Location inaccuracies in WSAN placement algorithms

The random deployment of Wireless Sensor and Actuator Network (WSAN) nodes in areas often inaccessible, results in so-called coverage holes – i.e. areas in the network that are not adequately covered by nodes to suit the requirements of the network. Various coverage protocol algorithms have been designed to reduce or eliminate coverage holes within WSANs by indicating how to move the nodes. The effectiveness of such coverage protocols could be jeopardised by inaccuracy in the initial node location data that is broadcast by the respective nodes. This study examines the effects of location inaccuracies on five sensor deployment and reconfiguration algorithms – They include two algorithms which assume that mobile nodes are deployed (referred to as the VEC and VOR algorithms); two that assume static nodes are deployed (referred to as the CNPSS and OGDC algorithms); and a single algorithm (based on a bidding protocol) that assumes a hybrid scenario in which both static and mobile nodes are deployed. Two variations of this latter algorithm are studied. A location simulation tool was built using the GE Smallworld GIS application and the Magik programming language. The simulation results are based on three above-mentioned deployment scenarios; mobile, hybrid and static. The simulation results suggest the VOR algorithm is reasonably robust if the location inaccuracies are somewhat lower than the sensing distance and also if a high degree of inaccuracy is limited to a relatively small percentage of the nodes. The VEC algorithm is considerably less robust, but prevents nodes from drifting beyond the boundaries in the case of large inaccuracies. The bidding protocol used by the hybrid algorithm appears to be robust only when the static nodes are accurate and there is a low degree of inaccuracy within the mobile nodes. Finally the static algorithms are shown to be the most robust; the CPNSS algorithm appears to be immune to location inaccuracies whilst the OGDC algorithm was shown to reduce the number of active nodes in the network to a better extent than that of the CPNSS algorithm. CopyrightDissertation (MSc)--University of Pretoria, 2010.Computer Scienceunrestricte

Distributed sensing coverage maintenance in sensor networks

Sensing coverage is one of the key performance indicators of a large-scale sensor network. Sensing coverage holes may appear anywhere in the network field at any time due to random deployment, depletion of sensor battery power, or natural events in the deployment environment such as strong wind blowing some sensors away. Discovering the exact boundaries of coverage holes is important because it enables fast and efficient patching of coverage holes. In this thesis, we propose a framework of sensing coverage maintenance in sensor networks. In our framework, a sensor network consists of stationary and mobile sensors, where mobile sensors are used as patching hosts. We divide the coverage maintenance into two components: coverage hole discovery and coverage hole patching, and propose new solutions to both components. (1) We present two efficient distributed algorithms that periodically discover the precise boundaries of coverage holes. Our algorithms can handle the case that the transmission range of a sensor is smaller than twice the sensing range of the sensor. This case is largely ignored by previous work. (2) We present an efficient hole patching algorithm, which runs in linear time, based on the knowledge of the precise boundary of each coverage hole. We further propose new solutions for looking up available patching hosts, and movement planning. We present rigorous mathematical proofs of the correctness of the proposed hole discovery algorithms. We also show the running time and the performance bound in terms of mobile sensors needed of our hole patching algorithm through solid mathematical analysis. Our simulation results show that our distributed discovery algorithms are much more efficient than their centralized counterparts in terms of network overhead and total discovery time while still achieving the same correctness in discovering the boundaries of coverage holes. Furthermore, our patching algorithm performs well in terms of number of mobile sensors needed with a linear running time, and our hole patching scheme can achieve fast hole patching time when moving mobile sensors in a parallel manner

Déploiement optimal de réseaux de capteurs dans des environnements intérieurs en support à la navigation des personnes à mobilité réduite

La participation sociale des personnes ayant une incapacité (PAI) est l'un des enjeux majeurs de notre société. La participation sociale des PAI est influencée par les résultats des interactions entre les facteurs personnels et les facteurs environnementaux (physiques et sociaux). L'une des activités quotidiennes les plus importantes en milieu urbain est la mobilité, ce qui est fondamental pour la participation sociale des PAI. L'environnement urbain est composé des infrastructures et des services principalement conçus pour les personnes sans incapacités et ne prend pas en compte les besoins spécifiques des PAI. Dans ce contexte, la conception et le développement des environnements intelligents peuvent contribuer à une meilleure mobilité et participation sociale des PAI grâce à l'avancement récent de technologie de l'information et de télécommunication ainsi que de réseaux de capteurs. Cependant, le déploiement de réseaux de capteurs en tant que technologie d'assistance pour améliorer la mobilité des personnes n'est conçu que sur la base des modèles trop simplistes de l'environnement physique. Bien que des approches de déploiement de réseaux de capteurs aient été développées ces dernières années, la plupart d'entre elles ont considéré le modèle simple des capteurs (cercle ou sphérique dans le meilleur des cas) et l'environnement 2D, (sans obstacle), indépendamment des besoins des PAI lors de leur mobilité. À cet égard, l'objectif global de cette thèse est le déploiement optimal de réseau de capteurs dans un environnement intérieur pour améliorer l'efficacité de la mobilité des personnes à mobilité réduite (PMR). Plus spécifiquement, nous sommes intéressés à la mobilité des personnes utilisatrices de fauteuil roulant manuel. Pour atteindre cet objectif global, trois objectifs spécifiques sont identifiés. Premièrement, nous proposons un cadre conceptuel pour l'évaluation de la lisibilité de l'environnement intérieur pour les PMR, afin de déterminer la méthode appropriée pour évaluer les interactions entre les facteurs personnels et les facteurs environnementaux (par exemple, pentes, rampes, marches, etc.). Deuxièmement, nous développons un algorithme d'optimisation locale basé sur la structure Voronoi 3D pour le déploiement de capteurs dans l'environnement intérieur 3D pour s'attaquer à la complexité de la structure de l'environnement intérieur (par exemple, différentes hauteurs de plafonds) afin de maximiser la couverture du réseau. Troisièmement, pour aider la mobilité des PMR, nous développons un algorithme d'optimisation ciblé pour le déploiement de capteurs multi-types dans l'environnement intérieur en tenant compte du cadre d'évaluation de la lisibilité pour les PMR. La question la plus importante de cette recherche est la suivante : quels sont les emplacements optimaux pour un ensemble des capteurs pour le positionnement et le guidage des PMR dans l'environnement intérieur complexe 3D. Pour répondre à cette question, les informations sur les caractéristiques des capteurs, les éléments environnementaux et la lisibilité des PMR ont été intégrés dans les algorithmes d'optimisation locale pour le déploiement de réseaux de capteurs multi-types, afin d'améliorer la couverture du réseau et d'aider efficacement les PMR lors de leur mobilité. Dans ce processus, le diagramme de Voronoi 3D, en tant que structure géométrique, est utilisé pour optimiser l'emplacement des capteurs en fonction des caractéristiques des capteurs, des éléments environnementaux et de la lisibilité des PMR. L'optimisation locale proposée a été mise en œuvre et testée avec plusieurs scénarios au Centre des congrès de Québec. La comparaison des résultats obtenus avec ceux des autres algorithmes démontre une plus grande efficacité de l'approche proposée dans cette recherche.Social participation of people with disabilities (PWD) is one of the challenging problems in our society. Social participation of PWD is influenced by results from the interactions between personal characteristics and the physical and social environments. One of the most significant daily activities in the urban environment is mobility which impacts on the social participation of PWD. The urban environment includes infrastructure and services are mostly designed for people without any disability and does not consider the specific needs of PWD. In this context, the design and development of intelligent environments can contribute to better mobility and social participation of PWD by leveraging the recent advancement in information and telecommunications technologies as well as sensor networks. Sensor networks, as an assistive technology for improving the mobility of people are generally designed based on the simplistic models of physical environment. Although sensor networks deployment approaches have been developed in recent years, the majority of them have considered the simple model of sensors (circle or spherical in the best case) and the environment (2D, without obstacles) regardless of the PWD needs during their mobility. In this regard, the global objective of this thesis is the determination of the position and type of sensors to enhance the efficiency of the people with motor disabilities (PWMD) mobility. We are more specifically interested in the mobility of people using manual wheelchair. To achieve this global objective, three specific objectives are demarcated. First, a framework is developed for legibility assessment of the indoor environment for PWMD to determine the appropriate method to evaluate the interactions between personal factors with environmental factors (e.g. slops, ramps, steps, etc.). Then, a local optimization algorithm based on 3D Voronoi structure for sensor deployment in the 3D indoor environment is developed to tackle the complexity of structure of indoor environment (e.g., various ceilings' height) to maximize the network coverage. Next, a purpose-oriented optimization algorithm for multi-type sensor deployment in the indoor environment to help the PWMD mobility is developed with consideration of the legibility assessment framework for PWMD. In this thesis, the most important question of this research is where the optimal places of sensors are for efficient guidance of the PWMD in their mobility in 3D complex indoor environments. To answer this question, the information of sensors characteristics, environmental elements and legibility of PWMD have been integrated into the local optimization algorithms for multi-type sensor networks deployment to enhance the network coverage as well as efficiently help the PWMD during their mobility. In this process, Voronoi diagram as a geometrical structure is used to change the sensors' location based on the sensor characteristics, environmental elements and legibility of PWMD. The proposed local optimization is implemented and tested for several scenarios in Quebec City Convention Centre. The obtained results show that these integration in our approach enhance its effectiveness compared to the existing methods

Reliable cost-optimal deployment of wireless sensor networks

Wireless Sensor Networks (WSNs) technology is currently considered one of the key technologies for realizing the Internet of Things (IoT). Many of the important WSNs applications are critical in nature such that the failure of the WSN to carry out its required tasks can have serious detrimental effects. Consequently, guaranteeing that the WSN functions satisfactorily during its intended mission time, i.e. the WSN is reliable, is one of the fundamental requirements of the network deployment strategy. Achieving this requirement at a minimum deployment cost is particularly important for critical applications in which deployed SNs are equipped with expensive hardware. However, WSN reliability, defined in the traditional sense, especially in conjunction with minimizing the deployment cost, has not been considered as a deployment requirement in existing WSN deployment algorithms to the best of our knowledge. Addressing this major limitation is the central focus of this dissertation. We define the reliable cost-optimal WSN deployment as the one that has minimum deployment cost with a reliability level that meets or exceeds a minimum level specified by the targeted application. We coin the problem of finding such deployments, for a given set of application-specific parameters, the Minimum-Cost Reliability-Constrained Sensor Node Deployment Problem (MCRC-SDP). To accomplish the aim of the dissertation, we propose a novel WSN reliability metric which adopts a more accurate SN model than the model used in the existing metrics. The proposed reliability metric is used to formulate the MCRC-SDP as a constrained combinatorial optimization problem which we prove to be NP-Complete. Two heuristic WSN deployment optimization algorithms are then developed to find high quality solutions for the MCRC-SDP. Finally, we investigate the practical realization of the techniques that we developed as solutions of the MCRC-SDP. For this purpose, we discuss why existing WSN Topology Control Protocols (TCPs) are not suitable for managing such reliable cost-optimal deployments. Accordingly, we propose a practical TCP that is suitable for managing the sleep/active cycles of the redundant SNs in such deployments. Experimental results suggest that the proposed TCP\u27s overhead and network Time To Repair (TTR) are relatively low which demonstrates the applicability of our proposed deployment solution in practice

Distributed approaches for coverage missions with multiple heterogeneous UAVs for coastal areas.

This Thesis focuses on a high-level framework proposal for heterogeneous aerial, fixed wing teams of robots, which operate in complex coastal areas. Recent advances in the computational capabilities of modern processors along with the decrement of small scale aerial platform manufacturing costs, have given researchers the opportunity to propose efficient and low-cost solutions to a wide variety of problems. Regarding marine sciences and more generally coastal or sea operations, the use of aerial robots brings forth a number of advantages, including information redundancy and operator safety. This Thesis initially deals with complex coastal decomposition in relation with a vehicles’ on-board sensor. This decomposition decreases the computational complexity of planning a flight path, while respecting various aerial or ground restrictions. The sensor-based area decomposition also facilitates a team-wide heterogeneous solution for any team of aerial vehicles. Then, it proposes a novel algorithmic approach of partitioning any given complex area, for an arbitrary number of Unmanned Aerial Vehicles (UAV). This partitioning schema, respects the relative flight autonomy capabilities of the robots, providing them a corresponding region of interest. In addition, a set of algorithms is proposed for obtaining coverage waypoint plans for those areas. These algorithms are designed to afford the non-holonomic nature of fixed-wing vehicles and the restrictions their dynamics impose. Moreover, this Thesis also proposes a variation of a well-known path tracking algorithm, in order to further reduce the flight error of waypoint following, by introducing intermediate waypoints and providing an autopilot parametrisation. Finally, a marine studies test case of buoy information extraction is presented, demonstrating in that manner the flexibility and modular nature of the proposed framework.Esta tesis se centra en la propuesta de un marco de alto nivel para equipos heterogéneos de robots de ala fija que operan en áreas costeras complejas. Los avances recientes en las capacidades computacionales de los procesadores modernos, junto con la disminución de los costes de fabricación de plataformas aéreas a pequeña escala, han brindado a los investigadores la oportunidad de proponer soluciones eficientes y de bajo coste para enfrentar un amplio abanico de cuestiones. Con respecto a las ciencias marinas y, en términos más generales, a las operaciones costeras o marítimas, el uso de robots aéreos conlleva una serie de ventajas, incluidas la redundancia de la información y la seguridad del operador. Esta tesis trata inicialmente con la descomposición de áreas costeras complejas en relación con el sensor a bordo de un vehículo. Esta descomposición disminuye la complejidad computacional de la planificación de una trayectoria de vuelo, al tiempo que respeta varias restricciones aéreas o terrestres. La descomposición del área basada en sensores también facilita una solución heterogénea para todo el equipo para cualquier equipo de vehículos aéreos. Luego, propone un novedoso enfoque algorítmico de partición de cualquier área compleja dada, para un número arbitrario de vehículos aéreos no tripulados (UAV). Este esquema de partición respeta las capacidades relativas de autonomía de vuelo de los robots, proporcionándoles una región de interés correspondiente. Además, se propone un conjunto de algoritmos para obtener planes de puntos de cobertura para esas áreas. Estos algoritmos están diseñados teniendo en cuenta la naturaleza no holonómica de los vehículos de ala fija y las restricciones que impone su dinámica. En ese sentido, esta Tesis también ofrece una variación de un algoritmo de seguimiento de rutas bien conocido, con el fin de reducir aún más el error de vuelo del siguiente punto de recorrido, introduciendo puntos intermedios y proporcionando una parametrización del piloto automático. Finalmente, se presenta un caso de prueba de estudios marinos de extracción de información de boyas, que demuestra de esa manera la flexibilidad y el carácter modular del marco propuesto

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

1999 Flight Mechanics Symposium

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on May 18-20, 1999. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers

Control of heterogeneous robot networks for assistance in search and rescue tasks

This project develops a decentralized control strategy for multiple heterogeneous robots oriented to the assistance in search and rescue situations from two complementary perspectives, the discrete tasks allocation and the real-time control. For the discrete task allocation through the mission, we present an optimized algorithm based on events, oriented to the minimization of the time required to attend all the victims in the mission environment. This algorithm allows assign to each robot an appropriate task considering that the robots may vary in their capacity for completing each task and also may vary in their moving capabilities. The considered tasks are the mission environment exploration, the victims’ search and identification, the medical supplies delivery to victims unable to move and the evacuation of victims capable to move. It is worth to mention that, through the development of each task and the estimation of its durations, the robots consider optimized routes considering a distance metric based in the breath first search algorithm called flooding distance with 8 neighbors (8NF) which considers only orthogonal and 45 degrees diagonal movements allowing an estimation of the geodesic distance to each point in the map. Regarding to the real-time control laws, they oversee the proper execution of the tasks assigned by the reallocation algorithm respecting the restrictions in the connectivity range, the obstacles avoidance and the fulfillment of each task. The exploration task is made employing an adaptation of the algorithm DisCoverage presented by [16] which employing a Voronoi cells based tessellation considering the arrival time to each point as reference, allows the determination of the map of non-convex spaces as those that may be found in search and rescue situations. The evasion of obstacles and the preservation of the robots’ links is achieved employing an approach of artificial potentials based in the work of [37]. The interest points related to each task tracking is made employing proportional control loops for each agent identifying the route points within the line of sight and considering optimized routes given by the 8NF flooding distance metric. Additionally, there is presented a heuristic reconfiguration algorithm that allows to change the network topology preserving its connectivity for each instant of time. This complete framework allows a team of autonomous robots to bring valuable assistance in certain search and rescue situations where the human teams may be insufficient, and/or the mission conditions may be harmful for the people considering that even if the robots cannot realize paramedical tasks yet, they can complete multiple useful tasks for reducing the effort and risks of the human teams in that kind of situations. The functioning of those algorithms is presented in non-trivial simulations intended to show the behaviors that emerge in the robots.Resumen: Este proyecto desarrolló una estrategia de control descentralizado para múltiples robots heterogéneos orientada a la asistencia en situaciones de búsqueda y rescate desde dos perspectivas complementarias, la asignación discreta de tareas y el control en tiempo real. Para la asignación discreta de las tareas a los robots a lo largo de la misión, presentamos un algoritmo optimizado de reasignación de tareas basado en eventos, orientado a la minimización del tiempo requerido para atender a todas las víctimas en el ambiente de misión. Este algoritmo permite asignar a cada robot una tarea apropiada considerando que los robots pueden diferir en su capacidad para completar cada tarea, así como también en sus capacidades de movimiento. Las tareas consideradas son la exploración del ambiente de misión, la búsqueda e identificación de víctimas, la entrega de suministros médicos a las víctimas incapaces de moverse y la evacuación de las víctimas capaces de moverse. Cabe destacar que, durante el desarrollo de cada tarea y la estimación de los tiempos de las mismas, los robots consideran rutas optimizadas considerando una métrica de distancia basada en el algoritmo de búsqueda en anchura (Breath first Search) llamada distancia por inundaci´on con 8 vecinos (8NF) la cual considera movimientos netamente ortogonales y diagonales a 45 grados permitiendo una estimación de la distancia geodésica a cada punto en el mapa. Con respecto a las leyes de control en tiempo real, estas están a cargo de la correcta ejecución de las tareas asignadas por el algoritmo de reasignación de tareas respetando las restricciones en el rango de conectividad, la evasión de colisiones y la completa ejecución de cada tarea. La exploración es desarrollada empleando una adaptación del algoritmo DisCoverage presentado por [16] el cuál empleando una teselación basada en celdas de Voronoi con el tiempo de llegada a cada punto como referencia, permite la determinaci´on del mapa de espacios no convexos como los que se pueden encontrar en algunas situaciones de búsqueda y rescate. La evasión de obstáculos y la preservación de los enlaces se realiza a través de un enfoque de potenciales artificiales basándose en el trabajo de [37]. El seguimiento de los puntos de interés relacionados a cada tarea se realiza empleando lazos de control proporcional para cada agente identificando los puntos de ruta dentro de la línea de visión y considerando rutas optimizadas tomando la estimaciói brindada por la métrica de distancia por inundación 8NF. Adicionalmente se presentó un algoritmo de reconfiguración de la red heurístico que permite cambiar la topología de la red manteniendo la conectividad de la misma para cada instante de tiempo. Este marco de trabajo completo permite a un equipo de robots autónomos brindar asistencia valiosa en ciertas situaciones de búsqueda y rescate d´onde los equipos humanos sean insuficientes y/o las condiciones de la misión pueden ser peligrosas para las personas teniendo en cuenta que si bien los robots actualmente no son capaces de realizar tareas paramédicas si son capaces de realizar múltiples tareas útiles para aligerar el trabajo y el riesgo para equipos humanos en estas situaciones. El funcionamiento de estos algoritmos es presentado en simulaciones no triviales en Matlab R buscando presentar los comportamientos que emergen en los robots y adicionalmente fue implementado en una versión simplificada con robots móviles tipo turtlebot y configuraciones simples de robots BioloidMaestrí

Research on Reliable Low-Power Wide-Area Communications Utilizing Multi-RAT LPWAN Technologies for IoT Applications

Předkládaná disertační práce je zaměřena na „Výzkum spolehlivé komunikace pro IoT aplikace v bezdrátových sítích využívajících technologie Multi-RAT LPWAN“. Navzdory značnému pokroku v oblasti vývoje LPWA technologií umožňující masivní komunikace mezi zařízeními (mMTC), nemusí tyto technologie výkonnostně dostačovat pro nově vznikající aplikace internetu věcí. Hlavním cílem této disertační práce je proto nalezení a vyhodnocení limitů současných LPWA technologií. Na základě těchto dat jsou nevrženy nové mechanismy umožňující snazší plánování a vyhodnocování síťového pokrytí. Navržené nástroje jsou vyladěny a validovány s využitím dat získaných z rozsáhlých měřících kampaních provedených v zákaznických LPWA sítích. Tato disertační práce dále obsahuje návrh LPWA zařízení vybavených více komunikačními rozhraními (multi-RAT) které mohou umožnit překonání výkonnostních limitů jednotlivých LPWA technologií. Současná implementace se zaměřuje zejména na snížení spotřeby zařízení s více rádiovými rozhraními, což je jejich největší nevýhodou. K tomuto účelu je využito algoritmů strojového učení, které jsou schopné dynamicky vybírat nejvhodnější rozhraní k přenosu.This doctoral thesis addresses the “Research on Reliable Low-Power Wide-Area Communications Utilizing Multi-RAT LPWAN Technologies for IoT Applications”. Despite the immense progress in massive Machine-Type Communication (mMTC) technology enablers such as Low-Power Wide-Area (LPWA) networks, their performance does not have to satisfy the requirements of novelty Internet of Things (IoT) applications. The main goal of this Ph.D. work is to explore and evaluate the limitations of current LPWA technologies and propose novel mechanisms facilitating coverage planning and assessment. Proposed frameworks are fine-tuned and cross-validated by the extensive measurement campaigns conducted in public LPWA networks. This doctoral thesis further introduces the novelty approach of multi-RAT LPWA devices to overcome the performance limitation of individual LPWA technologies. The current implementation primarily focuses on diminishing the greatest multi-RAT solutions disadvantage, i.e., increased power consumption by employing a machine learning approach to radio interface selection.

Heterojen robotlarla dinamik formasyon kontrolü.

Formation control in robotics is a growing topic where research works are mainly geared towards heterogeneous swarm colonies under either decentralized control or limited centralization. Swarm robotics where decentralization is applied, nevertheless assume that the agents are capable of getting global information about the whole swarm.Moreoverintheliterature,formationcontrolisgenerallydoneforknownfixed shapesthatcanbedefinedmathematically. Howevernodynamicallychangingshapes areenvisagedandnoshapetransitionsareclearlyhandledinthoseworks. Weattempt to bring a clear impact to the literature by focusing on tracking and realising formation shapes under dynamically changing formation shape demands. Furthermore,in our thesis work, we focus on robot colonies composed of heterogeneous robots of differentdynamicsandsensorcapabilitiesunderdecentralizeddynamicallychanging formation control. These robots are able furthermore, to just possess local mutual interactions only with their close-by neighboring agents. In our approach communications of each agent with its neighbors converges to information about the whole colony based on graph theory. Simulations in our work are generated using the Gazebo environment by modelling a rough territory. Hardware applications which implements the methods discussed in this thesis work are also developed. These applications are evaluated as proof of concept work which illustrates that the methods can be implemented in real time applications.M.S. - Master of Scienc