Throughput Performance of an Adaptive ARQ Scheme in Rayleigh Fading Channels

Using a simulation study we analyze the throughput performance of Yao’s adaptive ARQ scheme in time-varying channels. The simulation takes into account the Rayleigh amplitude and the fast or the slow fading characteristics of a wireless channel, under a representative M-FSK modulation and Reed-Solomon coding scheme. We show that, for a specific set of design parameters, Yao’s adaptive procedure works well for all channel fading rates, except for moderately slow rates. By observing variations of packet error rates at a specified SNR we provide an explanation for these varied behaviors under different channel fading rates

Studies on the performance of some ARQ schemes

This thesis consists of a summary part and seven published articles. All the articles are about performance analysis of ARQ schemes. Two of the publications study the performance of an ARQ scheme with packet combining, called the EARQ (extended ARQ) scheme. In the packet combining algorithm, the bitwise modulo-2 sum of two erroneous copies of a packet is computed to locate the errors. The packet combining algorithm involves a straightforward search procedure, the computational complexity of which easily becomes prohibitive. As a solution to this, a modified scheme is proposed, where the search procedure is attempted only when there are at most Nmax 1s at the output of the modulo-2 adder. In one article, time diversity was utilized, whereas space diversity reception was considered in the other work. The remaining five publications study the throughput performance of adaptive selective-repeat and go-back-N ARQ schemes, where the switching between the transmission modes is done based on the simple algorithm proposed by Y.-D. Yao in 1995. In this method, α contiguous NACKs or β contiguous ACKs indicate changes from 'good' to 'bad' or from 'bad' to 'good' channel conditions, respectively. The numbers α and β are the two design parameters of the adaptive scheme. The time-varying forward channel is modelled by two-state Markov chains, known as Gilbert-Elliott channel models. The states are characterized by bit error rates, packet error rates or fading parameters. The performance of the adaptive ARQ scheme is measured by its average throughput over all states of the system model, which is a Markov chain. A useful upper bound for the achievable average throughput is provided by the performance of an (assumed) ideal adaptive scheme which is always in the 'correct' transmission mode. The optimization of α and β is done based on minimizing the mean-square distance between the actual and the ideal performance curves. Methods of optimizing the packet size(s) used in the adaptive selective-repeat scheme are also proposed.reviewe

Theoretical Studies on Proteins to Reveal the Mechanism of Their Folding and Biological Functions

The folding mechanism of several β-structures (e.g., β-hairpins and β-sheets) was studied using newly developed enhanced sampling methods along with MD simulations in all implicit solvent environments. The influence of different implicit solvent models on the folding simulation of β-structure was also tested. Through the analysis of the free energy landscape as the function of several suitable reaction coordinates, we observed that the folding of β-hairpins is actually a two-state transition. In addition, the folding free energy landscapes for those related hairpins indicate the apparent sequence dependence, which demonstrates different folding mechanisms of similar β-structures of varied sequence. We also found that the stability of backbone hydrogen bonds is determined by the turn sequence and the composition of hydrophobic core cluster in β-structures. Neither of these findings was reported before. The processive movement of kinesin was also studied at the mesoscopic level. We developed a simple physical model to understand the asymmetric hand-over-hand mechanism of the kinesin walking on the microtubule. The hand-over-hand motion of the conventional kinesin is reproduced in our model and good agreement is achieved between calculated and experimental results. The experimentally observed limping of the truncated kinesin is also perfectly described by our model. The global conformational change of kinesin heads (e.g., the power stroke of neck-linkers which works as lever-arms during the kinesin walking, the transition between open and closed states of the switch region of the nucleotide binding domain in each head induced by the nucleotide binding and release) was studied for both dimeric and monomeric kinesins using a coarse-grained model, anisotropic network model (ANM). At the same time Langevin mode analysis was used to study the solvent influence on the motions of the kinesin head mimicked by ANM. Additionally, the correlation between the neck-linker and the nucleotide binding site was also studied for dimeric and monomeric kinesins. The former shows the apparent correlation between two subdomains whereas the latter does not, which may explain the experimental observation that only the dimeric kinesin is capable of walking processively on the microtubule

Analysis of Error Control and Congestion Control Protocols

This thesis presents an analysis of a class of error control and congestion control protocols used in computer networks. We address two kinds of packet errors: (a) independent errors and (b) congestion-dependent errors. Our performance measure is the expected time and the standard deviation of the time to transmit a large message, consisting of N packets. The analysis of error control protocols. Assuming independent packet errors gives an insight on how the error control protocols should really work if buffer overflows are minimal. Some pertinent results on the performance of go-back-n, selective repeat, blast with full retransmission on error (BFRE) and a variant of BFRE, the Optimal BFRE that we propose, are obtained. We then analyze error control protocols in the presence of congestion-dependent errors. We study the selective repeat and go-back-n protocols and find that irrespective of retransmission strategy, the expected time as well as the standard deviation of the time to transmit N packets increases sharply the face of heavy congestion. However, if the congestion level is low, the two retransmission strategies perform similarly. We conclude that congestion control is a far more important issue when errors are caused by congestion. We next study the performance of a queue with dynamically changing input rates that are based on implicit or explicit feedback. This is motivated by recent proposals for adaptive congestion control algorithms where the sender\u27s window size is adjusted based on perceived congestion level of a bottleneck node. We develop a Fokker-Planck approximation for a simplified system; yet it is powerful enough to answer the important questions regarding stability, convergence (or oscillations), fairness and the significant effect that delayed feedback plays on performance. Specifically, we find that, in the absence of feedback delay, a linear increase/exponential decrease rate control algorithm is provably stable and fair. Delayed feedback, however, introduces cyclic behavior. This last result not only concurs with some recent simulation studies, it also expounds quantitatively on the real causes behind them

Wavelet based image compression integrating error protection via arithmetic coding with forbidden symbol and map metric sequential decoding with ARQ retransmission

The phenomenal growth of digital multimedia applications has forced the communication

Advances in Spacecraft Attitude Control

Spacecraft attitude maneuvers comply with Euler's moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research. This book is meant for basic scientifically inclined readers, and commences with a chapter on the basics of spaceflight and leverages this remediation to reveal very advanced topics to new spaceflight enthusiasts. The topics learned from reading this text will prepare students and faculties to investigate interesting spaceflight problems in an era where cube satellites have made such investigations attainable by even small universities. It is the fondest hope of the editor and authors that readers enjoy this book

Active self-diagnosis in telecommunication networks

Les réseaux de télécommunications deviennent de plus en plus complexes, notamment de par la multiplicité des technologies mises en œuvre, leur couverture géographique grandissante, la croissance du trafic en quantité et en variété, mais aussi de par l évolution des services fournis par les opérateurs. Tout ceci contribue à rendre la gestion de ces réseaux de plus en plus lourde, complexe, génératrice d erreurs et donc coûteuse pour les opérateurs. On place derrière le terme réseaux autonome l ensemble des solutions visant à rendre la gestion de ce réseau plus autonome. L objectif de cette thèse est de contribuer à la réalisation de certaines fonctions autonomiques dans les réseaux de télécommunications. Nous proposons une stratégie pour automatiser la gestion des pannes tout en couvrant les différents segments du réseau et les services de bout en bout déployés au-dessus. Il s agit d une approche basée modèle qui adresse les deux difficultés du diagnostic basé modèle à savoir : a) la façon d'obtenir un tel modèle, adapté à un réseau donné à un moment donné, en particulier si l'on souhaite capturer plusieurs couches réseau et segments et b) comment raisonner sur un modèle potentiellement énorme, si l'on veut gérer un réseau national par exemple. Pour répondre à la première difficulté, nous proposons un nouveau concept : l auto-modélisation qui consiste d abord à construire les différentes familles de modèles génériques, puis à identifier à la volée les instances de ces modèles qui sont déployées dans le réseau géré. La seconde difficulté est adressée grâce à un moteur d auto-diagnostic actif, basé sur le formalisme des réseaux Bayésiens et qui consiste à raisonner sur un fragment du modèle du réseau qui est augmenté progressivement en utilisant la capacité d auto-modélisation: des observations sont collectées et des tests réalisés jusqu à ce que les fautes soient localisées avec une certitude suffisante. Cette approche de diagnostic actif a été expérimentée pour réaliser une gestion multi-couches et multi-segments des alarmes dans un réseau IMS.While modern networks and services are continuously growing in scale, complexity and heterogeneity, the management of such systems is reaching the limits of human capabilities. Technically and economically, more automation of the classical management tasks is needed. This has triggered a significant research effort, gathered under the terms self-management and autonomic networking. The aim of this thesis is to contribute to the realization of some self-management properties in telecommunication networks. We propose an approach to automatize the management of faults, covering the different segments of a network, and the end-to-end services deployed over them. This is a model-based approach addressing the two weaknesses of model-based diagnosis namely: a) how to derive such a model, suited to a given network at a given time, in particular if one wishes to capture several network layers and segments and b) how to reason a potentially huge model, if one wishes to manage a nation-wide network for example. To address the first point, we propose a new concept called self-modeling that formulates off-line generic patterns of the model, and identifies on-line the instances of these patterns that are deployed in the managed network. The second point is addressed by an active self-diagnosis engine, based on a Bayesian network formalism, that consists in reasoning on a progressively growing fragment of the network model, relying on the self-modeling ability: more observations are collected and new tests are performed until the faults are localized with sufficient confidence. This active diagnosis approach has been experimented to perform cross-layer and cross-segment alarm management on an IMS network.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

Advances in Spacecraft Attitude Control

Spacecraft attitude maneuvers comply with Euler's moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research. This book is meant for basic scientifically inclined readers, and commences with a chapter on the basics of spaceflight and leverages this remediation to reveal very advanced topics to new spaceflight enthusiasts. The topics learned from reading this text will prepare students and faculties to investigate interesting spaceflight problems in an era where cube satellites have made such investigations attainable by even small universities. It is the fondest hope of the editor and authors that readers enjoy this book

Stochastic and physical modeling of fundamental biological processes

Modeling is a necessary tool to understand the large volumes of data generated from quantitative experiments on biological systems. It combines our knowledge of a phenomenon into a succinct mathematical or computational description. In this dissertation, we first describe briefly two applications of modeling in biophysics: loading of the replication clamp into the replisome in the archaeon Methanosarcina acetivorans and genome packing initiation during the self-assembly of the T4 bacteriophage. We then describe in detail two systems: an improved model of the lac genetic switch which includes DNA looping in its gene regulation mechanism, and a spatially resolved, whole-cell model of ribosome biogenesis in Escherichia coli, which we then extend to include cell growth and replication of its genome. For the first system, conditions and parameters affecting the range of bistability of the lac genetic switch in E. coli are examined for a model which includes DNA looping interactions with the lac repressor and a lactose analog. This stochastic gene-mRNA-protein model of the lac switch describes DNA looping using a third transcriptional state. We exploit the fast bursting dynamics of mRNA by combining a novel geometric burst approximation with the Finite State Projection method. This limits the number of protein/mRNA states, allowing for an accelerated search of the model's parameter space. We evaluate how the addition of the third transcriptional state changes the bistability properties of the model and find a critical region of parameter space where the phenotypic switching occurs in a range seen in single molecule fluorescence studies. Stochastic simulations show induction in the looping model is preceded by a rare complete dissociation of the loop followed by an immediate burst of mRNA rather than a slower build up of mRNA as in the two-state model. The overall effect of the looped state is to allow for faster switching times while at the same time further differentiating the uninduced and induced phenotypes. Furthermore, the kinetic parameters are consistent with free energies derived from thermodynamic studies suggesting that this minimal model of DNA looping could have a broader range of application. For the second system, we study the biogenesis of the ribosome. Central to all life is the assembly of the ribosome: a coordinated process involving the hierarchical association of ribosomal protein to the RNAs forming the small and large ribosomal subunits. The process is further complicated by effects arising from the intracellular heterogeneous environment and the location of ribosomal operons within the cell. We provide a simplified model of ribosome biogenesis in slow growing E. coli. Kinetic models of in vitro small subunit reconstitution at the level of individual ribosomal protein to ribosomal RNA interactions are developed for two temperature regimes. The model at low temperatures predicts the existence of a novel 5’-3’-central assembly pathway, which we investigate further using molecular dynamics. The high temperature assembly network is incorporated into a model of in vivo ribosome biogenesis in slow growing E. coli. The model, described in terms of reaction-diffusion master equations, contains 1336 reactions and 251 species that dynamically couple transcription and translation to ribosome assembly. We use the Lattice Microbes software package to simulate the stochastic production of mRNA, proteins, and ribosome intermediates over a full cell cycle of 120 minutes. The whole-cell model captures the correct growth rate of ribosomes, predicts the localization of early assembly intermediates to the nucleoid region, and reproduces the known assembly timescales for the small subunit with no modifications made to the embedded in vitro assembly network. Finally, we extend the spatially resolved whole-cell model of ribosome biogenesis to include the effects of growth, DNA replication, and cell division. All biological processes are described in terms of reaction-diffusion master equations and solved stochastically using Lattice Microbes. In order to determine the replication parameters, we construct and analyze a series of E. coli strains with fluorescently labeled genes distributed evenly throughout their chromosomes. By measuring these cells' lengths and number of gene copies at the single-cell level, we could fit a statistical model of the initiation and duration of chromosome replication. We found that for our slow-growing (120 minute doubling time) E. coli cells, replication was initiated 42 minutes into the cell cycle and completed after an additional 42 minutes. While simulations of the biogenesis model produce the correct ribosome and mRNA counts over the cell cycle, the kinetic parameters for transcription and degradation are lower than anticipated from a recent analytical time dependent model of in vivo mRNA production. Describing expression in terms of a simple chemical master equation, we show that the discrepancies are due to the lack of non-ribosomal genes in the extended biogenesis model which effects the competition of mRNA for ribosome binding, and suggest corrections to parameters to be used in the whole-cell model when modeling expression of the entire transcriptome