A comprehensive survey on hybrid communication in context of molecular communication and terahertz communication for body-centric nanonetworks

With the huge advancement of nanotechnology over the past years, the devices are shrinking into micro-scale, even nano-scale. Additionally, the Internet of nano-things (IoNTs) are generally regarded as the ultimate formation of the current sensor networks and the development of nanonetworks would be of great help to its fulfilment, which would be ubiquitous with numerous applications in all domains of life. However, the communication between the devices in such nanonetworks is still an open problem. Body-centric nanonetworks are believed to play an essential role in the practical application of IoNTs. BCNNs are also considered as domain specific like wireless sensor networks and always deployed on purpose to support a particular application. In these networks, electromagnetic and molecular communications are widely considered as two main promising paradigms and both follow their own development process. In this survey, the recent developments of these two paradigms are first illustrated in the aspects of applications, network structures, modulation techniques, coding techniques and security to then investigate the potential of hybrid communication paradigms. Meanwhile, the enabling technologies have been presented to apprehend the state-of-art with the discussion on the possibility of the hybrid technologies. Additionally, the inter-connectivity of electromagnetic and molecular body-centric nanonetworks is discussed. Afterwards, the related security issues of the proposed networks are discussed. Finally, the challenges and open research directions are presented

Molecular communications techniques for the internet of bio-nano things

The ”Internet of Bio-Nano Things” (IoBNT) is a new networking paradigm defined as the interconnection of nanoscale devices. IoBNT is a revolutionizing concept that will likely enable a wide range of applications, in particular, it is envisioned that healthcare systems will be transformed with the development and integration of body-centric networks into future generations of communication systems. Within this context, molecular communications (MC) emerge as the most promising way of transmitting information for in-body communications, due to being inherently biocompatible, energy-efficient, and robust in physiological conditions. One of the biggest challenges is how to minimize the effects of environmental noise and reduce intersymbol interference (ISI) which can be very high in an MC via diffusion scenario. Analogous to traditional communications, channel coding is one of the most promising types of techniques for addressing this problem. This work is based on the study and evaluation of novel energy efficient and low complexity coding, modulation and detection schemes for MC. With a special focus on the implementation of Tomlinson, Cercas, Hughes (TCH) codes as a new attractive approach for the MC environment, due to the particular codeword properties which enable simplified detection. Simulation results show that TCH codes are more effective for these scenarios when compared to other existing alternatives, without introducing too much complexity or processing power into the system. Furthermore, an experimental macroscale proof-of-concept is described, which uses pH as the information carrier and demonstrates that the proposed TCH codes can improve the reliability in this type of communication channel.A ”Internet das Coisas” Bio-Nano é um novo paradigma de rede definido como a interconexão de dispositivos nano escala. Este é um conceito revolucionário que espectavelmente permitirá uma vasta gama de aplicações. Em particular, prevê-se que os sistemas de saúde sejam transformados com a integração de redes centradas no corpo, em futuras gerações de sistemas de comunicação. Neste contexto, as comunicações moleculares (CM) emergem como a forma mais promissora de transmitir informação, devido ao facto de serem intrinsecamente biocompatíveis, eficientes em termos energéticos e robustos em condições fisiológicas. Um dos maiores desafios é como minimizar os efeitos do ruído ambiental e reduzir a interferência intersimbólica que pode ser muito elevada num cenário de CM por difusão. A codificação de canal é um dos tipos de técnicas mais promissoras para abordar este problema. Este trabalho baseia-se na avaliação da modulação, da deteção e de novos esquemas de codificação energeticamente eficientes e de baixa complexidade aplicados em CM. Com especial foco, na implementação de códigos Tomlinson, Cercas, Hughes (TCH) como uma nova abordagem para um ambiente de CM, devido às suas particulares propriedades das palavras de código, que permitem uma deteção simplificada. Os resultados das simulações mostram que os códigos TCH são mais eficazes para estes cenários quando comparados com outras alternativas existentes, sem introduzir demasiada complexidade ou poder de processamento no sistema. Adicionalmente, é descrita uma experiência macroscópica, que utiliza o pH como portador de informação, demonstrando que os códigos TCH propostos podem melhorar a fiabilidade para CM

Random Matrix Theories in Quantum Physics: Common Concepts

We review the development of random-matrix theory (RMT) during the last decade. We emphasize both the theoretical aspects, and the application of the theory to a number of fields. These comprise chaotic and disordered systems, the localization problem, many-body quantum systems, the Calogero-Sutherland model, chiral symmetry breaking in QCD, and quantum gravity in two dimensions. The review is preceded by a brief historical survey of the developments of RMT and of localization theory since their inception. We emphasize the concepts common to the above-mentioned fields as well as the great diversity of RMT. In view of the universality of RMT, we suggest that the current development signals the emergence of a new "statistical mechanics": Stochasticity and general symmetry requirements lead to universal laws not based on dynamical principles.Comment: 178 pages, Revtex, 45 figures, submitted to Physics Report

Conception et évaluation de nouvelles méthodes pour améliorer les performances des réseaux de nano-communication

Abstract : The field of nanotechnology has undergone very rapid and fascinating development in recent years. This rapid and impressive advance has led to new applications of nanotechnology in the biomedical and military industries, making it a key area of research in multidisciplinary fields. However, the individual processing capacity of nanodevices is very limited, hence the need to design nanonetworks that allow the nanodevices to share information and to cooperate with each other. There are two solutions to establish a nanocommunication system: either by adapting the classical electromagnetic communication to the requirements of nano scale, or by using biological nanosystems inspired by nature such as the molecular communication proposed in the literature. In this thesis, we are interested in the second solution, which is exploiting the potential of biological nanosystems used by nature since billions of years to design biocompatible nanonetworks that can be used inside the human body for medical applications. Nevertheless, the use of this new paradigm is not without challenges. The very low achievable throughput and the Inter-Symbol Interference (ISI) are the most influential problems on the quality of molecular communication. The main objective of this thesis is to design and evaluate new methods inspired by nature in order to enhance the performance of nano-communication systems. To do this, the work is divided into three main parts. In the first part, we enhance the performance of molecular communication by proposing a new method that uses a photolysis-reaction instead of using enzyme to better attenuate ISI. We also propose an optimization of the receiver used in MIMO systems by judiciously choosing the parameters used in its design to reduce the influence of path loss on the quality of the system. The second part proposes a new wired nano-communication system based on self-assembled polymers that build an electrically conductive nanowire to connect the nanodevices to each other. The use of electrons as information carriers drastically increases the achievable throughput and reduces the delay. We study the dynamic process of self-assembly of the nanowire and we propose a bio-inspired receiver that detects the electrons sent through the conductive nanowire and converts them into a blue light. The third part applies the proposed wired nano-communication system to design an architecture ofWired Ad hoc NanoNETworks (WANNET) with a physical layer, Medium Acess Control (MAC) layer and application layer. We also calculate the maximum throughput and we evaluate the performance of the system.Le domaine des nanotechnologies a connu un développement très rapide et fascinant ces dernières années. Cette avancée rapide et impressionnante a conduit à de nouvelles applications dans les industries biomédicale et militaire, ce qui en fait un champ clé de recherche dans des domaines multidisciplinaires. Cependant, la capacité de traitement individuelle des nanodispositifs est très limitée, d'où la nécessité de concevoir des nanoréseaux qui permettent aux nanodispositifs de partager des informations et de coopérer entre eux. Il existe deux solutions pour mettre en place un système de nano-communication: soit en adaptant la communication électromagnétique classiques aux exigences de la nano échelle, soit en utilisant des nanosystèmes inspirés de la nature comme la communication moléculaire. Dans cette thèse, nous nous intéressons à la deuxième solution, qui exploite le potentiel des nanosystèmes biologiques utilisés par la nature depuis des milliards d'années pour concevoir des nanoréseaux biocompatibles pouvant être utilisés à l'intérieur du corps humain pour des applications médicales. Néanmoins, l'utilisation de ce nouveau paradigme n'est pas sans défis. Le très faible débit réalisable et l'Interférence Entre Symboles (IES) sont les problèmes les plus influents sur la qualité de la communication moléculaire. L'objectif principal de cette thèse est de concevoir et d'évaluer de nouvelles méthodes inspirées de la nature afin d'améliorer les performances des systèmes de nano-communication. Pour ce faire, le travail est divisé en trois parties principales. Dans la première partie, nous améliorons les performances de la communication moléculaire en proposant une nouvelle méthode qui utilise une réaction de photolyse pour mieux atténuer l'IES. Nous proposons également une optimisation du receveur utilisé dans les systèmes MIMO en choisissant judicieusement les paramètres utilisés dans sa conception pour réduire l'influence de l'atténuation de trajet sur la qualité du système. La deuxième partie propose un nouveau système de nano-communication filaire basé sur des polymères auto-assemblés qui construisent un nanofil électriquement conducteur pour connecter les nanodispositifs les uns aux autres. L'utilisation d'électrons comme supports d'informations augmente considérablement le débit réalisable et réduit le délai. Nous étudions le processus dynamique d'auto-assemblage du nanofil et nous proposons un receveur bio-inspiré qui détecte les électrons envoyés et les convertit en une lumière bleue. La troisième partie applique le système de nano-communication filaire proposé pour concevoir une architecture d'un nanoréseau ad hoc filaire (Wired Ad hoc NanoNETworks) WANNET avec une couche physique, une couche de contrôle d'accès moyen (Medium Access Control) MAC et une couche d'application. Nous calculons également le débit maximum et nous évaluons les performances du système

Designing a scalable dynamic load -balancing algorithm for pipelined single program multiple data applications on a non-dedicated heterogeneous network of workstations

Dynamic load balancing strategies have been shown to be the most critical part of an efficient implementation of various applications on large distributed computing systems. The need for dynamic load balancing strategies increases when the underlying hardware is a non-dedicated heterogeneous network of workstations (HNOW). This research focuses on the single program multiple data (SPMD) programming model as it has been extensively used in parallel programming for its simplicity and scalability in terms of computational power and memory size.;This dissertation formally defines and addresses the problem of designing a scalable dynamic load-balancing algorithm for pipelined SPMD applications on non-dedicated HNOW. During this process, the HNOW parameters, SPMD application characteristics, and load-balancing performance parameters are identified.;The dissertation presents a taxonomy that categorizes general load balancing algorithms and a methodology that facilitates creating new algorithms that can harness the HNOW computing power and still preserve the scalability of the SPMD application.;The dissertation devises a new algorithm, DLAH (Dynamic Load-balancing Algorithm for HNOW). DLAH is based on a modified diffusion technique, which incorporates the HNOW parameters. Analytical performance bound for the worst-case scenario of the diffusion technique has been derived.;The dissertation develops and utilizes an HNOW simulation model to conduct extensive simulations. These simulations were used to validate DLAH and compare its performance to related dynamic algorithms. The simulations results show that DLAH algorithm is scalable and performs well for both homogeneous and heterogeneous networks. Detailed sensitivity analysis was conducted to study the effects of key parameters on performance

Continuous attractor working memory and provenance of channel models

The brain is a complex biological system composed of a multitude of microscopic processes, which together give rise to computational abilities observed in everyday behavior. Neuronal modeling, consisting of models of single neurons and neuronal networks at varying levels of biological detail, can synthesize the gaps currently hard to constrain in experiments and provide mechanistic explanations of how these computations might arise. In this thesis, I present two parallel lines of research on neuronal modeling, situated at varying levels of biological detail. First, I assess the provenance of voltage-gated ion channel models in an integrative meta-analysis that investigates a backlog of nearly 50 years of published research. To cope with the ever-increasing volume of research produced in the field of neuroscience, we need to develop methods for the systematic assessment and comparison of published work. As we demonstrate, neuronal models offer the intriguing possibility of performing automated quantitative analyses across studies, by standardized simulated experiments. We developed protocols for the quantitative comparison of voltage-gated ion channels, and applied them to a large body of published models, allowing us to assess the variety and temporal development of different models for the same ion channels over the time scale of years of research. Beyond a systematic classification of the existing body of research made available in an online platform, we show that our approach extends to large-scale comparisons of ion channel models to experimental data, thereby facilitating field-wide standardization of experimentally-constrained modeling. Second, I investigate neuronal models of working memory (WM). How can cortical networks bridge the short time scales of their microscopic components, which operate on the order of milliseconds, to the behaviorally relevant time scales of seconds observed in WM experiments? I consider here a candidate model: continuous attractor networks. These can implement WM for a continuum of possible spatial locations over several seconds and have been proposed for the organization of prefrontal cortical networks. I first present a novel method for the efficient prediction of the network-wide steady states from the underlying microscopic network properties. The method can be applied to predict and tune the "bump" shapes of continuous attractors implemented in networks of spiking neuron models connected by nonlinear synapses, which we demonstrate for saturating synapses involving NMDA receptors. In a second part, I investigate the computational role of short-term synaptic plasticity as a synaptic nonlinearity. Continuous attractor models are sensitive to the inevitable variability of biological neurons: variable neuronal firing and heterogeneous networks decrease the time that memories are accurately retained, eventually leading to a loss of memory functionality on behaviorally relevant time scales. In theory and simulations, I show that short-term plasticity can control the time scale of memory retention, with facilitation and depression playing antagonistic roles in controlling the drift and diffusion of locations in memory. Finally, we place quantitative constraints on the combination of synaptic and network parameters under which continuous attractors networks can implement reliable WM in cortical settings

Polarization and Spatial Coupling:Two Techniques to Boost Performance

During the last two decades we have witnessed considerable activity in building bridges between the fields of information theory/communications, computer science, and statistical physics. This is due to the realization that many fundamental concepts and notions in these fields are in fact related and that each field can benefit from the insight and techniques developed in the others. For instance, the notion of channel capacity in information theory, threshold phenomena in computer science, and phase transitions in statistical physics are all expressions of the same concept. Therefore, it would be beneficial to develop a common framework that unifies these notions and that could help to leverage knowledge in one field to make progress in the others. A particularly striking example is the celebrated belief propagation algorithm. It was independently invented in each of these fields but for very different purposes. The realization of the commonality has benefited each of the areas. We investigate polarization and spatial coupling: two techniques that were originally invented in the context of channel coding (communications) thus resulting for the first time in efficient capacity-achieving codes for a wide range of channels. As we will discuss, both techniques play a fundamental role also in computer science and statistical physics and so these two techniques can be seen as further fundamental building blocks that unite all three areas. We demonstrate applications of these techniques, as well as the fundamental phenomena they provide. In more detail, this thesis consists of two parts. In the first part, we consider the technique of polarization and its resultant class of channel codes, called polar codes. Our main focus is the analysis and improvement of the behavior of polarization towards the most significant aspects of modern channel-coding theory: scaling laws, universality, and complexity (quantization). For each of these aspects, we derive fundamental laws that govern the behavior of polarization and polar codes. Even though we concentrate on applications in communications, the analysis that we provide is general and can be carried over to applications of polarization in computer science and statistical physics. As we will show, our investigations confirm some of the inherent strengths of polar codes such as their robustness with respect to quantization. But they also make clear in which aspects further improvement of polar codes is needed. For example, we will explain that the scaling behavior of polar codes is quite slow compared to the optimal one. Hence, further research is required in order to enhance the scaling behavior of polar codes towards optimality. In the second part of this thesis, we investigate spatial coupling. By now, there exists already a considerable literature on spatial coupling in the realm of information theory and communications. We therefore investigate mainly the impact of spatial coupling on the fields of statistical physics and computer science. We consider two well-known models. The first is the Curie-Weiss model that provides us with the simplest model for understanding the mechanism of spatial coupling in the perspective of statistical physics. Many fundamental features of spatial coupling can be simply explained here. In particular, we will show how the well-known Maxwell construction in statistical physics manifests itself through spatial coupling. We then focus on a much richer class of graphical models called constraint satisfaction problems (CSP) (e.g., K-SAT and Q-COL). These models are central to computer science. We follow a general framework: First, we introduce interpolation procedures for proving that the coupled and standard (un-coupled) models are fundamentally related, in that their static properties (such as their SAT/UNSAT threshold) are the same. We then use tools from spin glass theory (cavity method) to demonstrate the so-called phenomenon of threshold saturation in these coupled models. Finally, we present the algorithmic implications and argue that all these features provide a new avenue for obtaining better, provable, algorithmic lower bounds on static thresholds of the individual standard CSP models. We consider simple decimation algorithms (e.g., the unit clause propagation algorithm) for the coupled CSP models and provide a machinery to analyze these algorithms. These analyses enable us to observe that the algorithmic thresholds on the coupled model are significantly improved over the standard model. For some models (e.g., 3-SAT, 3-COL), these coupled algorithmic thresholds surpass the best lower bounds on the SAT/UNSAT threshold in the literature and provide us with a new lower bound. We conclude by pointing out that although we only considered some specific graphical models, our results are of general nature hence applicable to a broad set of models. In particular, a main contribution of this thesis is to firmly establish both polarization, as well as spatial coupling, in the common toolbox of information theory/communication, statistical physics, and computer science

A posteriori error estimation and modeling of unsaturated flow in fractured porous media

This doctoral thesis focuses on three topics: (1) modeling of unsaturated flow in fractured porous media, (2) a posteriori error estimation for mixed-dimensional elliptic equations, and (3) contributions to open-source software for complex multiphysics processes in porous media. In our first contribution, following a Discrete-Fracture Matrix (DFM) approach, we propose a model where Richards' equation governs the water flow in the matrix, whereas fractures are represented as lower-dimensional open channels, naturally providing a capillary barrier to the water flow. Therefore, water in the matrix is only allowed to imbibe the fracture if the capillary barrier is overcome. When this occurs, we assume that the water inside the fracture flows downwards without resistance and, therefore, is instantaneously at hydrostatic equilibrium. This assumption can be justifiable for fractures with sufficiently large apertures, where capillary forces play no role. Mathematically, our model can be classified as a coupled PDE-ODE system of equations with variational inequalities, in which each fracture is considered a potential seepage face. Our second contribution deals with error estimation for mixed-dimensional (mD) elliptic equations, which, in particular, model single-phase flow in fractured porous media. Here, based on the theory of functional a posteriori error estimates, we derive guaranteed upper bounds for the mD primal and mD dual variables, and two-sided bounds for the mD primal-dual pair. Moreover, we improve the standard results of the functional approach by proposing four ways of estimating the residual errors based on the conservation properties of the approximations, that is, (1) no conservation, (2) subdomain conservation, (3) local conservation, and (4) pointwise conservation. This results in sharper and fully-computable bounds when mass is conserved either locally or exactly. To our knowledge, to date, no error estimates have been available for fracture networks, including fracture intersections and floating subdomains. Our last contribution is related to the development of open-source software. First, we present the implementation of a new multipoint finite-volume-based module for unsaturated poroelasticity, compatible with the Matlab Reservoir Simulation Toolbox (MRST). Second, we present a new Python-based simulation framework for multiphysics processes in fractured porous media, named PorePy. PorePy, by design, is particularly well-suited for handling mixed-dimensional geometries, and thus optimal for DFM models. The first two contributions discussed above were implemented in PorePy.Denne avhandlingen tar for seg tre emner: (1) modellering av flyt i umettet porøst medium med sprekker, (2) a posteriori feilestimater for blandet-dimensjonale elliptiske ligninger, og (3) bidrag til åpen kildekode for komplekse multifysikk-prosesser i porøse medier. I det første bidraget anvender vi en Discrete-Fracture Matrix (DFM) (Diskret-Sprekk Matrise) metode til å sette opp en modell hvor Richard's ligning modellerer vann-flyt i matrisen, og sprekkene representeres som lavere-dimensjonale åpne kanaler, som naturlig virker som kapillærbarrierer til vann-flyten. Derfor vil vann i matrisen kun få tilgang til sprekken når kapillærbarrieren blir brutt. Når det inntreffer, antar vi at vannet i sprekken flyter nedover uten motstand, og at hydrostatisk ekvilibrium derfor inntreffer øyeblikkelig. Slike antakelser kan rettferdiggjøres for sprekker med tilstrekkelig stor apertur (åpning), hvor kapillærkrefter ikke har noen innvirkning. Fra et matematisk standpunkt kan modellen klassifiseres som en sammenkoblet PDE-ODE med variasjonelle ulikheter hvor hver sprekk behandles som en filtreringsfase. Det andre bidraget tar for seg feilestimater for blandet-dimensjonale elliptiske ligninger, som modellerer en-fase flyt i porøse medier med sprekker. Her anvender vi teorien for "funksjonal a posteriori feilestimater" til å finne øvre skranker for primær og dual variablene, samt øvre og nedre skranker for primær-dual paret. Dessuten viser vi at vi kan forbedre standardresultatene fra "funksjonal a posteriori feilestimater" ved å foreslå fire måte å estimere residualfeilen basert på bevaringsegenskapene til diskretiseringen. De fire forskjellige bevaringsegenskapene er; ingen bevaringsegenskap, under- domene bevaring, lokal bevaring og punktvis bevaring. Dette fører til skarpere skranker som er mulige å beregne når masse er bevart enten lokalt, eller eksakt. Vi kjenner ikke til andre tilgjengelige feilestimater for sprekknettverk som inkluderer snitt av sprekker og sprekkrender som ligger innenfor domenets rand. Det siste bidraget omhandler utvikling av åpen kildekode. Først presenterer vi imple- menteringen av en multipunktfluks-basert modul for flyt i umettet deformerbart porøst medium som er kompatibelt med "Matlab Reservoir Simulation Toolbox"(MRST). I tillegg presenterer vi et nytt Python-basert rammeverk for simulering av multifysikkprosesser i porøse medier med sprekker, som heter PorePy. Dette rammeverket er designet for å håndtere geometrier med blandede dimensjoner og er derfor optimalt for DFM modeller. De to første bidragene i avhandlingen (nevnt over) er implementert i PorePy.Doktorgradsavhandlin