TY - JOUR A1 - Mandarawi, Waseem A1 - Rottmeier, Jürgen A1 - Rezaeighale, Milad A1 - de Meer, Hermann T1 - Policy-Based Composition and Embedding of Extended Virtual Networks and SFCs for IIoT JF - Algorithms N2 - The autonomic composition of Virtual Networks (VNs) and Service Function Chains (SFCs)based on application requirements is significant for complex environments. In this paper, we use graph transformation in order to compose an Extended Virtual Network (EVN) that is based on different requirements, such as locations, low latency, redundancy, and security functions. The EVN can represent physical environment devices and virtual application and network functions. We build a generic Virtual Network Embedding (VNE) framework for transforming an Application Request (AR) to an EVN. Subsequently, we define a set of transformations that reflect preliminary topological, performance, reliability, and security policies. These transformations update the entities and demands of the VN and add SFCs that include the required Virtual Network Functions (VNFs). Additionally, we propose a greedy proactive heuristic for path-independent embedding of the composed SFCs. This heuristic is appropriate for real complex environments, such as industrial networks. Furthermore, we present an Industrail Internet of Things (IIoT) use case that was inspired by Industry 4.0 concepts,in which EVNs for remote asset management are deployed over three levels; manufacturing halls and edge and cloud computing. We also implement the developed methods in Alevin and show exemplary mapping results from our use case. Finally, we evaluate the chain embedding heuristic while using a random topology that is typical for such a use case, and show that it can improve the admission ratio and resource utilization with minimal overhead. KW - NFV KW - SFC KW - VNE KW - IIoT Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-8488 SN - 1999-4893 VL - 13 IS - 9 PB - MDPI ER - TY - THES A1 - Gerl, Armin T1 - Modelling of a Privacy Language and Efficient Policy-based De-identification N2 - The processing of personal information is omnipresent in our data-driven society enabling personalized services, which are regulated by privacy policies. Although privacy policies are strictly defined by the General Data Protection Regulation (GDPR), no systematic mechanism is in place to enforce them. Especially if data is merged from several sources into a data-set with different privacy policies associated, the management and compliance to all privacy requirements is challenging during the processing of the data-set. Privacy policies can vary hereby due to different policies for each source or personalization of privacy policies by individual users. Thus, the risk for negligent or malicious processing of personal data due to defiance of privacy policies exists. To tackle this challenge, a privacy-preserving framework is proposed. Within this framework privacy policies are expressed in the proposed Layered Privacy Language (LPL) which allows to specify legal privacy policies and privacy-preserving de-identification methods. The policies are enforced by a Policy-based De-identification (PD) process. The PD process enables efficient compliance to various privacy policies simultaneously while applying pseudonymization, personal privacy anonymization and privacy models for de-identification of the data-set. Thus, the privacy requirements of each individual privacy policy are enforced filling the gap between legal privacy policies and their technical enforcement. KW - Privacy Language KW - Personal Privacy KW - Privacy-Preservation KW - GDPR KW - LPL KW - Datenschutz KW - Anonymisierung KW - Pseudonymisierung KW - Formale Sprache KW - Datenschutzgesetz Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-7674 ER - TY - THES A1 - Jurgovsky, Johannes T1 - Context-Aware Credit Card Fraud Detection N2 - Credit card fraud has emerged as major problem in the electronic payment sector. In this thesis, we study data-driven fraud detection and address several of its intricate challenges by means of machine learning methods with the goal to identify fraudulent transactions that have been issued illegitimately on behalf of the rightful card owner. In particular, we explore several means to leverage contextual information beyond a transaction’s basic attributes on the transaction level, sequence level and user level. On the transaction level, we aim to identify fraudulent transactions which, in terms of their attribute values, are globally distinguishable from genuine transactions. We provide an empirical study of the influence of class imbalance and forecasting horizons on the classification performance of a random forest classifier. We augment transactions with additional features extracted from external knowledge sources and show that external information about countries and calendar events improves classification performance most noticeably on card-not-present transactions. On the sequence level, we aim to detect frauds that are inconspicuous in the background of all transactions but peculiar with respect to the short-term sequence they appear in. We use a Long Short-term Memory network (LSTM) for modeling the sequential succession of transactions. Our results suggest that LSTM-based modeling is a promising strategy for characterizing sequences of card-present transactions but it is not adequate for card-not-present transactions. On the user level, we elaborate on feature aggregations and propose a flexible concept allowing us define numerous features by means of a simple syntax. We provide a CUDA-based implementation for the computationally expensive extraction with a speed-up of two orders of magnitude over a single-core implementation. Our feature selection study reveals that aggregates extracted from users’ transaction sequences are more useful than those extracted from merchant sequences. Moreover, we discover multiple sets of candidate features with equivalent performance as manually engineered aggregates while being structurally different. Regarding future work, we motivate the usage of simple and transparent machine learning methods for credit card fraud detection and we sketch a simple user-focused modeling approach. KW - Credit Card Fraud Detection KW - Machine Learning KW - Data Augmentation KW - Feature Engineering KW - Kreditkartenmissbrauch KW - Computersicherheit Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-7622 ER - TY - THES A1 - Klaus, Tina T1 - Complexity Analysis of Quantizations of Multidimensional Stochastic Differential Equations N2 - The dissertation is located in the field of quantizations of certain stochastic processes, namely a solution X of a multidimensional stochastic differential equation (SDE). The quantization problem for X consists in approximating X by a a random element which takes only finitely many values. Our main interest lies in the investigation of the asymptotic behavior of the Nth minimal quantization error of X as N tends to infinity, which incorporates the determination of both the sharp rate of convergence and explicit asymptotic constants. Especially explicit asymptotic constants have been so far unknown in the context of multidimensional SDEs. Furthermore, as part of our analysis, we provide a method which yields a strongly asymptotically optimal sequence of N-quantization of X. In certain special cases our method is fully constructive and the algorithm is easy to implement. KW - Stochastische Differentialgleichung KW - Komplexität KW - Quantifizierung Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-7665 ER - TY - THES A1 - Charpenay, Victor T1 - Semantics for the Web of Things: Modeling the Physical World as a Collection of Things and Reasoning with their Descriptions N2 - The main research question of this thesis is to develop a theory that would provide foundations for the development of Web of Things (WoT) systems. A theory for WoT shall provide a model of the ‘things’ WoT agents relate to such that these relations determine what interactions take place between these agents. This thesis presents a knowledge-based approach in which the semantics of WoT systems is given by a transformation (an homomorphism) between a graph representing agent interactions and a knowledge graph describing ‘things’. It focuses on three aspects of knowledge graphs in particular: the vocabulary with which assertions can be made, the rules that can be defined over this vocabulary and its serialization to efficiently exchange pieces of a knowledge graph. Each aspect is developed in a dedicated chapter, with specific contributions to the state-of-the-art. The need for a unified vocabulary to describe ‘things’ in WoT and the Internet of Things (IoT) has been identified early on in the literature. Many proposals have been consequently published, in the form of Web ontologies. In Ch. 2, a systematic review of these proposals is being developed, as well as a comparison with the data models of the principal IoT frameworks and protocols. The contribution of the thesis in that respect is an alignment between the Thing Description (TD) model and the Semantic Sensor Network (SSN) ontology, two standards of the World Wide Web Consortium (W3C). The scope of this thesis is generally limited to Web standards, especially those defined by the Resource Description framework (RDF). Web ontologies do not only expose a vocabulary but also rules to extend a knowledge graph by means of reasoning. Starting from a set of TD documents, new relations between ‘things’ can be “discovered” this way, indicating possible interactions between the servients that relate to them. The experiments presented in Ch. 3 were done on the basis of this semantic discovery framework on two use cases: a building automation use case provided by Intel Labs and an industrial control use case developed internally at Siemens. The relations to discover often involve anonymous nodes in the knowledge graph: the chapter also introduces a novel skolemization algorithm to correctly process these nodes on a well-defined fragment of the Web Ontology Language (OWL). Finally, because this semantic discovery framework relies on the exchange of TD documents, Ch. 4 introduces a binary format for RDF that proves efficient in serializing TD assertions such that even the smallest WoT agents, i.e. micro-controllers, can store and process them. A formalization for the semantics-preserving compaction and querying of TD documents is also introduced in this chapter, at the basis of an embedded RDF store called the µRDF store. The ability of all WoT agents to query logical assertions about themselves and their environment, as found in TD documents, is a first step towards knowledge-based intelligent systems that can operate autonomously and dynamically in a decentralized way. The µRDF store is an attempt to illustrate the practical outcomes of the theory of WoT developed throughout this thesis. N2 - Die Dissertation entwickelt eine theoretische Grundlage für die Spezifikation Web of Things (WoT)-Systemen. Die Spezifikation der WoT-Systeme basiert auf einem Modell für die Dinge, oder Things, mit denen WoT-Agenten Beziehungen schaffen, welche Interaktionen zwischen Agenten erlauben. Diese Dissertation stellt einen wissensbasierten Ansatz vor, in dem die Semantik von WoT-Systemen als eine Transformation von einem Graphen von Agenten-Interaktionen nach einem Knowledge Graph definiert ist. Diese Arbeit deckt genau drei Aspekte Knowledge Graphs ab: das Vokabular, mit dem logische Schlüsse formuliert werden, die Regeln, die auf einem Vokabular basieren können und Serialisierung, um den effizienten Austausch zwischen Teilen eines Knowledge Graph zu ermöglichen. Alle drei Aspekt werden mit ihren wissenschaftlichen Beitrag in einem eigenen Kapitel adressiert. Der Bedarf an einem vereinigten Vokabular, um im WoT und dem Internet of Things (IoT) Things zu beschreiben, wurden in der Literatur frühzeitig identifiziert. Viele Ansatze wurden diesbezüglich vor allem als Web Ontologien veröffentlicht. Im Kapitel 2 werden diese Ansätze miteinander, sowie mit Datenmodelle dominierender IoT-Frameworks und Protokolle verglichen. Der Beitrag der Dissertation diesbezüglich ist die Verschmelzung des WoT Thing Description (TD) Modells und der Semantic Sensor Network (SSN) Ontologie, zwei vom World Wide Web Consortium (W3C) veröffentlichte Standards, in eine einzige Ontologie. Der Rahmen dieser Dissertation wird auf Web Standards begrenzt, insbesondere im Resource Description Framework (RDF) enthaltenen Standards. Web Ontologien bestehen nicht nur aus einm Vokabular, sondern auch aus Regel, um einen Knowledge Graphen durch Inferenz zu erweitern. Anhand einer Menge von TD-Dokumenten können neue Beziehungen zwischen Things abgeleitet werden und dadurch neue Interaktionen zwischen denjenigen Agenten, die sich auf diese Things beziehen eingeführt werden. Die im Kapitel 3 beschriebenen Experimente setzen dieses semantische Framework in zwei Domäne um: Gebäudeautomatisierung und Industrielle Kontrollsysteme. Das Erkennen impliziter Beziehungen zwischen Things hängt in bestimmten Fällen von sogenannten anonymen Knoten im Graphen ab: das Kapitel führt einen neuen Skolemization Algorithmus ein, um diese Knoten für einen bestimmten Teil der Web Ontology Language (OWL) korrekt zu verarbeiten. Zum Schluss, da die Umsetzung dieses semantischen Frameworks den Austausch von TD-Dokumenten erfordert, wird im Kapitel 4 ein binäres Format für RDF eingeführt, welches sich als sehr effizient für die Serialisierung erweist, damit auch kleine WoT Agenten, nämlich Mikrocontroller, TD-Dokumente speichern und verarbeiten können. Eine formale Definition für die Verdichtung und die Abfrage von TD-Dokumenten wird in diesem Kapitel eingeführt. Das Kapitel beschreibt auch die Implementierung einer eingebetteten RDF Datenbank, die µRDF Store genannt wurde. Die Fähigkeit WoT-Agenten logische Schlüsse über sich selbst und ihre Umgebung zu ziehen ist der erste Schritt in Richtung eines wissensbasierten intelligenten Systems, das autonom, dynamisch und dezentral agieren kann. Der µRDF Store zeigt die praktischen Vorteile, der in dieser Dissertation entwickelten Theorie für WoT auf. KW - Semantic Web KW - Web of Things KW - Internet of Things KW - Thing Description KW - Web Ontologies KW - Semantic Web KW - Internet der Dinge Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-7578 ER - TY - THES A1 - Wahl, Florian T1 - Methods for monitoring the human circadian rhythm in free-living N2 - Our internal clock, the circadian clock, determines at which time we have our best cognitive abilities, are physically strongest, and when we are tired. Circadian clock phase is influenced primarily through exposure to light. A direct pathway from the eyes to the suprachiasmatic nucleus, where the circadian clock resides, is used to synchronise the circadian clock to external light-dark cycles. In modern society, with the ability to work anywhere at anytime and a full social agenda, many struggle to keep internal and external clocks synchronised. Living against our circadian clock makes us less efficient and poses serious health impact, especially when exercised over a long period of time, e.g. in shift workers. Assessing circadian clock phase is a cumbersome and uncomfortable task. A common method, dim light melatonin onset testing, requires a series of eight saliva samples taken in hourly intervals while the subject stays in dim light condition from 5 hours before until 2 hours past their habitual bedtime. At the same time, sensor-rich smartphones have become widely available and wearable computing is on the rise. The hypothesis of this thesis is that smartphones and wearables can be used to record sensor data to monitor human circadian rhythms in free-living. To test this hypothesis, we conducted research on specialised wearable hardware and smartphones to record relevant data, and developed algorithms to monitor circadian clock phase in free-living. We first introduce our smart eyeglasses concept, which can be personalised to the wearers head and 3D-printed. Furthermore, hardware was integrated into the eyewear to recognise typical activities of daily living (ADLs). A light sensor integrated into the eyeglasses bridge was used to detect screen use. In addition to wearables, we also investigate if sleep-wake patterns can be revealed from smartphone context information. We introduce novel methods to detect sleep opportunity, which incorporate expert knowledge to filter and fuse classifier outputs. Furthermore, we estimate light exposure from smartphone sensor and weather in- formation. We applied the Kronauer model to compare the phase shift resulting from head light measurements, wrist measurements, and smartphone estimations. We found it was possible to monitor circadian phase shift from light estimation based on smartphone sensor and weather information with a weekly error of 32±17min, which outperformed wrist measurements in 11 out of 12 participants. Sleep could be detected from smartphone use with an onset error of 40±48 min and wake error of 42±57 min. Screen use could be detected smart eyeglasses with 0.9 ROC AUC for ambient light intensities below 200lux. Nine clusters of ADLs were distinguished using Gaussian mixture models with an average accuracy of 77%. In conclusion, a combination of the proposed smartphones and smart eyeglasses applications could support users in synchronising their circadian clock to the external clocks, thus living a healthier lifestyle. KW - context recognition KW - human circadian rhythm KW - machine learning KW - sleep timing KW - smart eyeglasses KW - Tagesrhythmus Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-7607 ER - TY - THES A1 - Kronawitter, Stefan T1 - Automatic Performance Optimization of Stencil Codes N2 - A widely used class of codes are stencil codes. Their general structure is very simple: data points in a large grid are repeatedly recomputed from neighboring values. This predefined neighborhood is the so-called stencil. Despite their very simple structure, stencil codes are hard to optimize since only few computations are performed while a comparatively large number of values have to be accessed, i.e., stencil codes usually have a very low computational intensity. Moreover, the set of optimizations and their parameters also depend on the hardware on which the code is executed. To cut a long story short, current production compilers are not able to fully optimize this class of codes and optimizing each application by hand is not practical. As a remedy, we propose a set of optimizations and describe how they can be applied automatically by a code generator for the domain of stencil codes. A combination of a space and time tiling is able to increase the data locality, which significantly reduces the memory-bandwidth requirements: a standard three-dimensional 7-point Jacobi stencil can be accelerated by a factor of 3. This optimization can target basically any stencil code, while others are more specialized. E.g., support for arbitrary linear data layout transformations is especially beneficial for colored kernels, such as a Red-Black Gauss-Seidel smoother. On the one hand, an optimized data layout for such kernels reduces the bandwidth requirements while, on the other hand, it simplifies an explicit vectorization. Other noticeable optimizations described in detail are redundancy elimination techniques to eliminate common subexpressions both in a sequence of statements and across loop boundaries, arithmetic simplifications and normalizations, and the vectorization mentioned previously. In combination, these optimizations are able to increase the performance not only of the model problem given by Poisson’s equation, but also of real-world applications: an optical flow simulation and the simulation of a non-isothermal and non-Newtonian fluid flow. KW - Optimierung KW - Codegenerierung Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-7618 ER - TY - THES A1 - Stadler, Thomas T1 - Eine Anwendung der Invariantentheorie auf das Korrespondenzproblem lokaler Bildmerkmale N2 - Als sich in der ersten Hälfte des 19. Jahrhunderts zunehmend mehr bedeutende Mathematiker mit der Suche nach Invarianten beschäftigten, konnte natürlich noch niemand vorhersehen, dass die Invariantentheorie mit Beginn des Computerzeitalters in der Bildverarbeitung bzw. dem Rechnersehen ein äußerst fruchtbares Anwendungsgebiet finden wird. In dieser Arbeit wird eine neue Anwendungsmöglichkeit der Invariantentheorie in der Bildverarbeitung vorgestellt. Dazu werden lokale Bildmerkmale betrachtet. Dabei handelt es sich um die Koordinaten einer Polynomfunktion bzgl. einer geeigneten Orthonormalbasis von P_n(R^2,R), die die zeitintegrierte Sensorinputfunktion auf lokalen Pixelfenstern bestmöglich approximiert. Diese Bildmerkmale werden in vielen Anwendungen eingesetzt, um Objekte in Bildern zu erkennen und zu lokalisieren. Beispiele hierfür sind die Detektion von Werkstücken an einem Fließband oder die Verfolgung von Fahrbahnmarkierungen in Fahrerassistenzsystemen. Modellieren lässt sich die Suche nach einem Muster in einem Suchbild als Paar von Stereobildern, auf denen lokal die affin-lineare Gruppe AGL(R) operiert. Will man also feststellen, ob zwei lokale Pixelfenster in etwa Bilder eines bestimmten dreidimensionalen Oberflächenausschnitts sind, ist zu klären, ob die Bildausschnitte durch eine Operation der Gruppe AGL(R) näherungsweise ineinander übergeführt werden können. Je nach Anwendung genügt es bereits, passende Untergruppen G von AGL(R) zu betrachten. Dank der lokalen Approximation durch Polynomfunktionen induziert die Operation einer Untergruppe G eine Operation auf dem reellen Vektorraum P_n(R^2,R). Damit lässt sich das Korrespondenzproblem auf die Frage reduzieren, ob es eine Transformation T in G gibt so, dass p ungefähr mit der Komposition von q und T für die zugehörigen Approximationspolynome p,q in P_n(R^2,R) gilt. Mit anderen Worten, es ist zu klären, ob sich p und q näherungsweise in einer G-Bahn befinden, eine typische Fragestellung der Invariantentheorie. Da nur lokale Bildausschnitte betrachtet werden, genügt es weiter, Untergruppen G von GL_2(R) zu betrachten. Dann erhält man sofort auch die Antwort für das semidirekte Produkt von R^2 mit G. Besonders interessant für Anwendungen ist hierbei die spezielle orthogonale Gruppe G=SO_2(R) und damit insgesamt die eigentliche Euklidische Gruppe. Für diese Gruppe und spezielle Pixelfenster ist das Korrespondenzproblem bereits gelöst. In dieser Arbeit wird das Problem in eben dieser Konstellation ebenfalls gelöst, allerdings auf elegante Weise mit Methoden der Invariantentheorie. Der Ansatz, der hier vorgestellt wird, ist aber nicht auf diese Gruppe und spezielle Pixelfenster begrenzt, sondern leicht auf weitere Fälle erweiterbar. Dazu ist insbesondere zu klären, wie sich sogenannte fundamentale Invarianten von lokalen Bildmerkmalen, also letztendlich Invarianten von Polynomfunktionen, berechnen lassen, d.h. Erzeugendensysteme der entsprechenden Invariantenringe. Mit deren Hilfe lässt sich die Zugehörigkeit einer Polynomfunktion zur Bahn einer anderen Funktion auf einfache Weise untersuchen. Neben der Vorstellung des Verfahrens zur Korrespondenzfindung und der dafür notwendigen Theorie werden in dieser Arbeit Erzeugendensysteme von Invariantenringen untersucht, die besonders "schöne" Eigenschaften besitzen. Diese schönen Erzeugendensysteme von Unteralgebren werden, analog zu Gröbner-Basen als Erzeugendensysteme von Idealen, SAGBI-Basen genannt ("Subalgebra Analogs to Gröbner Bases for Ideals"). SAGBI-Basen werden hier insbesondere aus algorithmischer Sicht behandelt, d.h. die Berechnung von SAGBI-Basen steht im Vordergrund. Dazu werden verschiedene Algorithmen erarbeitet, deren Korrektheit bewiesen und implementiert. Daraus resultiert ein Software-Paket zu SAGBI-Basen für das Computeralgebrasystem ApCoCoA, dessen Funktionalität in diesem Umfang in keinem Computeralgebrasystem zu finden sein wird. Im Zuge der Umsetzung der einzelnen Algorithmen konnte außerdem die Theorie der SAGBI-Basen an zahlreichen Stellen erweitert werden. KW - Computeralgebra KW - SAGBI-Basen KW - Invariantentheorie KW - Bildverarbeitung KW - (lokale) Bildmerkmale Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-4026 ER - TY - THES A1 - de Ponte Müller, Fabian T1 - Cooperative Relative Positioning for Vehicular Environments N2 - Fahrerassistenzsysteme sind ein wesentlicher Baustein zur Steigerung der Sicherheit im Straßenverkehr. Vor allem sicherheitsrelevante Applikationen benötigen eine genaue Information über den Ort und der Geschwindigkeit der Fahrzeuge in der unmittelbaren Umgebung, um mögliche Gefahrensituationen vorherzusehen, den Fahrer zu warnen oder eigenständig einzugreifen. Repräsentative Beispiele für Assistenzsysteme, die auf eine genaue, kontinuierliche und zuverlässige Relativpositionierung anderer Verkehrsteilnehmer angewiesen sind, sind Notbremsassitenten, Spurwechselassitenten und Abstandsregeltempomate. Moderne Lösungsansätze benutzen Umfeldsensorik wie zum Beispiel Radar, Laser Scanner oder Kameras, um die Position benachbarter Fahrzeuge zu schätzen. Dieser Sensorsysteme gemeinsame Nachteile sind deren limitierte Erfassungsreichweite und die Notwendigkeit einer direkten und nicht blockierten Sichtlinie zum Nachbarfahrzeug. Kooperative Lösungen basierend auf einer Fahrzeug-zu-Fahrzeug Kommunikation können die eigene Wahrnehmungsreichweite erhöhen, in dem Positionsinformationen zwischen den Verkehrsteilnehmern ausgetauscht werden. In dieser Dissertation soll die Möglichkeit der kooperativen Relativpositionierung von Straßenfahrzeugen mittels Fahrzeug-zu-Fahrzeug Kommunikation auf ihre Genauigkeit, Kontinuität und Robustheit untersucht werden. Anstatt die in jedem Fahrzeug unabhängig ermittelte Position zu übertragen, werden in einem neuartigem Ansatz GNSS-Rohdaten, wie Pseudoranges und Doppler-Messungen, ausgetauscht. Dies hat den Vorteil, dass sich korrelierte Fehler in beiden Fahrzeugen potentiell herauskürzen. Dies wird in dieser Dissertation mathematisch untersucht, simulativ modelliert und experimentell verifiziert. Um die Zuverlässigkeit und Kontinuität auch in "gestörten" Umgebungen zu erhöhen, werden in einem Bayesischen Filter die GNSS-Rohdaten mit Inertialsensormessungen aus zwei Fahrzeugen fusioniert. Die Validierung des Sensorfusionsansatzes wurde im Rahmen dieser Dissertation in einem Verkehrs- sowie in einem GNSS-Simulator durchgeführt. Zur experimentellen Untersuchung wurden zwei Testfahrzeuge mit den verschiedenen Sensoren ausgestattet und Messungen in diversen Umgebungen gefahren. In dieser Arbeit wird gezeigt, dass auf Autobahnen, die Relativposition eines anderen Fahrzeugs mit einer Genauigkeit von unter einem Meter kontinuierlich geschätzt werden kann. Eine hohe Zuverlässigkeit in der longitudinalen und lateralen Richtung können erzielt werden und das System erweist 90% der Zeit eine Unsicherheit unter 2.5m. In ländlichen Umgebungen wächst die Unsicherheit in der relativen Position. Mit Hilfe der on-board Sensoren können Fehler bei der Fahrt durch Wälder und Dörfer korrekt gestützt werden. In städtischen Umgebungen werden die Limitierungen des Systems deutlich. Durch die erschwerte Schätzung der Fahrtrichtung des Ego-Fahrzeugs ist vor Allem die longitudinale Komponente der Relativen Position in städtischen Umgebungen stark verfälscht. N2 - Advanced driver assistance systems play an important role in increasing the safety on today's roads. The knowledge about the other vehicles' positions is a fundamental prerequisite for numerous safety critical applications, making it possible to foresee critical situations, warn the driver or autonomously intervene. Forward collision avoidance systems, lane change assistants or adaptive cruise control are examples of safety relevant applications that require an accurate, continuous and reliable relative position of surrounding vehicles. Currently, the positions of surrounding vehicles is estimated by measuring the distance with e.g. radar, laser scanners or camera systems. However, all these techniques have limitations in their perception range, as all of them can only detect objects in their line-of-sight. The limited perception range of today's vehicles can be extended in future by using cooperative approaches based on Vehicle-to-Vehicle (V2V) communication. In this thesis, the capabilities of cooperative relative positioning for vehicles will be assessed in terms of its accuracy, continuity and reliability. A novel approach where Global Navigation Satellite System (GNSS) raw data is exchanged between the vehicles is presented. Vehicles use GNSS pseudorange and Doppler measurements from surrounding vehicles to estimate the relative positioning vector in a cooperative way. In this thesis, this approach is shown to outperform the absolute position subtraction as it is able to effectively cancel out common errors to both GNSS receivers. This is modeled theoretically and demonstrated empirically using simulated signals from a GNSS constellation simulator. In order to cope with GNSS outages and to have a sufficiently good relative position estimate even in strong multipath environments, a sensor fusion approach is proposed. In addition to the GNSS raw data, inertial measurements from speedometers, accelerometers and turn rate sensors from each vehicle are exchanged over V2V communication links. A Bayesian approach is applied to consider the uncertainties inherently to each of the information sources. In a dynamic Bayesian network, the temporal relationship of the relative position estimate is predicted by using relative vehicle movement models. Also real world measurements in highway, rural and urban scenarios are performed in the scope of this work to demonstrate the performance of the cooperative relative positioning approach based on sensor fusion. The results show that the relative position of another vehicle towards the ego vehicle can be estimated with sub-meter accuracy in highway scenarios. Here, good reliability and 90% availability with an uncertainty of less than 2.5m is achieved. In rural environments, drives through forests and towns are correctly bridged with the support of on-board sensors. In an urban environment, the difficult estimation of the ego vehicle heading has a mayor impact in the relative position estimate, yielding large errors in its longitudinal component. KW - Fahrerassistenzsystem Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-5411 ER - TY - THES A1 - Fischer, Andreas T1 - An Evaluation Methodology for Virtual Network Embedding N2 - The increasing scale and complexity of computer networks imposes a need for highly flexible management mechanisms. The concept of network virtualization promises to provide this flexibility. Multiple arbitrary virtual networks can be constructed on top of a single substrate network. This allows network operators and service providers to tailor their network topologies to the specific needs of any offered service. However, the assignment of resources proves to be a problem. Each newly defined virtual network must be realized by assigning appropriate physical resources. For a given set of virtual networks, two questions arise: Can all virtual networks be accommodated in the given substrate network? And how should the respective resources be assigned? The underlying problem is commonly known as the Virtual Network Embedding problem. A multitude of algorithms has already been proposed, aiming to provide solutions to that problem under various constraints. For the evaluation of these algorithms typically an empirical approach is adopted, using artificially created random problem instances. However, due to complex effects of random problem generation the obtained results can be hard to interpret correctly. A structured evaluation methodology that can avoid these effects is currently missing. This thesis aims to fill that gap. Based on a thorough understanding of the problem itself, the effects of random problem generation are highlighted. A new simulation architecture is defined, increasing the flexibility for experimentation with embedding algorithms. A novel way of generating embedding problems is presented which migitates the effects of conventional problem generation approaches. An evaluation using these newly defined concepts demonstrates how new insights on algorithm behavior can be gained. The proposed concepts support experimenters in obtaining more precise and tangible evaluation data for embedding algorithms. KW - Virtual Network Embedding KW - Empirical Evaluation KW - Network Virtualization KW - Experimental Algorithmics KW - Virtuelles Netz KW - Virtualisierung KW - Algorithmus KW - Virtuelles Netz KW - Kombinatorische Einbettung Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:739-opus4-4793 ER -