Hierarchical Routing in Low-Power Wireless Networks

Steen, M.R. van [Promotor

WHISPER – service integrated incident management system

ABSTRACT: This paper presents a cohesive summary of existing emergency response systems. We investigate and integrate principles, theories, and practices from four diverse, yet related, fields of knowledge with respect to information representation and decision support capability requirements for emergency planning and response (EPR) systems. This enables the cooperation between constituent agencies (e.g., fire, police and medical) and surrounding municipalities which operate using assorted decision support protocols, system architectures, networking strategies and along different levels of data security needs. Based upon our investigation, we have built a service architectural framework for providing and disseminating an integrated platform of knowledge capable of being used as intelligent interconnects between distributed EPR systems. Such a framework can support affordable integration for municipalities of all sizes, in particular smaller municipalities that often cannot afford costly off-the-shelf software solutions consisting of proprietary logic and requiring extensive customization and support cost. We also present a prototype web service based implementation and summarize the limitations of such an approach. Index: Emergency response system, emergency planning and response, emergency management, decision support, web service

A methodology for cooperation between electric utilities and consumers for microgrid utilization based on a systems engineering approach

In recent years, the energy market has experienced important challenges in its structure and requirements of its actors, such as the necessity for more reliable electric service, energy efficiency, environmental care practices, and the incorporation of decentralized power generation based on distributed energy resources (DER). Given this context, microgrids offer several advantages to the grid and its actors. However, few microgrid projects have been implemented, and the participation of electric utilities is lower than the expected. Hence, this research explores how electric utility - customer interactions can accommodate mutual benefits for both parties through the proposal of a Microgrid Reference Methodology (MRM) that guides the cooperation of these actors for future microgrid projects. For this research, an understanding of the microgrid system was imperative; hence, the interests and concerns of electric utilities and industrial customers were determined via questionnaires, interviews, and a literature review of specialized articles, books, and magazines. In addition, the MRM development was based on different frameworks and concepts from the fields of Systems Engineering, System of Systems, Management Science, and Infrastructure Architectures. The proposed MRM uses a four-level microgrid system in which the delta (business) level is added to the other three levels that are traditionally analyzed in microgrid design and modeling. The steps and processes necessary to determine the actors in the system and their interests, goals, criteria, and factors are exemplified with a generic case study, in which the proposed MRM evaluates the impact of different alternatives on the objectives of both parties. In addition, it was possible to identify external factors that can be influenced by other actors, such as regulators and government, to incentivize the implementation of microgrid projects

Untersuchung von ausbringungspezifischer Simulation zur Optimierung drahtloser Sensornetzwerke

This theses researches whether it is possible to map existing deployments to a simulator accurately enough to use simulation to optimize for this specific deployment. For this purpose DrySim was developed as an approach to achieve more realistic simulation of Wireless Sensor Networks (WSNs). DrySim has two components, RealSim and DryRun: RealSim traces the network connectivity of a deployed WSN and allows replaying it in a simulator, whereas DryRun supports exploring a configuration space by running simulations and extracting and preparing data for further analysis. Two different test beds located in office environments were used to evaluate and verify the approach. Measurements in the two test beds showed that they required different configuration options. This was reflected in simulation as well as trial results. The evaluation presents a solid data basis for three scenarios, with a total of 1320 test bed and 8800 simulation runs between 5 and 20 minutes. During the evaluation care was taken to avoid systematic or probe effects. Analysis of the test beds also revealed that the default settings of ContikiOS, a popular WSN operating system, are unsuitable for most WSN deployments. The theses also features an analysis of the impact of different components on a WSN node. Specifically it was evaluated how accurately they can and must be simulated to achieve realistic results. These studies revealed two important points: Firstly the micro controller must be emulated to achieve real time accuracy. Secondly the radio characteristics of a network cannot be predicted and thus must be measured in the final deployment. In previous work, only specific aspects of simulating WSNs were researched. The research done in the context of DrySim, however, shows that to achieve realistic WSN simulation the main components, which are software, micro controller and radio chip and the radio network, must not be treated separately. With DrySim a solution is presented that allows for realistic enough simulation to tune configuration parameters to a specific deployment, while keeping the effort of tweaking the simulation model at a minimum.Diese Arbeit untersucht, ob es möglich ist bestehendes Sensornetzwerk in einem Simulator abzubilden, so dass dieses auf im Simulator ausbringungspezifisch optimiert werden kann. Hierzu wurde DrySim entwickelt. Ein Ansatz um eine realistischere Simulation von drahtlosen Sensornetzwerken (WSN) zu erzielen. DrySim besteht aus zwei Komponenten, RealSim und DryRun: RealSim zeichnet die Netzwerkkonnektivität eines ausgebrachten WSN auf und kann diese im einem Simulator wiedergeben. DryRun hingeben kann durch die Ausführung von Simulationen einen Konfigurationsraum erkunden und die gewonnenen Daten aufbereiten. Der Ansatz wurde in zwei Testnetzwerke, die in Büroräumen ausgebracht waren evaluiert. Die Messungen in den beiden Netzwerken haben gezeigt, dass sie unterschiedliche Konfigurationen benötigen, was sich auch in den Simulationen widergespiegelt hat. Die Evaluation präsentiert eine solide Datenbasis für drei Szenarien, mit 1320 Versuchen auf den Testnetzwerken und 8800 Simulationen zwischen 5 und 20 Minuten. Es wurde darauf geachtet den Einfluss durch systematische Fehler und die Beobachtung zu vermeiden. Die Untersuchung hat auch gezeigt, dass die Standardeinstellungen von ContikiOS, eines verbreiteten WSN-Betriebssystems für die meisten Umgebungen ungeeignet sind. Die Arbeit analysiert auch den Einfluss der verschiedenen Komponenten auf einen WSN-Knoten. Insbesondere wurde untersucht, wie akkurat diese simuliert werden können und müssen um realistische Simulationsergebnisse zu erzielen. Hierbei wurden zwei wichtige Punkte herausgearbeitet: Erstens muss der Mikrocontroller emuliert werden, um Echtzeitgenauigkeit zu erreichen. Zweitens können die Funkcharakteristiken eines Netzwerks nicht vorhergesagt werden und müssen daher vermessen werden. Vorhergehenden Arbeiten haben sich meist auf spezifische Aspekte der Simulation von Sensornetzwerken konzentriert. Die in Kontext von DrySim betriebene Forschung zeigt jedoch, dass realistische Simulationsergebnisse nur erreicht werden können, wenn die Hauptkomponenten, Software, Mikrocontroller, Radio-Chip und Funknetzwerk nicht getrennt betrachtet werden. Mit DrySim wird eine Lösung präsentiert, die es erlaubt bestehende Netzwerke so akkurat zu simulieren, dass man die Konfigurationsparameter auf dieses spezifische Netzwerk anpassen kann. Dabei bleibt der Konfigurationsaufwand bei einem Minimum

Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

Mission programming for flying ensembles: combining planning with self-organization

The application of autonomous mobile robots can improve many situations of our daily lives. Robots can enhance working conditions, provide innovative techniques for different research disciplines, and support rescue forces in an emergency. In particular, flying robots have already shown their potential in many use-cases when cooperating in ensembles. Exploiting this potential requires sophisticated measures for the goal-oriented, application-specific programming of flying ensembles and the coordinated execution of so defined programs. Because different goals require different robots providing different capabilities, several software approaches emerged recently that focus on specifically designed robots. These approaches often incorporate autonomous planning, scheduling, optimization, and reasoning attributable to classic artificial intelligence. This allows for the goal-oriented instruction of ensembles, but also leads to inefficiencies if ensembles grow large or face uncertainty in the environment. By leaving the detailed planning of executions to individuals and foregoing optimality and goal-orientation, the selforganization paradigm can compensate for these drawbacks by scalability and robustness. In this thesis, we combine the advantageous properties of autonomous planning with that of self-organization in an approach to Mission Programming for Flying Ensembles. Furthermore, we overcome the current way of thinking about how mobile robots should be designed. Rather than assuming fixed-design robots, we assume that robots are modifiable in terms of their hardware at run-time. While using such robots enables their application in many different use cases, it also requires new software approaches for dealing with this flexible design. The contributions of this thesis thus are threefold. First, we provide a layered reference architecture for physically reconfigurable robot ensembles. Second, we provide a solution for programming missions for ensembles consisting of such robots in a goal-oriented fashion that provides measures for instructing individual robots or entire ensembles as desired in the specific use case. Third, we provide multiple self-organization mechanisms to deal with the system’s flexible design while executing such missions. Combining different self-organization mechanisms ensures that ensembles satisfy the static requirements of missions. We provide additional self-organization mechanisms for coordinating the execution in ensembles ensuring they meet the dynamic requirements of a mission. Furthermore, we provide a solution for integrating goal-oriented swarm behavior into missions using a general pattern we have identified for trajectory-modification-based swarm behavior. Using that pattern, we can modify, quantify, and further process the emergent effect of varying swarm behavior in a mission by changing only the parameters of its implementation. We evaluate results theoretically and practically in different case studies by deploying our techniques to simulated and real hardware.Der Einsatz von autonomen mobilen Robotern kann viele Abläufe unseres täglichen Lebens erleichtern. Ihr Einsatz kann Arbeitsbedingungen verbessern, als innovative Technik für verschiedene Forschungsdisziplinen dienen oder Rettungskräfte im Einsatz unterstützen. Insbesondere Flugroboter haben ihr Potenzial bereits in vielerlei Anwendungsfällen gezeigt, gerade wenn mehrere in Ensembles eingesetzt werden. Das Potenzial fliegender Ensembles zielgerichtet und anwendungsspezifisch auszuschöpfen erfordert ausgefeilte Programmiermethoden und Koordinierungsverfahren. Zu diesem Zweck sind zuletzt viele unterschiedliche und auf speziell entwickelte Roboter zugeschnittene Softwareansätze entstanden. Diese verwenden oft klassische Planungs-, Scheduling-, Optimierungs- und Reasoningverfahren. Während dies vor allem den zielgerichteten Einsatz von Ensembles ermöglicht, ist es jedoch auch oft ineffizient, wenn die Ensembles größer oder deren Einsatzumgebungen unsicher werden. Die genannten Nachteile können durch das Paradigma der Selbstorganisation kompensiert werden: Falls Anwendungen nicht zwangsläufig auf Optimalität und strikte Zielorientierung ausgelegt sind, kann so Skalierbarkeit und Robustheit im System erreicht werden. In dieser Arbeit werden die vorteilhaften Eigenschaften klassischer Planungstechniken mit denen der Selbstorganisation in einem Ansatz zur Missionsprogrammierung für fliegende Ensembles kombiniert. In der dafür entwickelten Lösung wird von der aktuell etablierten Ansicht einer unveränderlichen Roboterkonstruktion abgewichen. Stattdessen wird die Hardwarezusammenstellung der Roboter als zur Laufzeit modifizierbar angesehen. Der Einsatz solcher Roboter erfordert neue Softwareansätze um mit genannter Flexibilität umgehen zu können. Die hier vorgestellten Beiträge zu diesem Thema lassen sich in drei Punkten zusammenfassen: Erstens wird eine Schichtenarchitektur als Referenz für physikalisch konfigurierbare Roboterensembles vorgestellt. Zweitens wird eine Lösung zur zielorientierten Missions-Programmierung für derartige Ensembles präsentiert, mit der sowohl einzelne Roboter als auch ganze Ensembles instruiert werden können. Drittens werden mehrere Selbstorganisationsmechanismen vorgestellt, die die autonome Ausführung so erstellter Missionen ermöglichen. Durch die Kombination verschiedener Selbstorganisationsmechanismen wird sichergestellt, dass Ensembles die missionsspezifischen Anforderungen erfüllen. Zusätzliche Selbstorganisationsmechanismen ermöglichen die koordinierte Ausführung der Missionen durch die Ensembles. Darüber hinaus bietet diese Lösung die Möglichkeit der Integration zielorientierten Schwarmverhaltens. Durch ein allgemeines algorithmisches Verfahren für auf Trajektorien-Modifikation basierendes Schwarmverhalten können allein durch die Änderung des Parametersatzes unterschiedliche emergente Effekte in einer Mission erzielt, quantifiziert und weiterverarbeitet werden. Zur theoretischen und praktischen Evaluierung der Ergebnisse dieser Arbeit wurden die vorgestellten Techniken in verschiedenen Fallstudien auf simulierter sowie realer Hardware zum Einsatz gebracht

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa