Actuellement, la distribution spatiale des thons tropicaux pêchés par les senneurs français dans l'Océan Indien est représentée à partir des données de captures et d'effort issues des livres de bord. Or ces données ne comportent qu'une position par jour et le nombre de calées réalisées pendant cette journée : l'ensemble des zones prospectées sans action de pêche, synonyme d'absence d'agrégations de thon n'est pas connu. Ces zones seraient pourtant utiles à la cartographie des abondances. Cette flottille étant équipée de systèmes VMS (Vessel Monitoring Systems), les trajectoires données par les VMS sont utilisées pour déduire du comportement des navires, les zones de présence (pêche) et d'absence (non pêche) d'agrégations de thonidés. L'objectif est donc d'estimer l'activité d'un navire à partir de sa trajectoire. L'application d'un modèle markovien permet de distinguer les activités de route, de recherche, et d'arrêt, et de pêche. Pour la majorité des sorties en mer (exceptées celles où un observateur est à bord), l'activité réelle du navire n'est pas connue (variable latente), ce qui justifie l'approche par chaînes de Markov à états cachés. Le modèle a été développé dans un contexte bayésien incluant des priors sur certains des paramètres (vitesses, angles de changement de cap et matrice de transition). Il a été calibré et validé grâce aux données collectées par des observateurs embarqués sur 10% de la flottille. Le taux d'erreur est de 10% pour des positions VMS enregistrées toutes les heures. Une fois estimée, l'activité des senneurs en chaque point de leur trajectoire a permis (1) d'obtenir des indicateurs spatiaux et temporels de l'effort de la flottille de senneurs français, et (2) d'étudier la structure spatiale des zones de présence de bancs de thons (variogrammes d'indicatrices) et d'en déduire, par cokrigeage d'indicatrices, des cartes de présence/présence potentielle/absence de thon capturable, pouvant être interprétées comme indices d'abondance de thon.

[Truncated abstract. Formulae and special characters can only be approximated here. Please see the pdf version of this abstract for an accurate representation.] The 3.24 Ga Panorama VMS District, located in the Pilbara Craton of Western Australia, is exposed as a cross-section through subvolcanic granite intrusions and a coeval submarine volcanic sequence that hosts Zn-Cu mineralization. The near-complete exposure across the district, the very low metamorphic grade, and the remarkable preservation of primary igneous and volcanic textures provides an unparalleled opportunity to examine the P-T-X-source evolution of a VMS ore-forming system and to assess the role of the subvolcanic intrusions as heat sources and/or metal contributors to the overlying VMS hydrothermal system. Detailed mapping of the Panorama VMS District has revealed seven major vein types related to the VMS hydrothermal system or to the subvolcanic intrusions. (1) Quartz-chalcopyrite veins, hosted in granophyric granite immediately beneath the granite-volcanic contact, formed prior to main stage VMS hydrothermal convection, and were precipitated from mixed H2OCO 2-NaCl-KCl fluids with variable salinities (2.5 to 8.5 wt% NaCl equiv). (2) Quartz-sericite veins, ubiquitous across the top 50m of the volcanic sequence, were formed from an Archean seawater with a salinity of 9.7 to 11.2 wt% NaCl equiv at temperatures of 90° to 135°C. These veins formed synchronous with the regional feldspar-sericite-quartz-ankerite alteration during seawater recharge into the main stage VMS hydrothermal convection cells. (3) Quartz-pyrite veins hosted in granophyric granite, and (4) quartz-carbonate-pyrite veins hosted in andesitebasalt, also formed from relatively unevolved Archean seawater (5.5 to 10.1 wt% NaCl equiv; 150° to 225°C), but during the collapse of the VMS hydrothermal system when cool, unmodified seawater invaded the top of the subvolcanic intrusions. (5) Quartz-topaz-muscovite greisen, (6) quartz-chlorite-chalcopyrite vein greisen, and (7) hydrothermal Cu-Zn-Sn veins are hosted in the subvolcanic intrusions. Primary H2O-NaCl-CaCl2 fluid inclusions in the vein greisens were complex high temperature hypersaline inclusions (up to 590°C and up to 56 wt% NaCl equiv). The H2O-CO2-NaCl fluid inclusions in the Cu-Zn-Sn veins have variable salinities, ranging from 4.9 to 14.1 wt% NaCl equiv, and homogenization temperatures ranging from 160° to 325°C. The hydrothermal quartz veins and magmatic metasomatic phases in the subvolcanic intrusions were formed from a magmatic-hydrothermal fluid that had evolved through wallrock reactions, cooling, and finally mixing with seawater-derived VMS hydrothermal fluids.

The velocity dimension of Big Data refers to the need to rapidly process data that arrives continuously as streams of messages or events. Distributed Stream Processing Systems (DSPS) refer to distributed programming and runtime platforms that allow users to define a composition of dataflow logic that are executed on distributed resources over streams of incoming messages. A DSPS uses commodity clusters and Cloud Virtual Machines (VMs) for its execution. In order to meet the required performance for these applications, the DSPS needs to schedule these dataßows efficiently over the resources. Despite their growing use, resource scheduling for DSPSÕs tends to be done in an ad hoc manner, favoring empirical and reactive approaches, rather than a model-driven and analytical approach. Such empirical strategies may arrive at an approximate schedule for the dataflow that needs further tuning to meet the quality of service. We propose a model-based scheduling approach that makes use of performance profiles and benchmarks developed for tasks in the dataßow to plan both the resource allocation and the resource mapping that together form the schedule planning process. We propose the Model Based Allocation (MBA) and the Slot Aware Mapping (SAM) approaches that efectively utilize knowledge of the performance model of logic tasks to provide an efficient and predictable scheduling behavior. We implemented and validate these algorithms using the popular open source Apache Storm DSPS for several micro and application dataflows. The results show that our model-driven approach is able to reduce the amount of required resources (VMs) by 30% − 50% relative to existing techniques. Also we see that our strategies o↵er a predictable behavior that ensures that the expected and actual rates supported and resources used match closely. This can enable deterministic schedule planning even under dynamic conditions. Besides this static scheduling, we also examine the ability to dynamically consolidate tasks onto fewer VMs when the load on the dataßow decreases or the VMs get fragmented. We propose reliable task migration models for Apache Storm dataßows that are able to rapidly move the task assignment in the cluster, and resume the dataflow execution without any message loss.

L'objectif principal de cette thèse concerne la mise en oeuvre d'une méthoded'éléments finis stabilisés pour la simulation des plasmas de fusion. Pour cela,nous avons d'abord dérivé les modèles magnétohydrodynamiques depuis lemodèle cinétique. Les modèles MHD sont généralement utilisés pour simuler lesinstabilités macroscopiques des plasmas. Nous nous sommes concentrés sur lemodèles de la MHD complète. Ensuite, l'approche numérique est décrite dans lecadre de la stabilisation Variationelle Multi-Échelles (VMS). Cette stabilisationvient ajouter un terme à la formulation faible pour mimer les effets des échellesnon-résolues sur celles résolues. Si les effets de ces sous-échelles ne sont paspris en compte lorsque l'on traite des écoulements dominés par convection,comme dans le cadre des plasmas de fusion, le schéma numérique conduit àdes résultats non-physiques. Une étude détaillée de l'instabilité de « Kinkinterne » a été faite ainsi qu'une étude préliminaire des plasmas avec point-Xayant pour but la validation du schéma numérique développé ici / The main objective of this thesis concerns the implementation of a robuststabilized finite element method for simulating fusion plasmas. For that, we firstderive the magnetohydrodynamic models from the kinetic model. MHD modelsare generally used for macroscopic simulations of plasma instabilities. Weconcentrate ou efforts on the full MHD model. Next, the numerical approach isdescribed in the context of the Variational Multi-Scale (VMS) stabilization. Thisstabilization comes to add a term to the weak formulation to mimics the effectsof the unresolved scales over the coarse scales. If the effects of these subscalesare not taken into account when dealing with fluxes dominated byconvection, as it is the cases for fusion plasmas, the numerical scheme canlead to unphysical results. A detailed study of the resistive internal kinkinstability has been done as well as an introductory study of the so called Xpointplasmas in order to validate the numerical scheme developed here

Virtualisation is one of the underlying technologies that led to the success of cloud computing platforms (CCPs). The technology, along with other features such as multitenancy allows delivering of computing resources in the form of service through efficient sharing of physical resources. As these resources are provided through virtualisation, a robust agreement is outlined for both the quantity and quality-of-service (QoS) in a service level agreement (SLA) documents. QoS is one of the essential components of SLA, where performance is one of its primary aspects. As the technology is progressively maturing and receiving massive acceptance, researchers from industry and academia continue to carry out novel theoretical and practical studies of various essential aspects of CCPs with significant levels of success. This thesis starts with the assessment of the current level of knowledge in the literature of cloud computing in general and CCPs in particular. In this context, a substantive literature review was carried out focusing on performance modelling, testing, analysis and evaluation of Infrastructure as a Service (IaaS), methodologies. To this end, a systematic mapping study (SMSs) of the literature was conducted. SMS guided the choice and direction of this research. The SMS was followed by the development of a novel open queueing network model (QNM) at equilibrium for the performance modelling and analysis of an OpenStack IaaS CCP. Moreover, it was assumed that an external arrival pattern is Poisson while the queueing stations provided exponentially distributed service times. Based on Jackson’s theorem, the model was exactly decomposed into individual M/M/c (c ≥ 1) stations. Each of these queueing stations was analysed in isolation, and closed-form expressions for key performance metrics, such as mean response time, throughput, server (resource) utilisation as well as bottleneck device were determined. Moreover, the research was extended with a proposed open QNM with a bursty external arrival pattern represented by a Compound Poisson Process (CPP) with geometrically distributed batches, or equivalently, variable Generalised Exponential (GE) interarrival and service times. Each queueing station had c (c ≥ 1) GE-type servers. Based on a generic maximum entropy (ME) product form approximation, the proposed open GE-type QNM was decomposed into individual GE/GE/c queueing stations with GE-type interarrival and service times. The evaluation of the performance metrics and bottleneck analysis of the QNM were determined, which provided vital insights for the capacity planning of existing CCP architectures as well as the design and development of new ones. The results also revealed, due to a significant impact on the burstiness of interarrival and service time processes, resulted in worst-case performance bounds scenarios, as appropriate. Finally, an investigation was carried out into modelling and analysis of performance and security trade-offs for a CCP architecture, based on a proposed generalised stochastic Petri net (GSPN) model with security-detection control model (SDCM). In this context, ‘optimal’ combined performance and security metrics were defined with both M-type or GE-type arrival and service times and the impact of security incidents on performance was assessed. Typical numerical experiments on the GSPN model were conducted and implemented using the Möbius package, and an ‘optimal’ trade-offs were determined between performance and security, which are crucial in the SLA of the cloud computing services. / Petroleum technology development fund (PTDF) of the government of Nigeria Usmanu Danfodiyo University, Sokoto