Norbert Giambiasi

Application of the Cell-DEVS Paradigm for Cell Spaces Modelling and Simulation

We present the results obtained when using the Cell-DEVS paradigm for cell spaces modelling and simulation. This formalism allows one to model and simulate cell spaces, including delay functions, to specify their timing behavior. Cell spaces can be defined in an automated fashion, simplifying the construction of new models, and easing the verification of the structural models. The approach was implemented in a development tool, showing that development times can im prove by several orders of magnitude. The main results of development experiences are pre sented, showing the usefulness of the approach.

Timed cell-DEVS: modeling and simulation of cell spaces

DEVS and Cellular Automata formalisms are applied to define a modeling paradigm for cellular models. Different delay functions to specify the timing behavior of each cell, allowing the modeler to represent the timing complex behavior in a simple fashion. Implementation models for the formalism are presented according with the modeler and developer points of view. As a result, efficient and cost-effective development of cellular models simulators could be achieved.

N-dimensional Cell-DEVS Models

This article presents an extension to the timed binary Cell-DEVS paradigm. The goal is to allow the modeling of n-dimensional generic cell spaces, including transport or inertial delays for each cell. The automatic definition of cell spaces is achieved, simplifying the construction of new models. The model definition is independent of the simulation mechanism, easing the verification of the structural models. It was shown that the Cell-DEVS models can be integrated in a DEVS hierarchy, improving the definition and description of complex systems. This approach allows improvements in the execution times and precision for the cell spaces simulations due to the use of a continuous time base.

G-DEVS/HLA Environment for Distributed Simulations of Workflows

We present a Workflow environment allowing distributed simulation based on DEVS/G-DEVS formalisms. A description language for Workflow processes and an automatic transformation of a Workflow into a G-DEVS model have been defined. We then introduce a new distributed Workflow Reference Model with HLA-compliant Workflow components. We detail the HLA objects shared between Workflow federates and present the publishing/subscribing status of each of these federates. Finally, we illustrate the use of this distributed environment with an example of a Microelectronic production Workflow.

Customer–supplier relationship management in an intelligent supply chain network

Outsourcing is leading to more and more complex industrial organisations. This can be attributed to the fact that several decision centres interact. As a consequence, changes in customer–supplier relationships can be noticed. In recent years, these relations have strongly evolved to lead to better internal management of each partner and a better general performance to satisfy customers. These evolutions created a new approach to the relationship between companies, called ‘industrial partnership’, in the form of a network. Networks induce a need at customer–supplier relation control level. The contribution and participation of each of the partners are thus fundamental to make supply chain management (SCM) a successful project. The control system of each actor partner must thus be adaptable enough to satisfy the production requirements. Our contribution to the improvement of customer–supplier relationship is a decentralised self-organised control model based on the concept of holon. In this model, the decision system manages a group of actors’ operations who are in a partnership. In this paper in particular a process for the evaluation of the suppliers network is discussed.

A Generalized Discrete Event System (G-DEVS) Flattened Simulation Structure: Application to High-Level Architecture (HLA) Compliant Simulation of Workflow

The objective of the paper is to specify a new flattened Generalized Discrete Event System simulation engine structure and the Workflow modeling and simulation environment embedding it. We express first the new flattened simulation structure and give the corresponding transformation functions. We analyze performance tests conducted on this new simulation structure to measure its efficiency. Then, having selected the essential concepts in the elaboration of the Workflow, we present a language of description to define the Workflow processes. Finally, we define a distributed Workflow Reference Model that interfaces components of the Workflow with respect to the High-Level Architecture standard. Today enterprises can take advantage of this platform in the context of networking where interoperability, flexibility, and efficiency are challenging concepts.

Generalized discrete event abstraction of continuous systems: GDEVS formalism

In this paper, we propose to model basic continuous component of dynamic systems in a way that facilitate the transposition to a G-DEVS model, which is a paradigm that offers the ability to develop a uniform approach to model hybrid systems (abstraction closer to real systems), i.e. composed of both continuous and discrete components. In that, our approach is clearly a discrete event approach where the choice of the time interval between two steps of calculation is based on the behavior changes of the process and no longer constant and/or a priori given, the underlying objective being to strictly satisfy to a given accuracy with a low computational cost. More precisely, we present a generalized discrete event model of an integrator using polynomial descriptions of input–output trajectories. We shall show its great capability of easily handling the delicate problem of input discontinuities, and a detailed comparison with classical discrete time simulation methods, will demonstrate its relevant properties. Several examples, including a complete hybrid system, will illustrate our results. � 2005 Elsevier B.V. All rights reserved.

Integration of a flat holonic form in an HLA environment

Managers need to create and sustain internal systems and controls to ensure that their customer focused strategies are being implemented. Companies are currently in a spiral of permanent optimization. Accordingly, many companies turn to their core activity. In this framework, one notices the development of the concept of “industrial partnership”. In this context and to control the customer–supplier relationships (CSR), we proposed a self-organized control model in which all partner entities (customers/suppliers) negotiate to guarantee good quality connections between customers and suppliers. This means meeting customer expectations as closely as possible and respecting supplier capacities. In this proposal, self-organized control is characterized more precisely by an organizational architecture of the flat holonic form type. This flat holonic form is based on the concept of autonomous control entity (ACE). The holonic architecture, the behaviour of an ACE, the interaction mechanisms between ACEs and the self-evaluation supplier process are presented, and then the modelling of ACEs using discrete event system specification (DEVS) is described. An implementation of the simulation of such a system was done via a distributed simulation environment high level architecture (HLA). A case study illustrating the proposed approach is presented.

Cell-DEVS/GDEVS for Complex Continuous Systems

The Cell-Discrete Event System Specification (Cell-DEVS) formalism allows defining asynchronous cell spaces with explicit timing delays (based on the specifications of the DEVS formalism). The authors used Cell-DEVS to solve different applications and go one step further in the definition of complex continuous systems by combining Cell-DEVS and Generalized DEVS (GDEVS). They focus on a model describing the electrical behavior of the heart tissue, as previous research in this field has thoroughly studied this problem using differential equations and cellular automata. The authors show that they can provide adequate levels of precision at a fraction of the computing cost of differential equations. Their thesis is that the use of the GDEVS formalism is perfectly suited to attack problems such as this one, improving complex systems analysis. The authors show that their approach permits making models easily extensible to provide different actions in different cells while not affecting performance.

Min–Max-DEVS modeling and simulation

Abstract The representation of timing, a key element in modeling hardware behavior, is realized in hardware description languages including ADLIB-SABLE, Verilog, and VHDL, through delay constructs. The use of delays in the literature may be organized into four classes. Under the first category, the mean values are utilized as precise delay elements in the simulators. VHDL adopts this view to characterize transport delays, where a single value is utilized, rise and fall delays, and inertial delays. In describing the lifetime of a state, also termed time advance function, DEVS proposes to use precise delay elements. Under the second category, termed min–max delay, a delay is represented through an interval, implying that the value of the delay is not known precisely and that any of the values in the interval represents a possible value for the actual delay. In the third category, a delay is expressed in the form of a stochastic distribution. The use of fuzzy models of delays constitutes the fourth category. In the real world, however, precise values for delays are very difficult, if not impossible, to obtain with certainty. The reasons include variations in the manufacturing process, temperature, voltage, and other environmental parameters. Consequently, simulations that employ precise delay values are susceptible to inaccurate results. This paper proposes an extension to the classical DEVS by introducing min–max delays for use in both internal and external transition functions. In the augmented formalism, termed Min–Max-DEVS, the state of a hardware model may, in some time interval, become unknown and is represented by the symbol, ϕ . The occurrence of ϕ implies greater accuracy of the results, not lack of information. Min–Max-DEVS offers a unique advantage, namely, the execution of a single simulation pass utilizing min–max delays is equivalent to multiple simulation passes, each corresponding to a set of precise delay values selected from the interval. This, in turn, poses a key challenge – efficient execution of the Min–Max-DEVS simulator.