Tesis sobre el tema "Dynamiques de graphes"
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Crespelle, Christophe. "Représentations dynamiques de graphes". Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2007. http://tel.archives-ouvertes.fr/tel-00402838.
Texto completoLes connexions entre les trois types de représentation précités sont exploitées pour la conception d'algorithmes de reconnaissance entièrement dynamiques pour les cographes orientés, les graphes de permutation et les graphes d'intervalles. Pour les cographes orientés, l'algorithme présenté est de complexité optimale, il traite les modifications de sommet en temps O(d), où d est le degré du sommet en question, et les modifications d'arête en temps constant. Les algorithmes pour les graphes de permutation et les graphes d'intervalles ont la même complexité : les modifications d'arête et de sommet sont traitées en temps O(n), où n est le nombre de sommets du graphe. Une des contributions du mémoire est de mettre en lumière des similarités très fortes entre les opérations d'ajout d'un sommet dans un graphe de permutation et dans un graphe d'intervalles.
L'approche mise en oeuvre dans ce mémoire est assez générale pour laisser entrevoir les mêmes possibilités algorithmiques pour d'autres classes de graphes définies géométriquement.
Duvignau, Romaric. "Maintenance et simulation de graphes aléatoires dynamiques". Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0177/document.
Texto completoWe study the problem of maintaining a given distribution of randomgraphs under an arbitrary sequence of vertex insertions and deletions. Keeping inmind our objective to model the evolution of dynamic logical networks, we work ina local model where we do not have direct access to the list of all vertices. Instead,we assume access to a global primitive that returns a random vertex, chosen uniformlyfrom the whole vertex set. The maintenance problem has been explored onseveral simple random graph models (Erdos–Rényi random graphs, pairing modelbased random graphs, uniform k-out graphs). For each model, one or several updatealgorithms for the maintenance task have been described and analyzed ; the mostelaborate of them are asymptically optimal. The maintenance task rise several simulationissues linked to our distributed context. In particular, we have focused onmaintenability of random graph distributions and simulability of families of probabilitydistributions over integers in our local random model. Special attention hasbeen paid to efficient simulation of particular distributions we were interested in(certain binomial distributions). The latter has been obtained through the use ofproperties of a new generation tree for permutations, which has been introducedalong the way
Vernet, Mathilde. "Modèles et algorithmes pour les graphes dynamiques". Thesis, Normandie, 2020. http://www.theses.fr/2020NORMLH12.
Texto completoGraph problems have been widely studied in the case of static graphs. However, these graphs do not allow a time dimension to be considered, even though time is an important variable for the situations to model. Dynamic graphs make it possible to model evolution over time. This is a reason to wonder about graph problems in a dynamic context. First, it is necessary to define the most appropriate dynamic graphs model and the precise problem on those graphs. When the problem cannot be efficiently solved directly using known static graph methods, an algorithm specific to dynamic graphs must be designed and analyzed theoretically and practically.With that approach, this thesis' objective is to study graph problems' extensions to dynamic graphs. This works deals with several graph problems in a dynamic context by focusing on algorithmic aspects and without considering application domains
Wade, Ahmed mouhamadou. "Complexité de l'exploration par agent mobile des graphes dynamiques". Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0484/document.
Texto completoIn this thesis, we study the complexity of the problem of exploration by a mobileagent in dynamic graphs. A mobile entity (called agent) moving in a dynamic graph hasto traverse/visit each of its vertices at least once. This fundamental problem in computatingby mobile agents has been well-studied in static graphs since the original paper ofClaude Shannon. However, for highly dynamic graphs, only the case of periodic dynamicgraphs has been studied. We study this problem in two families of dynamic graphs,periodically-varying graphs (PV-graphs) and T-interval-connected dynamic graphs. Theobtained results improve the existing results and give optimal bounds on the studiedproblems
Durbec, Amélia. "Dynamiques causales de graphes réversibles et quantiques". Electronic Thesis or Diss., Aix-Marseille, 2022. http://www.theses.fr/2022AIXM0459.
Texto completoCausal graph dynamics are a twofold extension of cellular automata: the underlying grid is extended to an arbitrary graph of bounded degree and the graph itself can evolve in time.In the reversible regime, we prove that causal graph dynamics can be reversible while creating/destroying vertices, through three different models that we prove to be equivalent.Based on these results, we exhibit causal dynamics that are both reversible and increasing in space, which brings new insights into the compatibility between the time arrow and reversibility. We define a notion of graph subshifts, which can be used to study causal dynamics of graphs by unifying temporal and spatial dimensions, in the same way that 1D cellular automata can be studied with 2D subshifts of finite type.In the quantum regime, our first contribution is to provide a rigorous definition of state space. A notable question was whether vertex names are necessary; we prove they are indeed necessary in order to prevent faster-than-light signaling. We also point out that renaming on graphs is the natively discrete analog of coordinate changes
Maag, Maria Coralia Laura. "Apprentissage automatique de fonctions d'anonymisation pour les graphes et les graphes dynamiques". Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066050/document.
Texto completoData privacy is a major problem that has to be considered before releasing datasets to the public or even to a partner company that would compute statistics or make a deep analysis of these data. Privacy is insured by performing data anonymization as required by legislation. In this context, many different anonymization techniques have been proposed in the literature. These techniques are difficult to use in a general context where attacks can be of different types, and where measures are not known to the anonymizer. Generic methods able to adapt to different situations become desirable. We are addressing the problem of privacy related to graph data which needs, for different reasons, to be publicly made available. This corresponds to the anonymized graph data publishing problem. We are placing from the perspective of an anonymizer not having access to the methods used to analyze the data. A generic methodology is proposed based on machine learning to obtain directly an anonymization function from a set of training data so as to optimize a tradeoff between privacy risk and utility loss. The method thus allows one to get a good anonymization procedure for any kind of attacks, and any characteristic in a given set. The methodology is instantiated for simple graphs and complex timestamped graphs. A tool has been developed implementing the method and has been experimented with success on real anonymized datasets coming from Twitter, Enron or Amazon. Results are compared with baseline and it is showed that the proposed method is generic and can automatically adapt itself to different anonymization contexts
Maag, Maria Coralia Laura. "Apprentissage automatique de fonctions d'anonymisation pour les graphes et les graphes dynamiques". Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066050.
Texto completoData privacy is a major problem that has to be considered before releasing datasets to the public or even to a partner company that would compute statistics or make a deep analysis of these data. Privacy is insured by performing data anonymization as required by legislation. In this context, many different anonymization techniques have been proposed in the literature. These techniques are difficult to use in a general context where attacks can be of different types, and where measures are not known to the anonymizer. Generic methods able to adapt to different situations become desirable. We are addressing the problem of privacy related to graph data which needs, for different reasons, to be publicly made available. This corresponds to the anonymized graph data publishing problem. We are placing from the perspective of an anonymizer not having access to the methods used to analyze the data. A generic methodology is proposed based on machine learning to obtain directly an anonymization function from a set of training data so as to optimize a tradeoff between privacy risk and utility loss. The method thus allows one to get a good anonymization procedure for any kind of attacks, and any characteristic in a given set. The methodology is instantiated for simple graphs and complex timestamped graphs. A tool has been developed implementing the method and has been experimented with success on real anonymized datasets coming from Twitter, Enron or Amazon. Results are compared with baseline and it is showed that the proposed method is generic and can automatically adapt itself to different anonymization contexts
Martiel, Simon. "Approches informatique et mathématique des dynamiques causales de graphes". Thesis, Nice, 2015. http://www.theses.fr/2015NICE4043/document.
Texto completoCellular Automata constitute one of the most established model of discrete physical transformations that accounts for euclidean space. They implement three fundamental symmetries of physics: causality, homogeneity and finite density of information. Even though their origins lies in physics, they are widely used to model spatially distributed computation (self-replicating machines, synchronization problems,...), as well as a great variety of multi-agents phenomena (traffic jams, demographics,...). While being one of the most studied model of distributed computation, their rigidity forbids any trivial extension toward time-varying topology, which is a fundamental requirement when it comes to modelling phenomena in biology, sociology or physics: for instance when looking for a discrete formulation of general relativity. Causal graph dynamics generalize cellular automata to arbitrary, bounded degree, time-varying graphs. In this work, we generalize the fundamental structure results of cellular automata for this type of transformations. We endow our graphs with a compact metric space structure, and follow two approaches. An axiomatic approach based on the notions of continuity and shift-invariance, and a constructive approach, where a local rule is applied synchronously on every vertex of the graph. Compactness allows us to show the equivalence of these two definitions, extending the famous result of Curtis-Hedlund-Lyndon’s theorem. Another physics-inspired symmetry is then added to the model, namely reversibility
Boria, Nicolas. "Optimisation combinatoire et environnements dynamiques". Paris 9, 2011. http://basepub.dauphine.fr/xmlui/handle/123456789/7232.
Texto completoNeggaz, Mohammed Yessin. "Automatic classification of dynamic graphs". Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0169/document.
Texto completoDynamic networks consist of entities making contact over time with one another. A major challenge in dynamic networks is to predict mobility patterns and decide whether the evolution of the topology satisfies requirements for the successof a given algorithm. The types of dynamics resulting from these networks are varied in scale and nature. For instance, some of these networks remain connected at all times; others are always disconnected but still offer some kind of connectivity over time and space (temporal connectivity); others are recurrently connected,periodic, etc. All of these contexts can be represented as dynamic graph classes corresponding to necessary or sufficient conditions for given distributed problems or algorithms. Given a dynamic graph, a natural question to ask is to which of the classes this graph belongs. In this work we provide a contribution to the automation of dynamic graphs classification. We provide strategies for testing membership of a dynamic graph to a given class and a generic framework to test properties in dynamic graphs. We also attempt to understand what can still be done in a context where no property on the graph is guaranteed through the distributed problem of maintaining a spanning forest in highly dynamic graphs
Gautero, François. "CW-complexes dynamiques". Nice, 1998. http://www.theses.fr/1998NICE5137.
Texto completoEichler, Cédric. "Modélisation formelle de systèmes dynamiques autonomes : graphe, réécriture et grammaire". Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30057/document.
Texto completoModern, large-scale systems are deployed in changing environments. They must dynamically adapt to context changes. In this scope, autonomic computing aims at reducing slow and costly human interventions, by building self-managed systems. Self-adaptability of a system is primarily based on a suitable description of its components, their interactions and the various states it can adopt. Various modeling approaches have been elaborated. They usually focus on some aspects or properties of dynamic systems and do not tackle each of self-management's requirements. This manuscript deals with graph-based representations of dynamic systems and their suitability for the implementation of autonomic computing's four fundamental properties : self-optimization, self-protection, self-healing and self-configuring. This thesis offers four principal theoretical and applied contributions. The first one is a methodology for the construction and generative characterization of transformations correct by construction whose application necessarily preserves a system's correctness. The second one consists in an extension of graph rewriting systems allowing to easily and efficiently represent, update, evaluate and configure a system's characteristics. An experimental study reveals a significant efficiency gain with regard to classical methods. The two lasts contribution are articulated around the design of two autonomic managers driving: (1) complex events processing requests and (2) any Machine-to-Machine system complying to the ETSI M2M2 standard
Albano, Alice. "Dynamique des graphes de terrain : analyse en temps intrinsèque". Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066260/document.
Texto completoWe are surrounded by a multitude of interaction networks from different contexts. These networks can be modeled as graphs, called complex networks. They have a community structure, i.e. groups of nodes closely related to each other and less connected with the rest of the graph. An other phenomenon studied in complex networks in many contexts is diffusion. The spread of a disease is an example of diffusion. These phenomena are dynamic and depend on an important parameter, which is often little studied: the time scale in which they are observed. According to the chosen scale, the graph dynamics can vary significantly. In this thesis, we propose to study dynamic processes using a suitable time scale. We consider a notion of relative time which we call intrinsic time, opposed to "traditional" time, which we call extrinsic time. We first study diffusion phenomena using intrinsic time, and we compare our results with an extrinsic time scale. This allows us to highlight the fact that the same phenomenon observed at two different time scales can have a very different behavior. We then analyze the relevance of the use of intrinsic time scale for detecting dynamic communities. Comparing communities obtained according extrinsic and intrinsic scales shows that the intrinsic time scale allows a more significant detection than extrinsic time scale
Albano, Alice. "Dynamique des graphes de terrain : analyse en temps intrinsèque". Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066260.
Texto completoWe are surrounded by a multitude of interaction networks from different contexts. These networks can be modeled as graphs, called complex networks. They have a community structure, i.e. groups of nodes closely related to each other and less connected with the rest of the graph. An other phenomenon studied in complex networks in many contexts is diffusion. The spread of a disease is an example of diffusion. These phenomena are dynamic and depend on an important parameter, which is often little studied: the time scale in which they are observed. According to the chosen scale, the graph dynamics can vary significantly. In this thesis, we propose to study dynamic processes using a suitable time scale. We consider a notion of relative time which we call intrinsic time, opposed to "traditional" time, which we call extrinsic time. We first study diffusion phenomena using intrinsic time, and we compare our results with an extrinsic time scale. This allows us to highlight the fact that the same phenomenon observed at two different time scales can have a very different behavior. We then analyze the relevance of the use of intrinsic time scale for detecting dynamic communities. Comparing communities obtained according extrinsic and intrinsic scales shows that the intrinsic time scale allows a more significant detection than extrinsic time scale
Ouassir, Abdelmajid. "Contribution au diagnostic de systèmes dynamiques par l'utilisation de graphes orientés signés". Compiègne, 1997. http://www.theses.fr/1997COMP1073.
Texto completoIn this thesis, an important class of qualitative causal models based on the Signed Directed Graph (SDG) was carried out. The SDG model consists of nodes symbolizing process variables, and signed directed arcs that represent the local cause and effet relationships between variables. Previous work on SDG models has not adequately addressed the role of feedback and complex dynamics. Disturbance propagation is restricted to feedforward path in the SDG and heuristics are applied to account for complex dynamic process behavior arising due to interactions in negative feedback loops. The heuristics are imcomplite as they do not account for all instances of dynamic behavior. In diagnostic applications, these limitations result in unnecessary losses of diagnostic resolution and the production of inaccurate diagnosis. The above limitations are crucial and have in the past reduced the potential applications of diagnostic systems based on SDG models. A rigorous analysis was performed and indicated that disturbance propagation assumptions (simple transition) and heuristics are inadequate, leading to the exclusion of inverse and compensatory response arising from interactions in non-control negative feedback loops in the SDG. On of the recurring concepts developed in this thesis has been the systematic use of "multiple transition" assumption. An algorithmic technique for deriving the knowledge base for online diagnostic reasoning program for continous process was developed. A nouvel feature of the technique is that certain behaviors not apparent from SDG models but result from global process interactions are automatically represented in the diagnostic knowledge base
VENET, ARNAUD. "Analyse statique des systemes dynamiques de graphes dans les langages non types". Palaiseau, Ecole polytechnique, 1998. http://www.theses.fr/1998EPXX0073.
Texto completoCuenca, Pauta Erick. "Visualisation de données dynamiques et complexes : des séries temporelles hiérarchiques aux graphes multicouches". Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTS054/document.
Texto completoThe analysis of data that is increasingly complex, large and from different sources (e.g. internet, social medias, etc.) is a dificult task. However, it remains crucial for many fields of application. It implies, in order to extract knowledge, to better understand the nature of the data, its evolution or the many complex relationships it may contain. Information visualization is about visual and interactive representation methods to help a user to extract knowledge. The work presented in this document takes place in this context. At first, we are interested in the visualization of large hierarchical time series. After analyzing the different existing approaches, we present the MultiStream system for visualizing, exploring and comparing the evolution of the series organized into a hierarchical structure. We illustrate its use by two examples: emotions expressed in social media and the evolution of musical genres. In a second time, we tackle the problem of complex data modeled in the form of multilayer graphs (different types of edges can connect the nodes). More specifically, we are interested in the visual querying of large graphs and we present VERTIGo, a system which makes it possible to build queries, to launch them on a specific engine, to visualize/explore the results at different levels of details and to suggest new query extensions. We illustrate its use with a graph of co-authors from different communities
Ghanem, Abdelmotaal Marwan Tarek. "Les centralités temporelles : étude de l'importance des noeuds dans les réseaux dynamiques". Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS086.
Texto completoNowadays, interactions are a huge part of our daily life. These interactions can represent the diffusion of rumors, diseases, etc. Understanding how these interactions affect our life is quite important. A natural way to do so is using graph theory. However, this is not straightforward as studies show the temporal aspect, in other words, the order of interactions, should be taken into account. In this work, we concentrated on detecting the important individuals in these graphs using centrality metrics that take into account the temporal aspect. We proposed a comparison protocol that compares the different centrality metrics that exist. We applied it on several networks, which gave us insight on how the different metrics react. Secondly, we observed the high computational need of these centrality metrics. Therefore, we introduced a method to reduce this need. And finally, we introduced a novel centrality metric that we call ego-betweenness centrality
Rannou, Léo. "Temporal Connectivity and Path Computation for Stream Graph". Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS418.
Texto completoFor a long time, structured data and temporal data have been analysed separately. Many real world complex networks have a temporal dimension, such as contacts between individuals or financial transactions. Graph theory provides a wide set of tools to model and analyze static connections between entities. Unfortunately, this approach does not take into account the temporal nature of interactions. Stream graph theory is a formalism to model highly dynamic networks in which nodes and/or links arrive and/or leave over time. The number of applications of stream graph theory has risen rapidly, along with the number of theoretical concepts and algorithms to compute them. Several theoretical concepts such as connected components and temporal paths in stream graphs were defined recently, but no algorithm was provided to compute them. Moreover, the algorithmic complexities of these problems are unknown, as well as the insight they may shed on real-world stream graphs of interest. In this thesis, we present several solutions to compute notions of connectivity and path concepts in stream graphs. We also present alternative representations - data structures designed to facilitate specific computations - of stream graphs. We provide implementations and experimentally compare our methods in a wide range of practical cases. We show that these concepts indeed give much insight on features of large-scale datasets. Straph, a python library, was developed in order to have a reliable library for manipulating, analysing and visualising stream graphs, to design algorithms and models, and to rapidly evaluate them
Mostefaoui, Mustapha. "Analyse des propriétés temporelles des graphes d'événements valués continus". Nantes, 2001. http://www.theses.fr/2001NANT2100.
Texto completoCasteigts, Arnaud. "Contribution à l'algorithmique distribuée dans les réseaux mobiles ad hocCalculs locaux et réétiquetages de graphes dynamiques". Bordeaux 1, 2007. http://www.theses.fr/2007BOR13430.
Texto completoGhanem, Abdelmotaal Marwan Tarek. "Les centralités temporelles : étude de l'importance des noeuds dans les réseaux dynamiques". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS086/document.
Texto completoNowadays, interactions are a huge part of our daily life. These interactions can represent the diffusion of rumors, diseases, etc. Understanding how these interactions affect our life is quite important. A natural way to do so is using graph theory. However, this is not straightforward as studies show the temporal aspect, in other words, the order of interactions, should be taken into account. In this work, we concentrated on detecting the important individuals in these graphs using centrality metrics that take into account the temporal aspect. We proposed a comparison protocol that compares the different centrality metrics that exist. We applied it on several networks, which gave us insight on how the different metrics react. Secondly, we observed the high computational need of these centrality metrics. Therefore, we introduced a method to reduce this need. And finally, we introduced a novel centrality metric that we call ego-betweenness centrality
Aynaud, Thomas. "Détection de communautés dans les réseaux dynamiques". Paris 6, 2011. http://www.theses.fr/2011PA066438.
Texto completoMost complex networks have a particular structure in which nodes are arranged in groups, called communities, with many internal links but only a few between them. The identification of communities gives insights on the structure of the graph and is important in many contexts. We will study this structure in the case of dynamic networks using two different approaches. The first approach consists in tracking communities over time by detecting them at every timestep and following their evolution. We will see that although very natural, this approach raises many questions of stability: the algorithms tend to change their results a lot even if the network changes only a little. This implies that the observed changes in the communities are in fact related to the algorithm and not to real transformations in network structure. We therefore propose an analysis of the instability of three algorithms and a solution to the instability. The second approach consists in detecting the community structure not just for a moment but for a period of time called the time window. The length of the time window is then a crucial problem and we propose a hierachical time segmentation method in time windows. Moreover, the time windows do not have to be contiguous allowing for example to detect a repeating structure. Finally, we conclude with applications to event detection on the Internet and segmentation of videos. We will show that we can detect events by finding the times when the structure changes abruptly. For the segmentation of videos, we also had stability issues and thus we have developed a more stable tracking and detection algorithm
Castets, Mathieu. "Pavages réguliers et modélisation des dynamiques spatiales à base de graphes d'interaction : conception, implémentation, application". Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS241/document.
Texto completoThe modelling and simulation of spatial dynamics, particularly for studying landscape changes or environmental issues, raises the question of integrating different forms of spatial representation within the same model. Ocelet is an approach for modelling spatial dynamics based on the original concept of interaction graph. Such a graph holds both the structure of a relation between entities of a model and the semantics describing its evolution. The relationships between spatial entities are here translated into interaction graphs and these graphs are made to evolve during a simulation. The concepts on which Ocelet is based can potentially handle two known forms of spatial representation: shapes with contours (vector format) or regular grid cells (raster). The vector format is already integrated in the first version of Ocelet. The integration of raster and the combination of the two remained to be studied and carried out. The aim of the thesis is to first study the issues related to the integration of continuous fields and their representation by regular tiling, both in the Ocelet language and the concepts on which it is based. The dynamic aspects of this integration had to be taken into account and transitions between different forms of geographic data and interaction graphs had to be studied in the light of the concepts formalized. The concepts were then implemented in the Ocelet modelling platform, with the adaptation of both its compiler and runtime. Finally, these new concepts and tools were tested in three very different cases: two models on Reunion Island, the first simulating runoff in Ravine Saint Gilles watershed in the West Coast of the island, the other simulating the spread of invasive plants in the high plains inside the Reunion National Park. The last case describes the spatialisation of a crop model and is applied here to simulate the cereal crop yields in West Africa, in the context of an early warning system for regional crop monitoring
Hamaci, Samir. "Etude des graphes d'événements temporisés avec multiplieurs dans l'algèbre (min, +)". Angers, 2005. http://www.theses.fr/2005ANGE0021.
Texto completoTimed event graphs with multipliers form a subclass of Petri nets whose behavior can not be described by linear equations in (min, +) algebra. This nonlinearity is due to the presence of weights on arcs. This report is devoted to the study of dynamic systems modelled by discrete timed event graphs with multipliers and hybrid timed event graphs with multipliers. We tackle the problem of input-output representation of these graphs, in (min,+) algebra. To mitigate the problem of nonlinearity, an approach of modelling, based on operators, is proposed. A just in time control is calculated for discrete timed event graphs with multipliers. An extension of this control to the hybrid Timed event graphs with multipliers is presented. Then, the performance analysis of timed event graphs with multipliers, is tackled. We propose two linearization methods of these graphs, in the purpose to obtain a linear representation in (min, +) algebra, and to apply some basic results of the spectral theory, usually used to evaluate the performances of ordinary timed event graphs
Vimont, Guillaume. "Approximation dynamique de clusters dans un graphe social : méthodes et applications". Thesis, Paris 2, 2019. http://www.theses.fr/2019PA020007.
Texto completoWe study how to detect clusters in a graph defined by a stream of edges, without storing the entire graph. We show how to detect large clusters in the order of √n in graphs that have m = O(n log(n)) edges, while storing √n.log(n) edges. Social graphs satisfy this condition m. We extend our approach to dynamic graphs defined by the most recent stream of edges and multiple streams. We propose simple and robust methods based on the approximation to detect these clusters.We define the content correlation of two streams ρ(t) is the Jaccard similarity of their clusters in the windows before time t. We propose a simple and efficient method to approach this online correlation and show that for dynamic random graphs that follow a power law, we can guarantee a good approximation.As an applications we follow Twitter streams and compute their content correlations online. We then propose a search by correlation where answers to sets of keywords are entirely based on the small correlations of the streams. Answers are ordered by the correlations, and explanations can be traced with the stored clusters
Guennoun, Mohammed Karim. "Architectures dynamiques dans le contexte des applications à base de composants et orientées services". Toulouse 3, 2006. http://www.theses.fr/2006TOU30236.
Texto completoAdaptability for software applications can be separated into two categories. First relates to the behavioral adaptation also called algorithmic adaptation. This adaptation addresses the redefinition of the behavior of the application and its components and implies, for example, adding a new method into the interface of a component or updating the orchestration protocol that coordinates a set of services. Second category, in which we can classify our work, relates to the structural adaptation and implies a reconfiguration at the architectural level. This kind of reconfiguration deals with the organization of the architecture and involve, for instance, the substitution of a failing component by another with same functionalities or the redirection for a customer of a service which does not respect the QoS contract towards a service likely to offer better guarantees. In this thesis, we specify a meta-model relating to the description and the automatic management of dynamic architectures. Architecture instances are described by extended graphs where components (or services) are represented by vertices, and interdependencies (e. G. Connections, relations of control. . . Etc) are described by edges. The architectural styles are specified by extended graph grammars. The meta-model considers descriptions by admitting various abstraction levels and offers mechanisms to either abstract or refine descriptions according to specific points of view. It, also, makes it possible to describe architecture management protocols and to characterize the architectural properties to be preserved for each considered architectural level. We developed an algorithm for graph homomorphisms building and an algorithm for graph transformation in the context of extended graph grammars defined for our meta-model. .
Fotsu, Ngwompo Roger. "Contribution au dimensionnement des systèmes sur des critères dynamiques et énergétiques : approche par bond graph". Lyon, INSA, 1997. http://www.theses.fr/1997ISAL0023.
Texto completoThe purpose of this work is to present a methodology to validate the size of a system components for its proper operation based on dynamic and energetic criteria. If some specifications of a desired performance are given and a structure of actuator system is chosen, then the problem considered here is to check that components of the actuator system are able to follow the desired dynamic while satisfying the power constraints. The modelling tool adopted is bond graph for its property of representing power transfer and interconnections between elements of a system. The links between sizing problem and inverse system have led us to study the problem of system inversion firstly using classical theory. We then propose a bond graph based method for invertibility study and a procedure for construction of inverse bond graph using the concept of bicausality. Some structural anal y sis on the inverse bond graph are carried out by exploiting the properties of bicausal bonds. These theoretical tools and the graphic representation of inverse model then allow us to develop a method for verification of the appropriateness of an actuator system to some performance specifications by checking the proper operation of the system at each lev el from the output to the input. For illustration, the proposed method is applied to the validation of a two-link manipulator actuators and it is thus possible to analyse the causes of saturations and to detect components which impose limitations to the performance of the system
Frusque, Gaëtan. "Inférence et décomposition modale de réseaux dynamiques en neurosciences". Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN080.
Texto completoDynamic graphs make it possible to understand the evolution of complex systems evolving over time. This type of graph has recently received considerable attention. However, there is no consensus on how to infer and study these graphs. In this thesis, we propose specific methods for dynamical graph analysis. A dynamical graph can be seen as a succession of complete graphs sharing the same nodes, but with the weights associated with each link changing over time. The proposed methods can have applications in neuroscience or in the study of social networks such as Twitter and Facebook for example. The issue of this thesis is epilepsy, one of the most common neurological diseases in the world affecting around 1% of the population.The first part concerns the inference of dynamical graph from neurophysiological signals. To assess the similarity between each pairs of signals, in order to make the graph, we use measures of functional connectivity. The comparison of these measurements is therefore of great interest to understand the characteristics of the resulting graphs. We then compare functional connectivity measurements involving the instantaneous phase and amplitude of the signals. We are particularly interested in a measure called Phase-Locking-Value (PLV) which quantifies the phase synchrony between two signals. We then propose, in order to infer robust and interpretable dynamic graphs, two new indexes that are conditioned and regularized PLV. The second part concerns tools for dynamical graphs decompositions. The objective is to propose a semi-automatic method in order to characterize the most important patterns in the pathological network from several seizures of the same patient. First, we consider seizures that have similar durations and temporal evolutions. In this case the data can be conveniently represented as a tensor. A specific tensor decomposition is then applied. Secondly, we consider seizures that have heterogeneous durations. Several strategies are proposed and compared. These are methods which, in addition to extracting the characteristic subgraphs common to all the seizures, make it possible to observe their temporal activation profiles specific to each seizures. Finally, the selected method is used for a clinical application. The obtained decompositions are compared to the visual interpretation of the clinician. As a whole, we found that activated subgraphs corresponded to brain regions involved during the course of the seizures and their time course were highly consistent with classical visual interpretation
Mezyani, Touria El. "Méthodologie de surveillance des systèmes dynamiques hybrides". Lille 1, 2005. https://pepite-depot.univ-lille.fr/RESTREINT/Th_Num/2005/50376-2005-122.pdf.
Texto completoDémare, Thibaut. "Une approche systémique à base d'agents et de graphes dynamiques pour modéliser l'interface logistique port-métropole". Thesis, Le Havre, 2016. http://www.theses.fr/2016LEHA0021/document.
Texto completoA logistic system is an essential component of a spatial system. Actors are organised around infrastructures in order to move different kinds of flow (of goods, of information, or financial) over a territory. The logistic organisation comes from an auto-organised and distributed process from the actors. This works aims to understand, at different scales, how autonomous and heterogeneous actors (according to their goals and methods to take decisions) are collectively organised around infrastructures to manage different kinds of flow, and despite numerous constraints (temporal, spatial,...). We propose an agent-based model which allows to simulate the processes to create and organise logistic flow over a territory. The model describes an interface between international and urban flow in order to understand how the port and urban dynamics work together. The model integrates a structural and organisational dynamics thanks to dynamic graphs in order to represent the evolution of this kind of system. Thus, the agents can adapt themselves to system's perturbations as in the reality
Magos, Rivera Miguel. "Sur la modélisation des systèmes dynamiques à topologie variable : une formulation Hamiltonienne à ports paramétrée". Lyon 1, 2005. http://www.theses.fr/2005LYO10016.
Texto completoCasteigts, Arnaud. "Contribution à l'algorithmique distribuée dans les réseaux mobiles ad hoc - Calculs locaux et réétiquetages de graphes dynamiques". Phd thesis, Université Sciences et Technologies - Bordeaux I, 2007. http://tel.archives-ouvertes.fr/tel-00193181.
Texto completoVarloot, Rémi. "Dynamic network formation". Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEE048/document.
Texto completoThis thesis focuses on the rapid mixing of graph-related Markov chains. The main contribution concerns graphs with local edge dynamics, in which the topology of a graph evolves as edges slide along one another. We propose a classification of existing models of dynamic graphs, and illustrate how evolving along a changing structure improves the convergence rate. This is complemented by a proof of the rapid mixing time for one such dynamic. As part of this proof, we introduce the partial expansion of a graph. This notion allows us to track the progression of the dynamic, from a state with poor expansion to good expansion at equilibrium. The end of the thesis proposes an improvement of the Propp and Wilson perfect sampling technique. We introduce oracle sampling, a method inspired by importance sampling that reduces the overall complexity of the Propp and Wilson algorithm. We provide a proof of correctness, and study the performance of this method when sampling independent sets from certain graphs
Benamara, Lamia. "Dynamique des graphes de terrain : caractérisation et étude du biais lié à la mesure". Paris 6, 2011. http://www.theses.fr/2011PA066447.
Texto completoComplex networks appear in many contexts: computer networks, social networks, web graphs, etc. Until recently, these objects were mainly studied from a static point of view. However, most of these graphs are dynamic. This dynamics may appear differently depending on the context: social networks in which connections between people appear and disappear over time, web graphs in which web pages are created or deleted, etc. Many results of the last 10 years have introduced a set of tools for the analysis and the description of static graphs, but little has been done to study their dynamics. In this this thesis, we addressed the problem of characterizing the dynamics of complex networks, taking into account the measurement bias, by considering concrete cases of dynamic graphs. We made two main contributions. First, we studied the bias in the dynamics measurement induced by the fact that the observation period is finite. We introduced a new methodology for deciding if the length of the observation period is sufficient to rigorously characterize a given property. This methodology is generic and can be applied to any property in any dynamic system. To illustrate its relevance, we have applied it to several properties in a large P2P system. Our second contribution consists in an approach to characterize the dynamics of contact networks. We attempted to characterize the global dynamics of these systems, and to identify nodes with particular behaviors. We studied several datasets of contact networks between individuals and we have shown that each dataset has its particularities. We also found that some characteristics are shared by all datasets. In particular, the global dynamics of the network changes depending on the observation period and the behavior of some nodes differs from the global behavior of the system
Canu, Maël. "Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux". Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066378.
Texto completoOur research is in the field of complex network analysis and mining, specifically addressing the communit detection task, ie. algorithms aiming to uncover particularly dense subgraphs. We focus on the implementation of such an algorithm in a decentralised and distributed context : opportunistic MANET constituted of small wireless devices using peer-to-peer communication. To tackle the implementation constraints in such networks, we propose several methods designed according to the novel and trending vertex-centred paradigm, by combining Think-Like-a-Vertex graph processing with vertex-centred community detection methods based on leaders or seeds : they show specific properties allowing dsitributed implementations suiting the opportunistic MANET case. In this context, we first a global working principle and implement it in three different algorithms dedicated to three different configurations of community detection : the VOLCAN algorithm manages the classical disjoint community detection task in a static graph. We extend it with the LOCNeSs algorithm, that is dealing with overlapping communities which means that one vertex can belong to several communities. It adds more flexibility to the method and more significance to produced results. We also tackle the dynamic graphe case (graph evolving over time), addressed by the DynLOCNeSs algorithm.Each algorithm comes with a decentralised implementation and theoretical as well as experimental studies conducted both on real and synthetic benchmark data, allowing to evaluate the quality of the results and compare to existing state-of-the-art methods. Finally, we consider a special case of opportunistic decentralised MANET developped as a part of a research project about smart and communicating clothing. We formalise a task of path finding between smart t-shirts holders and propose a recommandation strategy using community structure, that we model and evaluate through an algorithm named SWAGG
Martinet, Lucie. "Réseaux dynamiques de terrain : caractérisation et propriétés de diffusion en milieu hospitalier". Thesis, Lyon, École normale supérieure, 2015. http://www.theses.fr/2015ENSL1010/document.
Texto completoIn this thesis, we focus on tools whose aim is to extract structural and temporal properties of dynamic networks as well as diffusion characteristics which can occur on these networks. We work on specific data, from the European MOSAR project, including the network of individuals proximity from time to time during 6 months at the Brek-sur-Mer Hospital. The studied network is notable because of its three dimensions constitution : the structural one induced by the distribution of individuals into distinct services, the functional dimension due to the partition of individual into groups of socio-professional categories and the temporal dimension.For each dimension, we used tools well known from the areas of statistical physics as well as graphs theory in order to extract information which enable to describe the network properties. These methods underline the specific structure of the contacts distribution which follows the individuals distribution into services. We also highlight strong links within specific socio-professional categories. Regarding the temporal part, we extract circadian and weekly patterns and quantify the similarities of these activities. We also notice distinct behaviour within patients and staff evolution. In addition, we present tools to compare the network activity within two given periods. To finish, we use simulations techniques to extract diffusion properties of the network to find some clues in order to establish a prevention policy
Pigné, Yoann. "Modélisation et traitement décentralisé des graphes dynamiquesApplication aux réseaux mobiles ad hoc". Phd thesis, Université du Havre, 2008. http://tel.archives-ouvertes.fr/tel-00371962.
Texto completoNous étudions la résolution de problèmes dans ces graphes à l'aide de méthodes inspirées de mécanismes d'intelligence collective.
Les modèles proposés sont validés dans le contexte applicatif des réseaux mobiles ad hoc. Une approche originale de construction et de maintien de chemins de communication sous plusieurs contraintes est proposée. Le problème de la construction et du maintien d'une forêt couvrante dans un réseau mobile ad hoc est également étudié.
Bratcu, Antoneta. "Détermination systématique des graphes de précédence et équilibrage des lignes d'assemblage". Phd thesis, Université de Franche-Comté, 2001. http://tel.archives-ouvertes.fr/tel-00258992.
Texto completoCazabet, Rémy. "Détection de communautés dynamiques dans des réseaux temporels". Phd thesis, Université Paul Sabatier - Toulouse III, 2013. http://tel.archives-ouvertes.fr/tel-00874017.
Texto completoEdibe, Bénédicte. "Modélisation et simulation de systèmes dynamiques par les bond graphs : application aux systèmes mécaniques polyarticulés". Rennes 1, 1995. http://www.theses.fr/1995REN1A007.
Texto completoZaïdi, Abdelaziz. "Intégration des réseaux bayésiens et bond graphs pour la supervision des systèmes dynamiques". Thesis, Lille 1, 2012. http://www.theses.fr/2012LIL10035/document.
Texto completoThe supervision of complex and critical industrial processes is a very heavy task which requires effective algorithms. The literature shows a growing interest of graphical approaches because of the simplicity of establishment of the derived algorithms. The model based diagnosis is a method which becomes widespread because of the richness of graphical and structural methods allowing modeling of most complex processes. The bond graph (BG) tool, with its multidisciplinary representation, is one of the most recognized approaches in this framework. In this context, we try in present work to couple this graphical approach with another graphical one allowing incorporating statistics of components failures. All this aims to mitigate the problems: unknown failure signatures or identical signatures for several components and monitoring the system degradation. Indeed, on the basis of consulted literature, it does not appear work which evokes a supervision strategy associating a Bayesian reliability model with a BG model based fault detection and isolation (FDI) approach. Consequently, the suggested work illustrates a method to outline this objective. We propose a new methodology for the supervision of the dynamic and hybrid dynamic systems. Our contribution appears in the proposal for a strategy of risk based supervision by combining two graphical approaches: BG and Bayesian networks (BN). The resulting model for diagnosis is a hybrid BN. It is able to make a decision under uncertainties of BG model and takes account of the probabilities of false alarm and non-detection. Furthermore, integration of two graphical approaches (BG and Bayesian networks (BN) to design robust supervision system is another innovative interest. Generated residuals from BG model are coupled with the component reliability model of components leading to a hybrid BN diagnostic model. This model is then used to make a decision under uncertainties of BG model and takes into account the probabilities of false alarm and non-detection. The developed theory is applied to a thermal power station
Six, Béranger. "Génération automatique de modèles pour la supervision des systèmes dynamiques hybrides : application aux systèmes ferroviaires". Thesis, Lille, 2018. http://www.theses.fr/2018LIL1I048.
Texto completoThis thesis work contributes to perform a automed model builder for Hybrid Dynamic Systems (HDS) with numerous modes. Technological components including sensors with an iconic format can be automatically export from a computer-aided design (CAD) scheme or manually drag from database and interconnected, so as to produce the overall HDS model, following industrial technological schemes. Once the model has been created, block diagram for simulation and diagnosis and a Fault Signature Matrix (FSM) could be generated.The theory and algorithm behind the software are based on Hybrid Bond Graphs (HBG). The switching behaviour engenders variables dynamics (particularly causal changes). To solve this problematic, news algorithm are performed. Compared with developed programs for automated modelling, the presented algorithm are valid for continuous, discrete and hybrid systems. The theory is illustrated by an industrial application which consists of the pneumo-electrical control of rolling stock
Coutereel, Luc. "Étude et réalisation d'un processeur d'aide à la modélisation des systèmes dynamiques par l'approche Bond-Graph". Lille 1, 1991. http://www.theses.fr/1991LIL10003.
Texto completoGuennoun, Mohammed Karim. "Architectures dynamiques dans le contexte des applications à base de composants et orientées service". Phd thesis, Université Paul Sabatier - Toulouse III, 2006. http://tel.archives-ouvertes.fr/tel-00136075.
Texto completoBournat, Marjorie. "Graceful Degradation and Speculation for Robots in Highly Dynamic Environments". Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS035.
Texto completoDistributed systems are systems composed of multiple communicant processes cooperating to solve a common task. This is a generic model for numerous real systems as wired or mobile networks, shared-memory multiprocessor systems, and so on. From an algorithmic point of view, it is well-known that strong assumptions (as asynchronism or mobility) on such systems lead often to impossibility results or high lower bounds on complexity. In this thesis, we study algorithms that adapt themselves to their environment (i.e., the union of all assumptions on the system) by focusing on the two following approaches. Graceful degradation circumvents impossibility results by degrading the properties offered by the algorithm as the environment become stronger. Speculation allows to bypass high lower bounds on complexity by optimizing the algorithm only on more probable environments. Robot networks are a particular case of distributed systems where processes are endowed with sensors and able to move from a location to another. We consider dynamic environments in which this ability may evolve with time. This thesis answers positively to the open question whether it is possible and attractive to apply gracefully degrading and speculative approaches to robot networks in dynamic environments. This answer is obtained through contributions on gracefully degrading gathering (where all robots have to meet on the same location in finite time) and on speculative perpetual exploration (where robots must visit infinitely often each location)
Gilbert, Frédéric. "Méthodes et modèles pour la visualisation de grandes masses de données multidimensionnelles nominatives dynamiques". Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14498/document.
Texto completoSince ten years, informations visualization domain knows a real interest.Recently, with the growing of communications, the research on social networks analysis becomes strongly active. In this thesis, we present results on dynamic social networks analysis. That means that we take into account the temporal aspect of data. We were particularly interested in communities extraction within networks and their evolutions through time. [...]
Carvin, Denis. "Mécanismes de supervision distribuée pour les réseaux de communication dynamiques". Thesis, Toulouse, INSA, 2015. http://www.theses.fr/2015ISAT0025/document.
Texto completoWith the massive rise of wireless technologies, the number of mobile stations is constantly growing. Both their uses and their communication resources are diversified. By integrating our daily life objects, our communication networks become dynamic in terms of physical topology but also in term of resources. Furthermore, they give access to a richer information. As a result, the management task has become complex and requires shorter response time that a human administrator can not respect. It becomes necessary to develop an autonomic management behavior in next generation networks. In any manner, managing a system requires essential steps which are : its measurement and its supervision. Whatever the nature of a system, this stage of information gathering, allows its characterization and its control. The field of networks is not the exception to the rule and objects that compose them will need to acquire information on their environment for a better adaptation. In this thesis, we focus on the efficient sharing of this information, for self-analysis and distributed performance evaluation purposes. After having formalized the problem of the distributed measurement, we address in a first part the fusion and the diffusion of measures in dynamic graphs. We develop a new heuristic for the average consensus problem offering a better contraction rate than the ones of the state of the art. In a second part, we consider more stable topologies where TCP is used to convey measures. We offer a scheduling mechanism for TCP flows that guaranty the same impact on the network congestion, while reducing the average latency. Finally, we show how nodes can supervise various metrics such as the system performance based on their utilities and suggest a method to allow them to analyze the evolution of this performance
Abdelsadek, Youcef. "Triangle packing for community detection : algorithms, visualizations and application to Twitter's network". Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0310.
Texto completoRelational data in our society are on a constant increasing, rising arduous challenges. In this thesis, we consider two aspects of relational data. First, we are interested in relational data with weighted relationship. As a concrete example, relationships among Twitter's users could be weighted with regard to their shared number of followers. The second aspect is related to the dynamism which is inherent to data nature. As an instance, in the previous example the number of common followers between two Twitter's users can change over time. In order to handle these complex and dynamic relational data, we use the modelling strength of graphs. Another facet considered in this thesis deals with community identification on weighted and dynamic graphs. For an analyst, the community detection might be helpful to grasp the semantic behind the graph structure. Our assumption relies on the idea to use a set of disjoint pairwise triangles as a basis to detect the community structure. To select these triangles, several algorithms are proposed (i.e., branch-and-bound, greedy search, heuristics and genetic algorithm). Thereafter, we propose a community detection algorithm, called Tribase. In the latter, the weights of communities are compared allowing dominant communities to gain in size. Tribase is compared with the well-known LFR benchmark. The results show that Tribase identifies efficiently the communities while a community structure exists. Additionally, to asset Tribase on real-world data, we consider social networks data, especially Twitter's data, of the ANR-Info-RSN project. In order to support the analyst in its knowledge acquisition, we elaborate a visual interactive approach. To this end, an interactive application, called NLCOMS is introduced. NLCOMS uses multiple synchronous views for visualizing community structure and the related information. Furthermore, we propose an algorithm for the identification of communities over time, called Dyci. The latter takes advantage from the previously detected communities. Several changes' scenarios are considered like, node/edge addition, node/edge removing and edge weight update. The main idea of the proposed algorithm is to track whether a part of the weighted graph becomes weak over time, in order to merge it with the "dominant" neighbour community. In order to assess the quality of the returned community structure, we conduct a comparison with a genetic algorithm on real-world data of the ARN-Info-RSN project. The conducted comparison shows that Dyci algorithm provides a good trade-off between efficiency and consumed time. Finally, the dynamic changes which occur to the underlying graph structure can be visualized with NLCOMS which combines physical an axial time to fulfil this need
Halfeld, Ferrari Alves Mirian. "Aspects dynamiques de XML et spécification des interfaces de services web avec PEWS". Habilitation à diriger des recherches, Université François Rabelais - Tours, 2007. http://tel.archives-ouvertes.fr/tel-00271099.
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