Orthogonal frequency division multiplexing (OFDM) modulator with redundancy has been adopted in many wireless communication systems for higher data rate transmissions. The introduced redundancy at the transmitter allows us to overcome serious inter-block interference (IBI) problems due to highly dispersive channel. However, the selection of redundancy length will affect the system performance and spectral efficiency, and is highly dependent on the length of channel impulse response. In this thesis, based on the pseudorandom postfix (PRP) OFDM scheme we propose a novel block-based OFDM transceiver framework. Since in the PRP-OFDM system the PRP can be employed for semi-blind channel estimation with order-one statistics of the received signal. Hence, for sufficient redundancy case the PRP-OFDM system with the Bayesian decision feedback equalizer (DFE) is adopted for suppressing the IBI and ISI simultaneously. However, for the insufficient redundancy case (the length of redundancy is less than the order of channel), we first propose a modified scheme for channel estimation. To further reduce the complexity of receiver, the maximum shortening signal-to-noise-ratio time domain equalizer (MSSNR TEQ) with the Bayesian DFE is developed for suppressing the IBI and ISI, separately. That is, after knowing the channel state information (CSI) and removing the effect of IBI with MSSNR TEQ, the Bayesian DFE is applied for eliminating the ISI. Via computer simulation, we verify that performance improvement, in terms of bit error rate (BER), compared with the conventional block-based minimum mean square error (MMSE)-DFE can be achieved.

Η ποιότητα πολλών εκ των αποτελεσμάτων της σύγχρονης έρευνας εξαρτώνται άμεσα από την «ποιότητα» και την ποσότητα των τυχαίων αριθμών που χρησιμοποιούνται. Ειδικότερα σε τομείς όπως η στοχαστική μοντελοποίηση και προσομοίωση προτιμώνται οι ντετερμινιστικές γεννήτριες τυχαίων αριθμών, ή αλλιώς γεννήτριες ψευδοτυχαίων αριθμών λόγω της δυνατότητας αναπαραγωγής των αποτελεσμάτων και της μεταφερσιμότητας τους. Επομένως, μας είναι χρήσιμο να εντοπίσουμε ψευδοτυχαίες γεννήτριες αριθμών με αυξημένη φαινόμενη τυχαιότητα αποτελεσμάτων. Για το λόγο αυτό, στη διπλωματική εργασία προτείνεται και εξετάζεται η καταλληλότητα της θραυσματικής διάστασης (fractal dimension) για την αξιολόγηση ψευδοτυχαίων γεννητριών τυχαίων αριθμών (Pseudorandom Number Generators). Η θραυσματική διάσταση αποτελεί μία μετρική που δύναται να εκφράσει την τυχαιότητα των αποτελεσμάτων μιας γεννήτριας ψευδοτυχαίων αριθμών καθώς «ποσοτικοποιεί» την κατανομή των ψευδοτυχαίων αριθμών στον ευκλείδειο χώρο. Σε πρώτο στάδιο γίνεται μία επισκόπηση των υπαρχουσών μεθοδολογιών παραγωγής τυχαίων αριθμών καθώς και των προσεγγίσεων για την αξιολόγηση της απόδοσης των ψευδοτυχαίων γεννητριών τυχαίων αριθμών. Οι καθιερωμένες τεχνικές που εφαρμόζονται για την αξιολόγηση μιας γεννήτριας εστιάζουν σε στατιστικά χαρακτηριστικά που έχουν ως στόχο να μετρήσουν πόσο απρόβλεπτα είναι τα αποτελέσματά της, ή χαρακτηριστικά όπως η περίοδος μιας γεννήτριας. Ακολούθως, μελετάται η θραυσματική διάσταση και οι προτεινόμενες στη βιβλιογραφία μέθοδοι υπολογισμού της. Στο στάδιο αυτό επιλέγεται η κατάλληλη μέθοδος για τον υπολογισμό της θραυσματικής διάστασης. Στο τελευταίο πειραματικό στάδιο παρουσιάζονται τα αποτελέσματα της μέτρησης της μορφοκλασματικής διάστασης. Οι ψευδοτυχαίες γεννήτριες προς αξιολόγηση που μετείχαν στα υπολογιστικά πειράματα ήταν η Γραμμική Αναλογική γεννήτρια, η γεννήτρια Blum-Blum-Shub, η γεννήτρια που βασίζεται στο κρυπτοσύστημα RSA και η γεννήτρια που βασίζεται στο πρόβλημα του διακριτού λογαρίθμου. Τα υπολογιστικά πειράματα επιχειρούν να ανακαλύψουν την απόδοση των εξεταζόμενων γεννητριών αλλά και την ευαισθησία της συμπεριφοράς τους ως προς τις παραμέτρους εισόδου των γεννητριών. / Scientific experimental results are highly dependent on the "quality" and quantity of random numbers used for these experiments. Especially in areas such as stochastic modeling and simulation, deterministic random number generators, known as pseudorandom number generators are preferred because of reproducibility of the results and their portability. Trying to identify pseudorandom number generators sequences which appear to be random, we examine the suitability of Fractal Dimension measurement for assessing Pseudorandom Number Generators. The established techniques that are used to evaluate a generator are focused on statistical features that are designed to detect correlations into generated pseudorandom number sequences. On the other hand, Fractal Dimension is a metric that can express the randomness of the results of a pseudorandom number generator as it "quantifies" the distribution of pseudorandom numbers in Euclidean space. We attempt to evaluate some Pseudorandom Number Generators, like classical Linear Congruential generator, Blum-Blum-Shub generator, the generator based on RSA cryptosystem and the generator based on the Discrete Logarithm problem. The computational experiments presented in our work attempt to assess the performance and the sensitivity of the examined generators.

A software GPS receiver is a functional GPS receiver in software. It has several advantages compared to its hardware counterparts. For instance, improvements in receiver architecture as well as GPS system structure can be easily adapted to it. Furthermore, interaction between nearby sensors can be coordinated easily. In this thesis, a SGR (software GPS receiver) is presented from a practical point of view. Major components of the SGR are implemented in Matlab environment. Furthermore, some alternative algorithms are implemented. SGR implementation is considered in two main sections namely a signal processing section and a navigation section. Signal processing section is driven by the raw GPS signal samples obtained from a GPS front-end of NordNavTM R-25 instrument. The conventional and the block adjustment of synchronizing signal (BAAS) processing methods are implemented and their performances are compared in terms of their speed and outputs. Signal processing section outputs raw GPS measurements and navigation data bits. Since the output data length is insufficient in our case, navigation section input is fed from AshtechTM GPS receiver for a moving platform and TrimbleTM GPS Receiver for a stationary platform. Satellite position computation, pseudorange corrections, Kalman filter and LSE (least squares estimation) are implemented in the navigation section. Kalman filter and LSE methods are compared in terms of positioning accuracy for a moving as well as a stationary platform. Results are compared with the commercial GPS outputs. This comparison shows that the software navigation section is equivalent to the commercial GPS in terms of positioning accuracy.

Nous présentons deux contributions dans le domaine de la programmation parallèle. La première est théorique : nous introduisons l’analyse SIPS, une approche nouvelle pour dénombrer le nombre d’opérations de synchronisation durant l’exécution d’un algorithme parallèle ordonnancé par vol de travail. Basée sur le concept d’horloges logiques, elle nous permet : d’une part de donner de nouvelles majorations de coût en moyenne; d’autre part de concevoir des programmes parallèles plus efficaces par adaptation dynamique de la granularité. La seconde contribution est pragmatique : nous présentons une parallélisation générique d’algorithmes pour la génération déterministe de nombres pseudo-aléatoires, indépendamment du nombre de processus concurrents lors de l’exécution. Alternative à l’utilisation d’un générateur pseudo-aléatoire séquentiel par processus, nous introduisons une API générique, appelée Par-R qui est conçue et analysée grâce à SIPS. Sa caractéristique principale est d’exploiter un générateur séquentiel qui peut “sauter” directement d’un nombre à un autre situé à une distance arbitraire dans la séquence pseudo-aléatoire. Grâce à l’analyse SIPS, nous montrons qu’en moyenne, lors d’une exécution par vol de travail d’un programme très parallèle (dont la profondeur ou chemin critique est très petite devant le travail ou nombre d’opérations), ces opérations de saut sont rares. Par-R est comparé au générateur pseudo-aléatoire DotMix écrit pour Cilk Plus, une extension de C/C++ pour la programmation parallèle par vol de travail. Le surcout théorique de Par-R se compare favorablement au surcoput de DotMix, ce qui apparait aussi expériemntalement. De plus, étant générique, Par-R est indépendant du générateur séquentiel sous-jacent. / Nós apresentamos duas contribuições para a área de programação paralela. A primeira contribuição é teórica: nós introduzimos a análise SIPS, uma nova abordagem para a estimar o número de sincronizações realizadas durante a execução de um algoritmo paralelo. SIPS generaliza o conceito de relógios lógicos para contar o número de sincronizações realizadas por um algoritmo paralelo e é capaz de calcular limites do pior caso mesmo na presença de execuções paralelas não-determinísticas, as quais não são geralmente cobertas por análises no estado-da-arte. Nossa análise nos permite estimar novos limites de pior caso para computações escalonadas pelo popular algoritmo de roubo de tarefas e também projetar programas paralelos e adaptáveis que são mais eficientes. A segunda contribuição é pragmática: nós apresentamos uma estratégia de paralelização eficiente para a geração de números pseudoaleatórios. Como uma alternativa para implementações fixas de componentes de geração aleatória nós introduzimos uma API chamada Par-R, projetada e analisada utilizando-se SIPS. Sua principal idea é o uso da capacidade de um gerador sequencial R de realizar um “pulo” eficiente dentro do fluxo de números gerados; nós os associamos a operações realizadas pelo escalonador por roubo de tarefas, o qual nossa análise baseada em SIPS demonstra ocorrer raramente em média. Par-R é comparado com o gerador paralelo de números pseudoaleatórios DotMix, escrito para a plataforma de multithreading dinâmico Cilk Plus. A latência de Par-R tem comparação favorável à latência do DotMix, o que é confirmado experimentalmente, mas não requer o uso subjacente fixado de um dado gerador aleatório. / We present two contributions to the field of parallel programming. The first contribution is theoretical: we introduce SIPS analysis, a novel approach to estimate the number of synchronizations performed during the execution of a parallel algorithm. Based on the concept of logical clocks, it allows us: on one hand, to deliver new bounds for the number of synchronizations, in expectation; on the other hand, to design more efficient parallel programs by dynamic adaptation of the granularity. The second contribution is pragmatic: we present an efficient parallelization strategy for pseudorandom number generation, independent of the number of concurrent processes participating in a computation. As an alternative to the use of one sequential generator per process, we introduce a generic API called Par-R, which is designed and analyzed using SIPS. Its main characteristic is the use of a sequential generator that can perform a “jump-ahead” directly from one number to another on an arbitrary distance within the pseudorandom sequence. Thanks to SIPS, we show that, in expectation, within an execution scheduled by work stealing of a “very parallel” program (whose depth or critical path is subtle when compared to the work or number of operations), these operations are rare. Par-R is compared with the parallel pseudorandom number generator DotMix, written for the Cilk Plus dynamic multithreading platform. The theoretical overhead of Par-R compares favorably to DotMix’s overhead, what is confirmed experimentally, while not requiring a fixed generator underneath.

Résumé non disponible / The race to computing power increases every day in the simulation community. A few years ago, scientists have started to harness the computing power of Graphics Processing Units (GPUs) to parallelize their simulations. As with any parallel architecture, not only the simulation model implementation has to be ported to the new parallel platform, but all the tools must be reimplemented as well. In the particular case of stochastic simulations, one of the major element of the implementation is the pseudorandom numbers source. Employing pseudorandom numbers in parallel applications is not a straightforward task, and it has to be done with caution in order not to introduce biases in the results of the simulation. This problematic has been studied since parallel architectures are available and is called pseudorandom stream distribution. While the literature is full of solutions to handle pseudorandom stream distribution on CPU-based parallel platforms, the young GPU programming community cannot display the same experience yet.In this thesis, we study how to correctly distribute pseudorandom streams on GPU. From the existing solutions, we identified a need for good software engineering solutions, coupled to sound theoretical choices in the implementation. We propose a set of guidelines to follow when a PRNG has to be ported to GPU, and put these advice into practice in a software library called ShoveRand. This library is used in a stochastic Polymer Folding model that we have implemented in C++/CUDA. Pseudorandom streams distribution on manycore architectures is also one of our concerns. It resulted in a contribution named TaskLocalRandom, which targets parallel Java applications using pseudorandom numbers and task frameworks.Eventually, we share a reflection on the methods to choose the right parallel platform for a given application. In this way, we propose to automatically build prototypes of the parallel application running on a wide set of architectures. This approach relies on existing software engineering tools from the Java and Scala community, most of them generating OpenCL source code from a high-level abstraction layer.

Nous présentons deux contributions dans le domaine de la programmation parallèle. La première est théorique : nous introduisons l’analyse SIPS, une approche nouvelle pour dénombrer le nombre d’opérations de synchronisation durant l’exécution d’un algorithme parallèle ordonnancé par vol de travail. Basée sur le concept d’horloges logiques, elle nous permet : d’une part de donner de nouvelles majorations de coût en moyenne; d’autre part de concevoir des programmes parallèles plus efficaces par adaptation dynamique de la granularité. La seconde contribution est pragmatique : nous présentons une parallélisation générique d’algorithmes pour la génération déterministe de nombres pseudo-aléatoires, indépendamment du nombre de processus concurrents lors de l’exécution. Alternative à l’utilisation d’un générateur pseudo-aléatoire séquentiel par processus, nous introduisons une API générique, appelée Par-R qui est conçue et analysée grâce à SIPS. Sa caractéristique principale est d’exploiter un générateur séquentiel qui peut “sauter” directement d’un nombre à un autre situé à une distance arbitraire dans la séquence pseudo-aléatoire. Grâce à l’analyse SIPS, nous montrons qu’en moyenne, lors d’une exécution par vol de travail d’un programme très parallèle (dont la profondeur ou chemin critique est très petite devant le travail ou nombre d’opérations), ces opérations de saut sont rares. Par-R est comparé au générateur pseudo-aléatoire DotMix écrit pour Cilk Plus, une extension de C/C++ pour la programmation parallèle par vol de travail. Le surcout théorique de Par-R se compare favorablement au surcoput de DotMix, ce qui apparait aussi expériemntalement. De plus, étant générique, Par-R est indépendant du générateur séquentiel sous-jacent. / Nós apresentamos duas contribuições para a área de programação paralela. A primeira contribuição é teórica: nós introduzimos a análise SIPS, uma nova abordagem para a estimar o número de sincronizações realizadas durante a execução de um algoritmo paralelo. SIPS generaliza o conceito de relógios lógicos para contar o número de sincronizações realizadas por um algoritmo paralelo e é capaz de calcular limites do pior caso mesmo na presença de execuções paralelas não-determinísticas, as quais não são geralmente cobertas por análises no estado-da-arte. Nossa análise nos permite estimar novos limites de pior caso para computações escalonadas pelo popular algoritmo de roubo de tarefas e também projetar programas paralelos e adaptáveis que são mais eficientes. A segunda contribuição é pragmática: nós apresentamos uma estratégia de paralelização eficiente para a geração de números pseudoaleatórios. Como uma alternativa para implementações fixas de componentes de geração aleatória nós introduzimos uma API chamada Par-R, projetada e analisada utilizando-se SIPS. Sua principal idea é o uso da capacidade de um gerador sequencial R de realizar um “pulo” eficiente dentro do fluxo de números gerados; nós os associamos a operações realizadas pelo escalonador por roubo de tarefas, o qual nossa análise baseada em SIPS demonstra ocorrer raramente em média. Par-R é comparado com o gerador paralelo de números pseudoaleatórios DotMix, escrito para a plataforma de multithreading dinâmico Cilk Plus. A latência de Par-R tem comparação favorável à latência do DotMix, o que é confirmado experimentalmente, mas não requer o uso subjacente fixado de um dado gerador aleatório. / We present two contributions to the field of parallel programming. The first contribution is theoretical: we introduce SIPS analysis, a novel approach to estimate the number of synchronizations performed during the execution of a parallel algorithm. Based on the concept of logical clocks, it allows us: on one hand, to deliver new bounds for the number of synchronizations, in expectation; on the other hand, to design more efficient parallel programs by dynamic adaptation of the granularity. The second contribution is pragmatic: we present an efficient parallelization strategy for pseudorandom number generation, independent of the number of concurrent processes participating in a computation. As an alternative to the use of one sequential generator per process, we introduce a generic API called Par-R, which is designed and analyzed using SIPS. Its main characteristic is the use of a sequential generator that can perform a “jump-ahead” directly from one number to another on an arbitrary distance within the pseudorandom sequence. Thanks to SIPS, we show that, in expectation, within an execution scheduled by work stealing of a “very parallel” program (whose depth or critical path is subtle when compared to the work or number of operations), these operations are rare. Par-R is compared with the parallel pseudorandom number generator DotMix, written for the Cilk Plus dynamic multithreading platform. The theoretical overhead of Par-R compares favorably to DotMix’s overhead, what is confirmed experimentally, while not requiring a fixed generator underneath.

Nous présentons deux contributions dans le domaine de la programmation parallèle. La première est théorique : nous introduisons l’analyse SIPS, une approche nouvelle pour dénombrer le nombre d’opérations de synchronisation durant l’exécution d’un algorithme parallèle ordonnancé par vol de travail. Basée sur le concept d’horloges logiques, elle nous permet : d’une part de donner de nouvelles majorations de coût en moyenne; d’autre part de concevoir des programmes parallèles plus efficaces par adaptation dynamique de la granularité. La seconde contribution est pragmatique : nous présentons une parallélisation générique d’algorithmes pour la génération déterministe de nombres pseudo-aléatoires, indépendamment du nombre de processus concurrents lors de l’exécution. Alternative à l’utilisation d’un générateur pseudo-aléatoire séquentiel par processus, nous introduisons une API générique, appelée Par-R qui est conçue et analysée grâce à SIPS. Sa caractéristique principale est d’exploiter un générateur séquentiel qui peut “sauter” directement d’un nombre à un autre situé à une distance arbitraire dans la séquence pseudo-aléatoire. Grâce à l’analyse SIPS, nous montrons qu’en moyenne, lors d’une exécution par vol de travail d’un programme très parallèle (dont la profondeur ou chemin critique est très petite devant le travail ou nombre d’opérations), ces opérations de saut sont rares. Par-R est comparé au générateur pseudo-aléatoire DotMix écrit pour Cilk Plus, une extension de C/C++ pour la programmation parallèle par vol de travail. Le surcout théorique de Par-R se compare favorablement au surcoput de DotMix, ce qui apparait aussi expériemntalement. De plus, étant générique, Par-R est indépendant du générateur séquentiel sous-jacent. / Nós apresentamos duas contribuições para a área de programação paralela. A primeira contribuição é teórica: nós introduzimos a análise SIPS, uma nova abordagem para a estimar o número de sincronizações realizadas durante a execução de um algoritmo paralelo. SIPS generaliza o conceito de relógios lógicos para contar o número de sincronizações realizadas por um algoritmo paralelo e é capaz de calcular limites do pior caso mesmo na presença de execuções paralelas não-determinísticas, as quais não são geralmente cobertas por análises no estado-da-arte. Nossa análise nos permite estimar novos limites de pior caso para computações escalonadas pelo popular algoritmo de roubo de tarefas e também projetar programas paralelos e adaptáveis que são mais eficientes. A segunda contribuição é pragmática: nós apresentamos uma estratégia de paralelização eficiente para a geração de números pseudoaleatórios. Como uma alternativa para implementações fixas de componentes de geração aleatória nós introduzimos uma API chamada Par-R, projetada e analisada utilizando-se SIPS. Sua principal idea é o uso da capacidade de um gerador sequencial R de realizar um “pulo” eficiente dentro do fluxo de números gerados; nós os associamos a operações realizadas pelo escalonador por roubo de tarefas, o qual nossa análise baseada em SIPS demonstra ocorrer raramente em média. Par-R é comparado com o gerador paralelo de números pseudoaleatórios DotMix, escrito para a plataforma de multithreading dinâmico Cilk Plus. A latência de Par-R tem comparação favorável à latência do DotMix, o que é confirmado experimentalmente, mas não requer o uso subjacente fixado de um dado gerador aleatório. / We present two contributions to the field of parallel programming. The first contribution is theoretical: we introduce SIPS analysis, a novel approach to estimate the number of synchronizations performed during the execution of a parallel algorithm. Based on the concept of logical clocks, it allows us: on one hand, to deliver new bounds for the number of synchronizations, in expectation; on the other hand, to design more efficient parallel programs by dynamic adaptation of the granularity. The second contribution is pragmatic: we present an efficient parallelization strategy for pseudorandom number generation, independent of the number of concurrent processes participating in a computation. As an alternative to the use of one sequential generator per process, we introduce a generic API called Par-R, which is designed and analyzed using SIPS. Its main characteristic is the use of a sequential generator that can perform a “jump-ahead” directly from one number to another on an arbitrary distance within the pseudorandom sequence. Thanks to SIPS, we show that, in expectation, within an execution scheduled by work stealing of a “very parallel” program (whose depth or critical path is subtle when compared to the work or number of operations), these operations are rare. Par-R is compared with the parallel pseudorandom number generator DotMix, written for the Cilk Plus dynamic multithreading platform. The theoretical overhead of Par-R compares favorably to DotMix’s overhead, what is confirmed experimentally, while not requiring a fixed generator underneath.

Sofisticadas técnicas para estimação de modelos baseadas em simulação, os filtros de partículas ou métodos de Monte Carlo Seqüenciais, foram empregadas recentemente para solucionar diversos problemas difícieis no campo da robótica móvel. No entanto, o sucesso dos fitros de partículas limitou-se à computação de parâmetros em espaços de baixa dimensionalidade. Os atuais esforços de pesquisa em robótica móvel têm comecado a explorar certas propriedades estruturais de seus domnios de aplicação que envolvem a utilização de filtros de partculas em espacos de maior dimensão, aumentando consideravelmente a complexidade da simulação envolvida. Simulações estatsticas dessa natureza requerem uma grande quantidade de numeros pseudo-aleatorios que possam ser gerados eficientemente e atendam a certos criterios de qualidade. O processo de geração de numeros pseudo-aleatorios torna-se o ponto crtico de tais aplicações em termos de desempenho. Neste contexto, a computação reconguravel insere-se como uma tecnologia capaz de satisfazer a demanda por alto desempenho das grandes simulações estatsticas pois sistemas baseados em arquiteturas reconguraveis possuem o potencial de mapear computação em hardware visando aumento de eficiência sem comprometer seriamente sua exibilidade. Tecnologias reconguraveis também possui o atrativo de um baixo consumo de energia, uma caracterstica essencial para os futuros robôs moveis embarcados. Esta dissertação apresenta a implementação um sistema embarcado baseado em FPGA e projetado para solucionar o problema de localização de robôs por meio de tecnicas probabilsticas. A parte fundamental de todo este sistema e um veloz gerador de numeros aleatorios mapeado ao hardware reconguravel que foi capaz de atender rígidos criterios estatsticos de qualidade / Sophisticated techniques for estimation of models based on simulation, particle filters or Sequential Monte Carlo Methods, were recently used to solve many difficult problems in the field of mobile robotics. However, the success of particle filters was limited to the computation of parameters in low dimensionality spaces. The current research efforts in mobile robotics have begun to explore some structural properties of their application\'s domain involving the use of particle filters in spaces of a higher dimension, greatly increasing the complexity of the involved simulation. Statistical simulations of this nature require a lot of pseudorandom numbers that can be generated efficiently and meet certain quality criteria. The process of generating pseudorandom number becomes the critical point of such applications in terms of performance. In this context, reconfigurable computing is a technology capable of meeting the demand for high performance of large statistical simulations because systems based on reconfigurable architectures have the potential to map computation to hardware aiming to increase eficiency without a serious drawback in exibility. Reconfigurable technologies are also attractive because of their low energy consume, a essential feature for the future mobile robots. This dissertation presents an implementation of a FPGA based embedded system designed to solve the robot localization problem by the means of probabilistic technics. The fundamental part from the whole system is a fast random number generator mapped to reconfigurable hardware wich atends a rigid quality criteria

La cryptographie a été un facteur clé pour permettre la vente de services et du commerce par Internet. Le cloud computing a amplifié cette révolution et est devenu un service très demandé grâce à ses avantages comme : puissance de calcul importante, services à bas coûts, rendement, évolutivité, accessibilité et disponibilité. Parallèlement à la hausse de nouveaux business, des protocoles pour des calculs sécurisés ont aussi émergé. Le but de cette thèse est de contribuer à la sécurité des protocoles d’Internet existants en fournissant une analyse de la source aléatoire de ces protocoles et en introduisant des protocoles mieux adaptés pour les environnements des cloud computing. Nous proposons de nouvelles constructions en améliorant l'efficacité des solutions actuelles afin de les rendre plus accessibles et pratiques. Nous fournissons une analyse de sécurité détaillée pour chaque schéma avec des hypothèses raisonnables. Nous étudions la sécurité du cloud computing à différents niveaux. D'une part, nous formalisons un cadre pour analyser quelques-uns des générateurs de nombres pseudo-aléatoires populaires à ce jour qui sont utilisés dans presque chaque application cryptographique. D'autre part, nous proposons deux approches efficaces pour des calculs en cloud. Le premier permet à un utilisateur de partager publiquement son secret de haute entropie avec des serveurs différents pour plus tard le récupérer par interaction avec certains de ces serveurs en utilisant seulement son mot de passe et sans données authentifiées. Le second permet à un client d'externaliser à un serveur une base de données en toute sécurité, qui peut être recherchée et modifiée ultérieurement. / Cryptography has been a key factor in enabling services and products trading over the Internet. Cloud computing has expanded this revolution and it has become a highly demanded service or utility due to the advantages of high computing power, cheap cost of services, high performance, scalability, accessibility as well as availability. Along with the rise of new businesses, protocols for secure computation have as well emerged. The goal of this thesis is to contribute in the direction of securing existing Internet protocols by providing an analysis of the sources of randomness of these protocols and to introduce better protocols for cloud computing environments. We propose new constructions, improving the efficiency of current solutions in order to make them more accessible and practical. We provide a detailed security analysis for each scheme under reasonable assumptions. We study the security in a cloud computing environment in different levels. On one hand, we formalize a framework to study some popular real-life pseudorandom number generators used in almost every cryptographic application. On the other, we propose two efficient applications for cloud computing. The first allows a user to publicly share its high-entropy secret across different servers and to later recover it by interacting with some of these servers using only his password without requiring any authenticated data. The second, allows a client to securely outsource to a server an encrypted database that can be searched and modified later.

This thesis deals with a method of spectrum-spreading of the data signals transmitted in the radio channel. There exist three different ways of spreading application, they uses pseudorandom sequences and also orthogonal sequences. In these systems we can find various kinds of modulations, one of them (Quadrature Phase Shift Keying) is shown at the end of the thesis. Spectrum spreading orthogonal multiplex OFDM is based on this method. The thesis wants to present the principle of the spectrum spreading method and the description of systems, transmitters and receivers that are using this method.