A fusion system sometimes requires the capability to represent the temporal changes of uncertain sensory information in dynamic and uncertain situation. A Bayesian Network can construct a coherent fusion structure with the hypothesis node which cannot be observed directly and sensors through a number of intermediate nodes that are interrelated by cause and effect. In some BN applications for observing a hypothesis node with the number of participated sensors, rank and select the appropriate options (different combination of sensors allocation) in the decision-making is a challenging problem. By user interaction, we can acquire more and useful information through multi-criteria decision aid (MCDA) as semi-automatically decision support. So in this study, Multi Attribute Decision Making (MADM) techniques as TOPSIS, SAW, and Mixed (Rank Average) for decision-making as well as AHP and Entropy for obtaining the weights of indexes have been used. Since MADM techniques have most probably different results according to different approaches and assumptions in the same problem, statistical analysis done on them. According to results, the correlation between applied techniques for ranking BN options is strong and positive because of the close proximity of weights suggested by AHP and Entropy. Mixed method as compared to TOPSIS and SAW is ideal techniques; moreover, AHP is more acceptable than Entropy for weighting of indexes.

Il existe deux approches classiques et bien comprises des tâches de traitement vidéo pour la vidéoconférence. Le premier utilise une unité centralisée de contrôle multipoint. Dans la deuxième approche, les tâches de traitement vidéo sont directement traitées dans les clients. La performance est ensuite limitée par les caractéristiques du périphérique. Dans cette thèse, nous proposons une troisième approche alternative. Nous proposons un système qui distribue des tâches de traitement vidéo en temps réel sur les ressources internes de l'entreprise. Une méthode dédiée de prise de décision basée sur les multi-attributs est conçue pour tenir compte de la variété des attributs qui influent sur la qualité de l'expérience. Des algorithmes de distribution et de redistribution de tâches sont élaborés. Nous testons ensuite l'approche proposée au moyen de la simulation afin d'étudier l'impact des principaux paramètres critiques. L'approche proposée pose une question sur laquelle un PC peut être utilisé comme plate-forme pour le serveur multimédia. Nous estimons une qualité perçue des flux vidéo afin d'étudier l'influence de la charge CPU. Nous avons également élaboré des algorithmes, combinant l'approche Cloud / Fog avec différents types de serveurs multimédia. Le résultat fournit une solution de conférence optimisée en termes de coût tant pour le fournisseur que pour le consommateur, ainsi que pour l'expérience de l'utilisateur final. En combinant les algorithmes élaborés et l'architecture avec les résultats de l'expérimentation, nous concluons que la solution proposée peut être utilisée comme une nouvelle approche de la problématique de la vidéoconférence. / There exist two classical and well-understood approaches to video processing tasks for videoconferencing. The first one is using a centralized Multipoint Control Unit (MCU). In the second approach, the video processing tasks are directly handled in endpoints. Performance is then restricted by device characteristics, especially in the case of mobile devices. In this thesis, we propose a third alternative approach. We propose a system, which distributes real-time video processing tasks on enterprise desktop grid. A dedicated Multi Attribute Decision Making method is designed in order to take into account the variety of attributes impacting Quality of Experience. A number of task distribution and redistribution algorithms are elaborated. We then test the proposed approach by means of simulation in order to study the impact of the main critical parameters. The proposed approach arises a question to which extent a PC can be used as a platform for media server and how CPU load affects the quality of provided video conference. We estimate a perceived quality of video streams in order to investigate CPU load influence. Also we elaborated algorithms, combining Cloud/Fog approach with different types of media servers, the result provides an optimized conferencing solution in the terms of cost for both provider and consumer as well as in terms of end user experience. Combining elaborated algorithms and architecture with experimentation results we conclude that proposed solution can be used as a novel approach to video conferencing problematic.

The past decades have seen the state of the art in aerospace system design progress from a scope of simple optimization to one including robustness, with the objective of permitting a single system to perform well even in off-nominal future environments. Integrating flexibility, or the capability to easily modify a system after it has been fielded in response to changing environments, into system design represents a further step forward. One challenge in accomplishing this rests in that the decision-maker must consider not only the present system design decision, but also sequential future design and operation decisions. Despite extensive interest in the topic, the state of the art in designing flexibility into aerospace systems, and particularly space systems, tends to be limited to analyses that are qualitative, deterministic, single-objective, and/or limited to consider a single future time period. To address these gaps, this thesis develops a stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps. First, system configuration options are identified and costs of switching from one configuration to another are compiled into a cost transition matrix. Second, probabilities that demand on the system will transition from one mission to another are compiled into a mission demand Markov chain. Third, one performance matrix for each design objective is populated to describe how well the identified system configurations perform in each of the identified mission demand environments. The fourth step employs multi-period decision analysis techniques, including Markov decision processes (MDPs) from the field of operations research, to find efficient paths and policies a decision-maker may follow. The final step examines the implications of these paths and policies for the primary goal of informing initial system selection. Overall, this thesis unifies state-centric concepts of flexibility from economics and engineering literature with sequential decision-making techniques from operations research. The end objective of this thesis' framework and its supporting analytic and computational tools is to enable selection of the next-generation space systems today, tailored to decision-maker budget and performance preferences, that will be best able to adapt and perform in a future of changing environments and requirements. Following extensive theoretical development, the framework and its steps are applied to space system planning problems of (1) DARPA-motivated multiple- or distributed-payload satellite selection and (2) NASA human space exploration architecture selection.