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International audience; The automotive industry is shifting to mass production of electrified vehicles. Simulation is a key step for developing these new vehicles. System simulation tools as Simcenter Amesim includes ready-to-use multi-physics libraries in that perspective. A new library is being created based on the Energetic Macroscopic Representation formalism to speed-up the battery electric vehicles (BEV) development process. The paper presents the BEV multi-level simulation where the simulations were done using 3 different levels for the battery models. By using “plug & play” method different BEV model configurations can be built in a fast, precise and systematic way.

This paper proposes two approaches for the integration of cyber-physical systems in a production line in order to obtain predictions concerning the actual production, core operation in the context of Industry 4.0. The first approach relies on the Multi-Level paradigm where multiple descriptions of the same CPS are modeled with different levels of details. Then, the models are switched at runtime. The second approach relies on abstraction techniques of CPS maintaining a certain levels of details. The two approaches are validated and compared with a real use case scenario to identify the most effective simulation strategy.

Hybrid lightweight parts aim at improving the economical and ecological performance of automobiles by reducing weight and, consequently, CO 2 emissions. The environmental advantageousness requires careful attention during the car's design phase to prevent problem shifting from use phase into production. Due to the degree of novelty of hybrid components, reliable data about energy and resource demands in production is not yet available. This work presents a multi-level simulation framework for coupling models from different disciplines in order to derive LCA-relevant data. Exemplarily, a discrete-event process chain simulation is connected with a physical process model for a forming process.

Discrete event simulation (DES) models imitates the behavior of a production system. Models can be developed to reflect different levels of the production system, e.g supply chain level or manufacturing line level. Product Lifecycle Management (PLM) systems have been developed in order to manage product and manufacturing related data. DES models is one kind of product lifecycle’s data which can be managed by a PLM system. This paper presents a method and its implementation for management of interacting multi-level models utilizing a PLM system.

none 4 no This paper presents a methodology for simulating the Internet of Things (IoT) using multi-level simulation models. With respect to conventional simulators, this approach allows us to tune the level of detail of different parts of the model without compromising the scalability of the simulation. As a use case, we have developed a two-level simulator to study the deployment of smart services over rural territories. The higher level is base on a coarse grained, agent-based adaptive parallel and distributed simulator. When needed, this simulator spawns OMNeT++ model instances to evaluate in more detail the issues concerned with wireless communications in restricted areas of the simulated world. The performance evaluation confirms the viability of multi-level simulations for IoT environments. mixed Stefano, Ferretti; Gabriele, D’Angelo; Vittorio, Ghini; Moreno, Marzolla Stefano, Ferretti; Gabriele, D’Angelo; Vittorio, Ghini; Moreno, Marzolla

In this paper, a methodology is presented and employed for simulating the Internet of Things (IoT). The requirement for scalability, due to the possibly huge amount of involved sensors and devices, and the heterogeneous scenarios that might occur, impose resorting to sophisticated modeling and simulation techniques. In particular, multi-level simulation is regarded as a main framework that allows simulating large-scale IoT environments while keeping high levels of detail, when it is needed. We consider a use case based on the deployment of smart services in decentralized territories. A two level simulator is employed, which is based on a coarse agent-based, adaptive parallel and distributed simulation approach to model the general life of simulated entities. However, when needed a finer grained simulator (based on OMNeT++) is triggered on a restricted portion of the simulated area, which allows considering all issues concerned with wireless communications. Based on this use case, it is confirmed that the ad-hoc wireless networking technologies do represent a principle tool to deploy smart services over decentralized countrysides. Moreover, the performance evaluation confirms the viability of utilizing multi-level simulation for simulating large scale IoT environments., Simulation Modelling Practice and Theory, Elsevier, vol. 73 (April 2017)

In this Habilitation Thesis, I present my research activity in the field of multiagent simulation within the SMAC team (LIFL, Université Lille 1), since the beginning of my career of teacher and researcher in 2002. My work focuses on the design and implementation of methods and tools aimed at facilitating the modeling of large-scale complex systems. Therefore, I developped with my colleagues an " interaction-oriented " approach, characterized by the unification of several concepts used in the field of MAS. It is supported by a large methodological and algorithmic elaboration (the IODA method), in which each entity of the model is represented by an agent and each behavior by a rule called an interaction. This method relies upon the separation between declarative and procedural features, which facilitates the acquisition of thematic expertise. In addition, several software tools have been built throughout this research (e.g. the JEDI platform and the IODA exension for the NetLogo platform). This method has also been applied to various fields (cell biology, serious games, marketing, cartography). To conclude, I present my research project for the coming years, which proposes to combine issues raised by recent work: on the one hand, the multi-level simulation (aimed at defining an operational framework for automatizing the change of observation scale or point of view upon the subsystems of a complex phenomenon) ; and on the other hand, the automatic information retrieval from real data, in order to increase the behavioral realism of populations of agents. In addition, a collaboration with the IGN on using those techniques for cartographic generalization opens perspectives towards the transposition of those simulation methods to the field of problem solving.; Dans ce mémoire de synthèse d'habilitation à diriger des recherches, je présente les travaux en simulation multi-agents que j'ai menés au sein de l'équipe SMAC (LIFL, Université Lille 1) depuis le début de ma carrière d'enseignant-chercheur en 2002. Ceux-ci portent sur la conception et la mise en application de méthodes et d'outils de simulation destinés à faciliter la modélisation de systèmes complexes à large échelle. Dans ce but, j'ai développé avec mes collègues une approche " orientée interactions " caractérisée par une unification des concepts utilisés dans le domaine des SMA. Elle a donné lieu à une importante élaboration méthodologique et algorithmique (la méthode IODA) dans laquelle toute entité du modèle est représentée par un agent, et tout comportement par une règle appelée interaction. Cette méthode s'appuie sur une séparation entre déclaratif et procédural qui facilite l'acquisition de l'expertise auprès des thématiciens. Par ailleurs de nombreux outils logiciels sont nés de ces recherches (dont la plateforme JEDI et une extension IODA pour la plateforme NetLogo), ainsi que diverses applications dans des domaines variés (biologie cellulaire, serious games, marketing, cartographie). Pour conclure, je présente mon projet de recherche pour les prochaines années qui se propose d'articuler des problématiques issues de travaux récents, d'une part sur la simulation multi-niveaux (qui vise à définir un cadre opérationnel permettant le changement d'échelle d'observation ou de point de vue sur les sous-systèmes d'un système complexe), et d'autre part sur la recherche automatique d'informations dans des données réelles pour augmenter le réalisme comportemental des populations d'agents. Par ailleurs une collaboration avec l'IGN sur l'utilisation de ces techniques pour la généralisation cartographique permet également d'envisager la transposition de ces méthodes de simulation à la résolution de problèmes.

O uso de ferramentas de simulação para validar projetos de sistemas digitais é uma prática comum, devido às vantagens que estas trazem ao desenvolvimento destes sistemas, tais como: custo, segurança, velocidade e acuracidade. Porém, a simulação seqüencial de alguns sistemas pode levar várias horas ou até mesmo dias, fazendo desta maneira surgir a necessidade de técnicas para acelerar tal procedimento. Uma solução encontrada para aumentar a velocidade de simulação pode estar no uso de técnicas de sistemas distribuídos, já que muitas vezes o próprio sistema real tem embutido em si um certo paralelismo, o que facilita os procedimentos de distribuição. Ao se tratar da simulação de sistemas distribuídos logo surge um dos grandes problemas inerentes a estes, o controle global do tempo, fazendo com que a sincronização entre os processos seja bastante complicada. Neste trabalho são estudados dois paradigmas de sincronização, o otimista e o conservativo. Tendo como base estes paradigmas, formularam-se duas técnicas para solucionar o problema de sincronização, no contexto da simulação multinível de sistemas digitais. Nos estudos realizados, utilizou-se como plataforma a API WinSock para Windows a fim de proporcionar a comunicação entre processos. Ao final é feita uma análise comparativa das versões desenvolvidas, as quais fizeram uso das técnicas de sincronização acima mencionadas. The use of simulation tools to validate the design of digital systems is a common practice, due to the benefits these tools bring to the development of those systems: cost, security, velocity, and accuracy. However, the sequential simulation of some systems may take hours or even days, thus creating the need of techniques for speeding up this procedure. A solution for increasing the simulation speed may be the use of techniques based on distributed systems, since very often the real system has an implicit parallelism, which makes easier the aplication of distribution procedures. When dealing with the simulation of distributed systems, one of the big problems that arise is the global control of simulation time, which makes the synchronization among processes very complex. In this work two synchronization paradigms are studied: the optimist and the conservative ones. Based on these paradigms, two techniques for solving the problem of synchronization in the context of multi-level simulation of digital systems have been developed. In these studies, the API WinSock for Windows has been used for supporting the communication between processes. A comparative analysis of the versions we developed, that use the above mentioned synchronization techniques, is also presented.

In this Habilitation Thesis, I present my research activity in the field of multiagent simulation within the SMAC team (LIFL, Université Lille 1), since the beginning of my career of teacher and researcher in 2002. My work focuses on the design and implementation of methods and tools aimed at facilitating the modeling of large-scale complex systems. Therefore, I developped with my colleagues an " interaction-oriented " approach, characterized by the unification of several concepts used in the field of MAS. It is supported by a large methodological and algorithmic elaboration (the IODA method), in which each entity of the model is represented by an agent and each behavior by a rule called an interaction. This method relies upon the separation between declarative and procedural features, which facilitates the acquisition of thematic expertise. In addition, several software tools have been built throughout this research (e.g. the JEDI platform and the IODA exension for the NetLogo platform). This method has also been applied to various fields (cell biology, serious games, marketing, cartography). To conclude, I present my research project for the coming years, which proposes to combine issues raised by recent work: on the one hand, the multi-level simulation (aimed at defining an operational framework for automatizing the change of observation scale or point of view upon the subsystems of a complex phenomenon) ; and on the other hand, the automatic information retrieval from real data, in order to increase the behavioral realism of populations of agents. In addition, a collaboration with the IGN on using those techniques for cartographic generalization opens perspectives towards the transposition of those simulation methods to the field of problem solving.; Dans ce mémoire de synthèse d'habilitation à diriger des recherches, je présente les travaux en simulation multi-agents que j'ai menés au sein de l'équipe SMAC (LIFL, Université Lille 1) depuis le début de ma carrière d'enseignant-chercheur en 2002. Ceux-ci portent sur la conception et la mise en application de méthodes et d'outils de simulation destinés à faciliter la modélisation de systèmes complexes à large échelle. Dans ce but, j'ai développé avec mes collègues une approche " orientée interactions " caractérisée par une unification des concepts utilisés dans le domaine des SMA. Elle a donné lieu à une importante élaboration méthodologique et algorithmique (la méthode IODA) dans laquelle toute entité du modèle est représentée par un agent, et tout comportement par une règle appelée interaction. Cette méthode s'appuie sur une séparation entre déclaratif et procédural qui facilite l'acquisition de l'expertise auprès des thématiciens. Par ailleurs de nombreux outils logiciels sont nés de ces recherches (dont la plateforme JEDI et une extension IODA pour la plateforme NetLogo), ainsi que diverses applications dans des domaines variés (biologie cellulaire, serious games, marketing, cartographie). Pour conclure, je présente mon projet de recherche pour les prochaines années qui se propose d'articuler des problématiques issues de travaux récents, d'une part sur la simulation multi-niveaux (qui vise à définir un cadre opérationnel permettant le changement d'échelle d'observation ou de point de vue sur les sous-systèmes d'un système complexe), et d'autre part sur la recherche automatique d'informations dans des données réelles pour augmenter le réalisme comportemental des populations d'agents. Par ailleurs une collaboration avec l'IGN sur l'utilisation de ces techniques pour la généralisation cartographique permet également d'envisager la transposition de ces méthodes de simulation à la résolution de problèmes.