Weighted-DESYNC and Its Application to End-to-End Throughput Fairness in Wireless Multihop Network

The end-to-end throughput of a routing path in wireless multihop network is restricted by a bottleneck node that has the smallest bandwidth among the nodes on the routing path. In this study, we propose a method for resolving the bottleneck-node problem in multihop networks, which is based on multihop DESYNC (MH-DESYNC) algorithm that is a bioinspired resource allocation method developed for use in multihop environments and enables fair resource allocation among nearby (up to two hops) neighbors. Based on MH-DESYNC, we newly propose weighted-DESYNC (W-DESYNC) as a tool artificially to control the amount of resource allocated to the specific user and thus to achieve throughput fairness over a routing path. Proposed W-DESYNC employs the weight factor of a link to determine the amount of bandwidth allocated to a node. By letting the weight factor be the link quality of a routing path and making it the same across a routing path via Cucker-Smale flocking model, we can obtain throughput fairness over a routing path. The simulation results show that the proposed algorithm achieves throughput fairness over a routing path and can increase total end-to-end throughput in wireless multihop networks

Multichannel Distributed Coordination for Wireless Sensor Networks: Convergence Delay and Energy Consumption Aspects

This thesis develops new approaches for distributed coordination of data-intensive communications between wireless sensor nodes. In particular, the topic of synchronization, and its dual primitive, desynchronization at the Medium Access Control (MAC) or the Application (APP) layer of the OSI stack, is studied in detail. In Chapters 1 and 2, the related literature on the problem of synchronization is overviewed and the main approaches for distributed (de)synchronization at the MAC or APP layers are analyzed, designed and implemented on IEEE802.15.4- enabled wireless sensor nodes. Beyond the experimental validation of distributed (de)synchronization approaches, the three main contributions of this thesis, corresponding to the related publications found below, are: • establishing for the first time the expected time for convergence to distributed time division multiple access (TDMA) operation under the two main desynchronization models proposed in the literature and validating the derived estimates via a real-world implementation (Chapter 3); • proposing the extension of the main desynchronization models towards multi-hop and multi-channel operation; the latter is achieved by extending the concept of reactive listening to multi-frequency operation (Chapter 4 and 5). • analyzing the energy consumption of the distributed TDMA approach under different transmission probability density functions (Chapter 6 and 7). Conclusions and items for future work in relation to the proposals of this thesis are described in Chapter 8

Toward Brain Area Sensor Wireless Network

RÉSUMÉ De nouvelles approches d'interfaçage neuronal de haute performance sont requises pour les interfaces cerveau-machine (BMI) actuelles. Cela nécessite des capacités d'enregistrement/stimulation performantes en termes de vitesse, qualité et quantité, c’est à dire une bande passante à fréquence plus élevée, une résolution spatiale, un signal sur bruit et une zone plus large pour l'interface avec le cortex cérébral. Dans ce mémoire, nous parlons de l'idée générale proposant une méthode d'interfaçage neuronal qui, en comparaison avec l'électroencéphalographie (EEG), l'électrocorticographie (ECoG) et les méthodes d'interfaçage intracortical conventionnelles à une seule unité, offre de meilleures caractéristiques pour implémenter des IMC plus performants. Les avantages de la nouvelle approche sont 1) une résolution spatiale plus élevée - en dessous dumillimètre, et une qualité de signal plus élevée - en termes de rapport signal sur bruit et de contenu fréquentiel - comparé aux méthodes EEG et ECoG; 2) un caractère moins invasif que l'ECoG où l'enlèvement du crâne sous une opération d'enregistrement / stimulation est nécessaire; 3) une plus grande faisabilité de la libre circulation du patient à l'étude - par rapport aux deux méthodes EEG et ECoG où de nombreux fils sont connectés au patient en cours d'opération; 4) une utilisation à long terme puisque l'interface implantable est sans fil - par rapport aux deux méthodes EEG et ECoG qui offrent des temps limités de fonctionnement. Nous présentons l'architecture d'un réseau sans fil de microsystèmes implantables, que nous appelons Brain Area Sensor NETwork (Brain-ASNET). Il y a deux défis principaux dans la réalisation du projet Brain-ASNET. 1) la conception et la mise en oeuvre d'un émetteur-récepteur RF de faible consommation compatible avec la puce de capteurs de réseau implantable, et, 2) la conception d'un protocole de réseau de capteurs sans fil (WSN) ad-hoc économe en énergie. Dans ce mémoire, nous présentons un protocole de réseau ad-hoc économe en énergie pour le réseau désiré, ainsi qu'un procédé pour surmonter le problème de la longueur de paquet variable causé par le processus de remplissage de bit dans le protocole HDLC standard. Le protocole adhoc proposé conçu pour Brain-ASNET présente une meilleure efficacité énergétique par rapport aux protocoles standards tels que ZigBee, Bluetooth et Wi-Fi ainsi que des protocoles ad-hoc de pointe. Le protocole a été conçu et testé par MATLAB et Simulink.----------ABSTRACT New high-performance neural interfacing approaches are demanded for today’s Brain-Machine Interfaces (BMI). This requires high-performance recording/stimulation capabilities in terms of speed, quality, and quantity, i.e. higher frequency bandwidth, spatial resolution, signal-to-noise, and wider area to interface with the cerebral cortex. In this thesis, we talk about the general proposed idea of a neural interfacing method which in comparison with Electroencephalography (EEG), Electrocorticography (ECoG), and, conventional Single-Unit Intracortical neural interfacing methods offers better features to implement higher-performance BMIs. The new approach advantages are 1) higher spatial resolution – down to sub-millimeter, and higher signal quality − in terms of signal-to-noise ratio and frequency content − compared to both EEG and ECoG methods. 2) being less invasive than ECoG where skull removal Under recording/stimulation surgery is required. 3) higher feasibility of freely movement of patient under study − compared to both EEG and ECoG methods where lots of wires are connected to the patient under operation. 4) long-term usage as the implantable interface is wireless − compared to both EEG and ECoG methods where it is practical for only a limited time under operation. We present the architecture of a wireless network of implantable microsystems, which we call it Brain Area Sensor NETwork (Brain-ASNET). There are two main challenges in realization of the proposed Brain-ASNET. 1) design and implementation of power-hungry RF transceiver of the implantable network sensors' chip, and, 2) design of an energy-efficient ad-hoc Wireless Sensor Network (WSN) protocol. In this thesis, we introduce an energy-efficient ad-hoc network protocol for the desired network, along with a method to overcome the issue of variable packet length caused by bit stuffing process in standard HDLC protocol. The proposed ad-hoc protocol designed for Brain-ASNET shows better energy-efficiency compared to standard protocols like ZigBee, Bluetooth, and Wi-Fi as well as state-of-the-art ad-hoc protocols. The protocol was designed and tested by MATLAB and Simulink

DISTRIBUTIVE AND SELF-SUSTAINABLE SCHEDULING ALGORITHMS FOR WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSNs), due to their vital importance, are emerging as a ubiquitous networking arena which pervades some of the old applications and also enables many new ones. The credit for the rapid growth in WSN technology goes to its self-organising and self-configuring abilities. Generally, the distributed environment ofWSNs with little or no predetermined infrastructure, mobility, lack of bandwidth and scalability are the issues that affect network performance. In WSNs, lifetime is considered as the key challenging issues because all of the sensors are battery powered. Physically, it is infeasible to recharge or replace the battery. Most of the energy in WSN is wasted due to idle listening, collision, message overhearing, and message overhead

Techniques for Decentralized and Dynamic Resource Allocation

abstract: This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the ``cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer. The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol. The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized. The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA). The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics. While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints. The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Wireless Sensor Data Transport, Aggregation and Security

abstract: Wireless sensor networks (WSN) and the communication and the security therein have been gaining further prominence in the tech-industry recently, with the emergence of the so called Internet of Things (IoT). The steps from acquiring data and making a reactive decision base on the acquired sensor measurements are complex and requires careful execution of several steps. In many of these steps there are still technological gaps to fill that are due to the fact that several primitives that are desirable in a sensor network environment are bolt on the networks as application layer functionalities, rather than built in them. For several important functionalities that are at the core of IoT architectures we have developed a solution that is analyzed and discussed in the following chapters. The chain of steps from the acquisition of sensor samples until these samples reach a control center or the cloud where the data analytics are performed, starts with the acquisition of the sensor measurements at the correct time and, importantly, synchronously among all sensors deployed. This synchronization has to be network wide, including both the wired core network as well as the wireless edge devices. This thesis studies a decentralized and lightweight solution to synchronize and schedule IoT devices over wireless and wired networks adaptively, with very simple local signaling. Furthermore, measurement results have to be transported and aggregated over the same interface, requiring clever coordination among all nodes, as network resources are shared, keeping scalability and fail-safe operation in mind. Furthermore ensuring the integrity of measurements is a complicated task. On the one hand Cryptography can shield the network from outside attackers and therefore is the first step to take, but due to the volume of sensors must rely on an automated key distribution mechanism. On the other hand cryptography does not protect against exposed keys or inside attackers. One however can exploit statistical properties to detect and identify nodes that send false information and exclude these attacker nodes from the network to avoid data manipulation. Furthermore, if data is supplied by a third party, one can apply automated trust metric for each individual data source to define which data to accept and consider for mentioned statistical tests in the first place. Monitoring the cyber and physical activities of an IoT infrastructure in concert is another topic that is investigated in this thesis.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Accurate Localization with Ultra-Wideband Ranging for Multi-Robot Systems

RÉSUMÉ : Avec l’avancement de la technologie matérielle et logicielle, l’application de l’automatisation et de la robotique se développe rapidement. Les systèmes multi-robots sont particulièrement prometteurs en raison de leur grande efficacité et robustesse. De tels systèmes peuvent être utilisés pour aider les humains à effectuer efficacement des tâches dangereuses ou pénibles, telles que l’intervention en cas de catastrophe, l’exploration souterraine, etc. Pour déployer un système multi-robot dans un environnement sans GPS, la coordination des robots dans le système est un défi crucial. Chaque robot doit avoir une estimation précise de sa propre position pour permettre aux robots du système de collaborer pour la réalisation de leur tâche. Comme cette direction de recherche est relativement nouvelle, les approches existantes ne sont pas encore abouties. Elles consistent principalement en des systèmes centralisés qui reposent sur des signaux GPS. La dépendance sur un signal GPS limite l’application aux espaces extérieurs ouverts. De plus, les systèmes centralisés sont confrontés au risque d’un point de défaillance unique, qui limite la robustesse du système. Par ailleurs, un système centralisé n’est pas toujours approprié à une taille grandissante, comme lors d’ajout de nouveaux groupes de robots ou lors de la fusion de différents groupes. Par conséquent, une solution distribuée, décentralisée, et adaptée à de larges groupes de tailles variables pouvant produire une estimation et un suivi du positionnement des robots dans un environnement sans GPS est souhaitée. Dans ce travail, nous adoptons une stratégie descendante pour relever ces défis.----------ABSTRACT : With the advancement of hardware and software technology, the everyday applications of automation and robotics are developing rapidly. Multi-robot systems are particularly promising because of their high efficiency and robustness. Such systems can be used to assist humans in performing dangerous or strenuous tasks, such as disaster response, subterranean exploration, etc. To deploy a multi-robot system in an environment without a global positioning system (GPS), coordinating the robots in the system is a crucial challenge. Each robot needs to have the correct tracking of its own and its teammates positions to enable the robots to cooperate. Because this research direction is relatively new, there are not many mature methods: existing approaches are mainly centralized systems that rely on GPS signals. The dependence on GPS restricts the application to the outdoors or indoor spaces with expensive infrastructure. Centralized systems also face the risk of a single point of failure, which is not acceptable for critical systems. In addition, centralized systems can be hard to scale both statically and dynamically (e.g. adding new groups of robots or merging different groups). Therefore, a distributed and scalable solution with accurate positioning and tracking in a GPS-denied environment is desired. In this work, we follow a top-down strategy to address these challenges