutions
focus only on the performance of the network itself, without taking into
account the specificities and heterogeneity of the components which use it.
This comes from the difficulty to integrate models with different levels of
abstraction. Consequently, verification and validation of adhoc protocols
cannot guarantee that the different systems will work as expected in
operational conditions. However, the DEVS theory provides some mechanisms to
allow integration of models with different natures. This paper proposes an
integrated simulation architecture based on DEVS which improves the accuracy of
ad hoc infrastructure simulators in the case of disaster response scenarios.Comment: Preprint. Unpublishe
Multi-level agent-based modeling with the Influence Reaction principle
This paper deals with the specification and the implementation of multi-level
agent-based models, using a formal model, IRM4MLS (an Influence Reaction Model
for Multi-Level Simulation), based on the Influence Reaction principle.
Proposed examples illustrate forms of top-down control in (multi-level)
multi-agent based-simulations
Extending the DEVS Formalism with Initialization Information
DEVS is a popular formalism to model system behaviour using a discrete-event
abstraction. The main advantages of DEVS are its rigourous and precise
specification, as well as its support for modular, hierarchical construction of
models. DEVS frequently serves as a simulation "assembly language" to which
models in other formalisms are translated, either giving meaning to new
(domain-specific) languages, or reproducing semantics of existing languages.
Despite this rigourous definition of its syntax and semantics, initialization
of DEVS models is left unspecified in both the Classic and Parallel DEVS
formalism definition. In this paper, we extend the DEVS formalism by including
an initial total state. Extensions to syntax as well as denotational (closure
under coupling) and operational semantics (abstract simulator) are presented.
The extension is applicable to both main variants of the DEVS formalism. Our
extension is such that it adds to, but does not alter the original
specification. All changes are illustrated by means of a traffic light example
A Vectorial DEVS Extension for Large Scale System Modeling and Parallel Simulation
In this article we introduce an extension to the Discrete Event System (DEVS) formalism called Vectorial DEVS (VECDEVS) that allows to represent large scale systems in a graphic block diagram way. A pure VECDEVS model basically consist in an array of identical classic DEVSmodels that may differ in their parameters. The interconnection of VECDEVS models with some special classic DEVS models that can handle VECDEVS events allows to easily represent large systems of arbitrary structure. A noticeable feature of this extension is that VECDEVS models can be easily split for parallel simulation. For that purpose, we developed an algorithm that automatically splits VECDEVS models into an arbitrary number of sub-models for parallel simulation. The implementation of VECDEVS and the partitioning algorithm in a DEVS simulation tool is also described and its usage is illustrated through some application examples.Fil: Bergero, Federico. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Rosario. Centro Internacional Franco Argentino de Ciencias de la InformaciĂłn y Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Rosario. Centro Internacional Franco Argentino de Ciencias de la InformaciĂłn y Sistemas; Argentin
Toward composing variable structure models and their interfaces: a case of intensional coupling definitions
In this thesis, we investigate a combination of traditional component-based and variable structure modeling. The focus is on a structural consistent specification of couplings in modular, hierarchical models with a variable structure. For this, we exploitintensional definitions, as known from logic, and introduce a novel intensional coupling definition, which allows a concise yet expressive specification of complex communication and interaction patterns in static as well as variable structure models, without the need to worryabout structural consistency.In der Arbeit untersuchen wir ein Zusammenbringen von klassischer komponenten-basierter und variabler Strukturmodellierung. Der Fokus liegt dabei auf der Spezifikation von strukturkonsistenten Kopplungen in modular-hierarchischen Modellen mit einer variablen Struktur. DafĂĽr nutzen wir intensionale Definitionen, wie sie aus der Logik bekannt sind, und fĂĽhren ein neuartiges Konzept von intensionalen Kopplungen ein, welches kompakte gleichzeitig ausdrucksstarke Spezifikationen von komplexen Kommunikations- und Interaktionsmuster in statischen und variablen Strukturmodellen erlaubt
Dynamic Data Driven Application System for Wildfire Spread Simulation
Wildfires have significant impact on both ecosystems and human society. To effectively manage wildfires, simulation models are used to study and predict wildfire spread. The accuracy of wildfire spread simulations depends on many factors, including GIS data, fuel data, weather data, and high-fidelity wildfire behavior models. Unfortunately, due to the dynamic and complex nature of wildfire, it is impractical to obtain all these data with no error. Therefore, predictions from the simulation model will be different from what it is in a real wildfire. Without assimilating data from the real wildfire and dynamically adjusting the simulation, the difference between the simulation and the real wildfire is very likely to continuously grow. With the development of sensor technologies and the advance of computer infrastructure, dynamic data driven application systems (DDDAS) have become an active research area in recent years. In a DDDAS, data obtained from wireless sensors is fed into the simulation model to make predictions of the real system. This dynamic input is treated as the measurement to evaluate the output and adjust the states of the model, thus to improve simulation results. To improve the accuracy of wildfire spread simulations, we apply the concept of DDDAS to wildfire spread simulation by dynamically assimilating sensor data from real wildfires into the simulation model. The assimilation system relates the system model and the observation data of the true state, and uses analysis approaches to obtain state estimations. We employ Sequential Monte Carlo (SMC) methods (also called particle filters) to carry out data assimilation in this work. Based on the structure of DDDAS, this dissertation presents the data assimilation system and data assimilation results in wildfire spread simulations. We carry out sensitivity analysis for different densities, frequencies, and qualities of sensor data, and quantify the effectiveness of SMC methods based on different measurement metrics. Furthermore, to improve simulation results, the image-morphing technique is introduced into the DDDAS for wildfire spread simulation
Parallel and pseudorandom discrete event system specification vs. networks of spiking neurons: Formalization and preliminary implementation results
International audienceUsual Parallel Discrete Event System Specification (P-DEVS) allows specifying systems from modeling to simulation. However, the framework does not incorporate parallel and stochastic simulations. This work intends to extend P-DEVS to parallel simulations and pseudorandom number generators in the context of a spiking neural network. The discrete event specification presented here makes explicit and centralized the parallel computation of events as well as their routing, making further implementations more easy. It is then expected to dispose of a well defined mathematical and computational framework to deal with networks of spiking neurons
- …