194 research outputs found

    Multi-level agent-based modeling - A literature survey

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    During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

    A Contextualized Web-Based Learning Environments for DEVS Models

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    With the advance in applying technology in education, the traditional lecture-driven teaching style is gradually replaced by a more active teaching style where the students play a more active rule in the learning process. In this paper we introduce a new initiative to provide a suite of online tools for learning DEVS model. The uniqueness of this tutorial project is the integration of information technology and multimedia into education through the development of an interactive tutorial and the characteristic of contextualized learning. The tutorial teaches students about the basic aspects of discrete event system and simulation. The interactive tutorial fully utilizes the power of the information and multimedia technology, web application and the programming language Java, to enhance students’ learning to achieve rich interactivity. The tutorial greatly supports human-computer collaboration to enhance learning and to satisfy user goals by effectively allowing the user to interact

    Dynamic Data Driven Application System for Wildfire Spread Simulation

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    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

    A novel parallelization technique for DEVS simulation of continuous and hybrid systems.

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    In this paper, we introduce a novel parallelization technique for Discrete Event System Specification (DEVS) simulation of continuous and hybrid systems. Here, like in most parallel discrete event simulation methodologies, the models are first split into several sub-models which are than concurrently simulated on different processors. In order to avoid the cost of the global synchronization of all processes, the simulation time of each sub-model is locally synchronized in a real-time fashion with a scaled version of physical time, which implicitly synchronizes all sub-models. The new methodology, coined Scaled Real-Time Synchronization (SRTS), does not ensure a perfect synchronization in its implementation. However, under certain conditions, the synchronization error introduced only provokes bounded numerical errors in the simulation results. SRTS uses the same physical time-scaling parameter throughout the entire simulation. We also developed an adaptive version of the methodology (Adaptive-SRTS) where this parameter automatically evolves during the simulation according to the workload. We implemented the SRTS and Adaptive-SRTS techniques in PowerDEVS , a DEVS simulation tool, under a real-time operating system called the Real-Time Application Interface (RTAI) . We tested their performance by simulating three large-scale models, obtaining in all cases a considerable speedup.Fil: Bergero, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Cellier, François. Swiss Federal Institute Of Technology Zurich. Departament Informatik. Modeling And Simulation Research Group; Suiz

    Toward composing variable structure models and their interfaces: a case of intensional coupling definitions

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    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. Dafür nutzen wir intensionale Definitionen, wie sie aus der Logik bekannt sind, und führen ein neuartiges Konzept von intensionalen Kopplungen ein, welches kompakte gleichzeitig ausdrucksstarke Spezifikationen von komplexen Kommunikations- und Interaktionsmuster in statischen und variablen Strukturmodellen erlaubt

    A Continuous-Time Microsimulation and First Steps Towards a Multi-Level Approach in Demography

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    Microsimulation is a methodology that closely mimics life-course dynamics. In this thesis, we describe the development of the demographic microsimulation with a continuous time scale that we have realized in the context of the project MicMac - Bridging the micro-macro gap in population forecasting. Furthermore, we detail extensions that we have added to the initial version of the MicMac microsimulation.Mikrosimulation ist eine Prognosetechnik, die sich hervorragend eignet, um Bevölkerungsdynamik realitätsnah abzubilden. In dieser Dissertation beschreiben wir die Entwicklung einer demografischen Mikrosimulation, die wir im Rahmen des Projektes MicMac - Bridging the micro-macro gap in population forecasting erstellt haben. Zudem erläutern wir Erweiterungen, die wir an der ursprünglichen MicMac- Mikrosimulation vorgenommen haben

    Remote software upload techniques in future vehicles and their performance analysis

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    Updating software in vehicle Electronic Control Units (ECUs) will become a mandatory requirement for a variety of reasons, for examples, to update/fix functionality of an existing system, add new functionality, remove software bugs and to cope up with ITS infrastructure. Software modules of advanced vehicles can be updated using Remote Software Upload (RSU) technique. The RSU employs infrastructure-based wireless communication technique where the software supplier sends the software to the targeted vehicle via a roadside Base Station (BS). However, security is critically important in RSU to avoid any disasters due to malfunctions of the vehicle or to protect the proprietary algorithms from hackers, competitors or people with malicious intent. In this thesis, a mechanism of secure software upload in advanced vehicles is presented which employs mutual authentication of the software provider and the vehicle using a pre-shared authentication key before sending the software. The software packets are sent encrypted with a secret key along with the Message Digest (MD). In order to increase the security level, it is proposed the vehicle to receive more than one copy of the software along with the MD in each copy. The vehicle will install the new software only when it receives more than one identical copies of the software. In order to validate the proposition, analytical expressions of average number of packet transmissions for successful software update is determined. Different cases are investigated depending on the vehicle\u27s buffer size and verification methods. The analytical and simulation results show that it is sufficient to send two copies of the software to the vehicle to thwart any security attack while uploading the software. The above mentioned unicast method for RSU is suitable when software needs to be uploaded to a single vehicle. Since multicasting is the most efficient method of group communication, updating software in an ECU of a large number of vehicles could benefit from it. However, like the unicast RSU, the security requirements of multicast communication, i.e., authenticity, confidentiality and integrity of the software transmitted and access control of the group members is challenging. In this thesis, an infrastructure-based mobile multicasting for RSU in vehicle ECUs is proposed where an ECU receives the software from a remote software distribution center using the road side BSs as gateways. The Vehicular Software Distribution Network (VSDN) is divided into small regions administered by a Regional Group Manager (RGM). Two multicast Group Key Management (GKM) techniques are proposed based on the degree of trust on the BSs named Fully-trusted (FT) and Semi-trusted (ST) systems. Analytical models are developed to find the multicast session establishment latency and handover latency for these two protocols. The average latency to perform mutual authentication of the software vendor and a vehicle, and to send the multicast session key by the software provider during multicast session initialization, and the handoff latency during multicast session is calculated. Analytical and simulation results show that the link establishment latency per vehicle of our proposed schemes is in the range of few seconds and the ST system requires few ms higher time than the FT system. The handoff latency is also in the range of few seconds and in some cases ST system requires less handoff time than the FT system. Thus, it is possible to build an efficient GKM protocol without putting too much trust on the BSs

    The DEVStone Metric: Performance Analysis of DEVS Simulation Engines

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    The DEVStone benchmark allows us to evaluate the performance of discrete-event simulators based on the DEVS formalism. It provides model sets with different characteristics, enabling the analysis of specific issues of simulation engines. However, this heterogeneity hinders the comparison of the results among studies, as the results obtained on each research work depend on the chosen subset of DEVStone models. We define the DEVStone metric based on the DEVStone synthetic benchmark and provide a mechanism for specifying objective ratings for DEVS-based simulators. This metric corresponds to the average number of times that a simulator can execute a selection of 12 DEVStone models in one minute. The variety of the chosen models ensures we measure different particularities provided by DEVStone. The proposed metric allows us to compare various simulators and to assess the impact of new features on their performance. We use the DEVStone metric to compare some popular DEVS-based simulators
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