E. de Gentili

Discrete Event Modeling and Simulation of Wireless Sensor Network Performance

The wireless distributed microsensor networks have profited from recent technological advances and it seems essential to precisely understand these systems. Modeling and simulation appear to be an essential aspect of predicting the Wireless Sensor Network (WSN) specific behavior under different conditions. We want to provide a new method of modeling, simulation and visualization of WSN using a discrete-event approach. Described by Zeigler in the 1970s, the Discrete Event System Specification is ideal for describing the asynchronous nature of the events occuring in WSN. We have provided a basic model for the analysis of WSN performance, including routing management, energy consumption and relative CPU activity. Our approach uses a detailed definition of node-oriented components and aims to introduce methods of visualizing the network at a different level of abstraction.

Fuzz-iDEVS: towards a fuzzy toolbox for discrete event systems

In this paper, we present a set of tools for the simulation of fuzzy systems. The described methods allow to take into account and to handle a lot of imperfect parameters for the studied systems. The methods developed are based on fuzzy logic and DEVS formalism. Their goal is to expand fields of application of simulation environments, and to foster interdisciplinary collaborations. At first, we have applied them to study the spread of forest fires. This application was developed in collaboration with the fire-fighters.

Fuzzy simulation for discrete events systems

The aim of our research is to develop a new method of taking into account the imperfect parameters in a discrete events modeling and simulation formalism. This article describes our approach to modeling and compares several methods for fuzzy simulations.

iDEVS: New method to study inaccurate systems

Our recent research in the fields of modeling and simulation of complex systems, led us to study fuzzy systems. A system is fuzzy, because its parameters are inaccurate, or its behavior is uncertain. We propose in this paper to describe a new modeling method based on the association of DEVS formalism and the fuzzy sets theory. The combination of these two approaches we have permit to define a new method of inaccurate modeling. Our goal is to study systems with inaccurate parameters.

Wildfire impact on deterministic deployment of a Wireless Sensor Network by a discrete event simulation

Detecting and providing evolution informations of the wildfire can be a challenge for Wireless Sensor Networks. The network performance is directly related to the placement of the sensors within the field of interest. In this paper, we address the problem of wireless sensor deployment, for the purpose of following wildfire phenomenon. Based on a discrete event simulation using DEVS formalism, we show that the complexity of the fire position estimation is dependant of network deployement. We test four strategies of deployement and we show the limit of deterministic deployment in simple wildfire scenario.

DEVS-Flou: a discrete events and fuzzy sets theory-based modeling environment

The objective of this article is to present a generic approach of multi-modeling and of simulation of complex systems. In order to take into account fuzzy or badly known parameters, we propose to define an approach allowing the addition of a technique based on the fuzzy sets theory, in an environment of multi-modeling JDEVS based on unifying formalism DEVS

A fuzzy approach of modeling evolutionary interfaces systems

The objective of this article is to present a theoretical approach of evolutionary interfaces object-oriented modeling. It is proposed to apply it to a wildland fire spread model that is multidisciplinary by essence. Our aim is to propose a decision support system to effectively and rapidly take into account complexity and uncertainties related to the factors influencing the fire spread.

Discrete events system simulation-based deFuzzification method

This article presents our approach to discrete event simulation for system with inaccurate parameters. For such systems, simulation runs according to events whose dates are known; but in fuzzy modeling, it may be that the date of the events are inaccurate. To solve this problem, we suggest using a method that converts a inaccurate value into accurate value. This method is incorporated into a modelling and simulation formalism.

Fuzzy modeling for discrete events systems

In this paper, we present our work on fuzzy modeling, and in particular an approach based on the integration of the uncertain theories in the formalism of multi-modeling and simulation with discrete events. The goal of this approach is to help the expert of a field to specify in a simple way the behavior of a complex system with badly defined, fuzzy, etc. parameters. This approach can be employed in multiple fields, an application to the study of the forest fires propagation is presented in order to validate the models.

DEVS-WSN : A discrete event approach for Wireless Sensor Network simulation

Zeigler in the 70 s introduced Discrete Event system Specification (DEVS) formalism. This formalism is able to describe the asynchronous nature of the events occuring in Wireless Sensor Network (WSN). In this paper we introduce a DEVS application oriented components for WSN : DEVS- WSN. Based on pyDEVS, it wants to provide a simulation tool based on a discrete event approach. Our model uses a detained definition of all node components and is independent of operating system. DEVS-WSN provides a framework to build quickly and easily a complex Wireless Sensor Network and to analyze several parameters at various levels of abstraction : hardware components, node, network.