Universität Stuttgart

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    Inferring object hypotheses based on feature motion from different sources
    (2015) Fuchs, Steffen
    Perception systems in robotics are typically closely tailored to the given task, e.g., in typical pick-and-place tasks the perception systems only recognizes the mugs that are supposed to be moved and the table the mugs are placed on. The obvious limitation of those systems is that for a new task a new vision system must be designed and implemented. This master's thesis proposes a method that allows to identify entities in the world based on motion of various features from various sources. This is without relying on strong prior assumptions and to provide an important piece towards a more general perception system. While entities are rigid bodies in the world, the sources can be anything that allows to track certain features over time in order to create trajectories. For example, these feature trajectories can be obtained from RGB and RGB-D sensors of a robot, from external cameras, or even the end effector of the robot (proprioception). The core conceptual elements are: the distance variance between trajectory pairs is computed to construct an affinity matrix. This matrix is then used as input for a divisive k-means algorithm in order to cluster trajectories into object hypotheses. In a final step these hypotheses are combined with previously observed hypotheses by computing the correlations between the current and the updated sets. This approach has been evaluated on both simulated and real world data. Generating simulated data provides an elegant way for a qualitative analysis of various scenarios. The real world data was obtained by tracking Shi-Tomasi corners using the Lucas-Kanade optical flow estimation of RGB image sequences and projecting the features into range image space.
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    Control-plane consistency in software-defined networking: distributed controller synchronization using the ISIS² toolkit
    (2015) Strauß, Jan
    Software-defined Networking (SDN) is a recent approach in computer networks to ease the network administration by separating the control-plane and the data-plane. The data-plane only forwards packets according to certain rules specified by the control-plane. The control-plane, implemented by a software called controller, determines the forwarding rules based on a global view of the network. In order to increase fault tolerance and to eliminate a possible performance bottleneck, the controller can be distributed. The synchronization of the data that holds the global view is conventionally realized using distributed key-value stores offering a fixed consistency semantic, not respecting the heterogeneous consistency requirements of the data items in controller state. The virtual synchrony model, an alternative approach to the commonly used state machine replication method, offers a more flexible solution that can result in higher performance when certain assumptions on the data kept in controller state can be made. In this thesis a distributed controller based on OpenDaylight, a state-of-the-art SDN controller and the ISIS² library, that implements the virtual synchrony model, is proposed. The modular architecture of the proposed controller and the usage of a platform independent data model allows to extend or replace parts of the system. The implementation of the distributed controller is described and the macro and micro performance is evaluated with benchmarks.
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    Lastbalancierungsverfahren für dynamische und heterogene Linked-Cell Molekülsimulation
    (2015) Hirschmann, Steffen
    In dieser Arbeit wird die Lastbalancierung von Molekül- beziehungsweise Teilchensimulationen mit kurzreichweitigen Potenzialen betrachtet. Eine solche ist notwendig, um inhomogene Szenarien effizient über längere Zeiträume hinweg auf Parallelrechnern simulieren zu können. Hierzu werden die vorkommenden Arten von Last analysiert und in sogenannten Lastmodellen quantifiziert. Hierbei liegt der Fokus auf Rechen- und Kommunikationslasten. Anschließend wird das Problem der Lastbalancierung beschrieben. Es werden verschiedene in der Literatur bekannte Verfahren zur Lastbalancierung betrachtet, untersucht und evaluiert. Der Fokus liegt hierbei nicht auf einem einzelnen Anwendungsszenario, sondern auf der generellen Machbarkeit, den Eigenschaften und den Einschränkungen der jeweiligen Verfahren.
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    Robust Quasi-Newton methods for partitioned fluid-structure simulations
    (2015) Scheufele, Klaudius
    In recent years, quasi-Newton schemes have proven to be a robust and efficient way for the coupling of partitioned multi-physics simulations in particular for fluid-structure interaction. The focus of this work is put on the coupling of partitioned fluid-structure interaction, where minimal interface requirements are assumed for the respective field solvers, thus treated as black box solvers. The coupling is done through communication of boundary values between the solvers. In this thesis a new quasi-Newton variant (IQN-IMVJ) based on a multi-vector update is investigated in combination with serial and parallel coupling systems. Due to implicit incorporation of passed information within the Jacobian update it renders the problem dependent parameter of retained previous time steps unnecessary. Besides, a whole range of coupling schemes are categorized and compared comprehensively with respect to robustness, convergence behaviour and complexity. Those coupling algorithms differ in the structure of the coupling, i.\,e., serial or parallel execution of the field solvers and the used quasi-Newton methods. A more in-depth analysis for a choice of coupling schemes is conducted for a set of strongly coupled FSI benchmark problems, using the in-house coupling library preCICE. The superior convergence behaviour and robust nature of the IQN-IMVJ method compared to well known state of the art methods such as the IQN-ILS method, is demonstrated here. It is confirmed that the multi-vector method works optimal without the need of tuning problem dependent parameters in advance. Furthermore, it appears to be especially suitable in conjunction with the parallel coupling system, in that it yields fairly similar results for parallel and serial coupling. Although we focus on FSI simulation, the considered coupling schemes are supposed to be equally applicable to various kinds of different volume- or surface-coupled problems.
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    Eine OSLC-Plattform zur Unterstützung der Situationserkennung in Workflows
    (2015) Jansa, Paul
    Das Internet der Dinge gewinnt immer mehr an Bedeutung durch eine starke Vernetzung von Rechnern, Produktionsanlagen, mobilen Endgeräten und weiteren technischen Geräten. Derartige vernetzte Umgebungen werden auch als SMART Environments bezeichnet. Auf Basis von Sensordaten können in solchen Umgebungen höherwertige Situationen (Zustandsänderungen) erkannt und auf diese meist automatisch reagiert werden. Dadurch werden neuartige Technologien wie zum Beispiel "Industrie 4.0", "SMART Homes" oder "SMART Cities" ermöglicht. Komplexe Vernetzungen und Arbeitsabläufe in derartigen Umgebungen werden oftmals mit Workflows realisiert. Um eine robuste Ausführung dieser Workflows zu gewährleisten, müssen Situationsänderungen beachtet und auf diese entsprechend reagiert werden, zum Beispiel durch Workflow-Adaption. Das heißt, erst durch die Erkennung höherwertiger Situationen können solche Workflows robust modelliert und ausgeführt werden. Jedoch stellen die für die Erkennung von Situationen notwendige Anbindung und Bereitstellung von Sensordaten eine große Herausforderung dar. Oft handelt es sich bei den Sensordaten um Rohdaten. Sie sind schwer extrahierbar, liegen oftmals nur lokal vor, sind ungenau und lassen sich dementsprechend schwer verarbeiten. Um die Sensordaten zu extrahieren, müssen für jeden Sensor individuelle Adapter programmiert werden, die wiederum ein einheitliches Datenformat der Sensordaten bereitstellen müssen und anschließend mit sehr viel Aufwand untereinander verbunden werden. Im Rahmen dieser Diplomarbeit wird ein Konzept erarbeitet und entwickelt, mit dessen Hilfe eine einfache Integration von Sensordaten ermöglicht wird. Dazu werden die Sensoren über eine webbasierte Benutzeroberfläche oder über eine programmatische Schnittstelle in einer gemeinsamen Datenbank registriert. Die Sensordaten werden durch REST-Ressourcen abstrahiert, in RDF-basierte Repräsentationen umgewandelt und mit dem Linked-Data Prinzip miteinander verbunden. Durch die standardisierte Schnittstelle können Endbenutzer oder Anwendungen über das Internet auf die Sensordaten zugreifen, neue Sensoren anmelden oder entfernen.
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    Position sharing for location privacy in non-trusted systems
    (2015) Skvortsov, Pavel; Rothermel, Kurt (Prof. Dr. rer. nat. Dr. h.c.)
    Currently, many location-aware applications are available for mobile users of location-based services. Applications such as Google Now, Trace4You or FourSquare are being widely used in various environments where privacy is a critical issue for users. A general solution for preserving location privacy for a user is to degrade the quality of his or her position information. In this work, we propose an approach that uses spatial obfuscation to secure the users’ position information. By revealing the user’s position with a certain degree of obfuscation, the first crucial issue is the tradeoff between privacy and precision. This tradeoff problem is caused by limited trust in the location service providers: higher obfuscation increases privacy but leads to lower quality of service. We overcome this problem by introducing the position sharing approach. Our main idea is that position information is distributed amongst multiple providers in the form of separate data pieces called position shares. Our approach allows for the usage of non-trusted providers and flexibly manages the user’s location privacy level based on probabilistic privacy metrics. In this work, we present the multi-provider based position sharing approach, which includes algorithms for the generation of position shares and share fusion algorithms. The second challenge that must be addressed is that the user’s environmental context can significantly decrease the level of obfuscation. For example, a plane, a boat and a car create different requirements for the obfuscated region. Therefore, it is very important to consider map-awareness in selecting the obfuscated areas. We assume that a static map is known to an adversary, which may help in deriving the user’s true position. We analyze both how map-awareness affects the generation and fusion of position shares and the difference between the map-aware position sharing approach and its open space based version. Our security analysis shows that the proposed position sharing approach provides good security guarantees for both open space and constrained space based models. The third challenge is that multiple location servers and/or their providers may have different trustworthiness from the user’s point of view. In this case, the user would prefer not to reveal an equal level (precision) of position information to every server. We propose a placement optimization approach that ensures that risk is balanced among the location servers according to their individual trust levels. Our evaluation shows significant improvement of privacy guarantees after applying the optimized share distribution, in comparison with the equal share distribution. The fourth related problem is the location update algorithm. A high number of different location servers n (corresponding to n privacy levels) may lead to significant communication overhead. Each update would require n messages from the mobile user to the location servers, especially in cases of high update rate. Therefore, we propose an optimized location update algorithm to decrease the number of messages sent without reducing the number of privacy levels and the user’s privacy.
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    Distributed graph processing and partitioning for spatiotemporal queries in the context of camera networks
    (2015) Maaß, Steffen
    This work presents a scalable, distributed architecture for processing spatiotemporal queries in the context of camera networks based on a graph structure. With the ever-increasing presence of cameras and the emergence of camera-networks, e.g., in the context of campus security, it becomes increasingly important to provide a robust and scalable architecture to store and retrieve detected events. In this work a distributed graph processing engine will be presented which is well suited for read and write tasks in the environment of spatiotemporal image-similarity based workloads. The key ideas presented in this work are the architecture of a scalable graph processing system well-suited for processing spatio-temporal queries and the design of a distributed and robust vertex-partitioning strategy for the graph which is being defined by the spatiotemporal attributes of the stored events. The work will show multiple lightweight heuristics for partitioning the graph among the nodes participating in the system, focusing on load-balancing between workers and high edge-locality for vertices. The system and the partitioning strategies will be evaluated, showing that the system scales with the number of workers and the problem size and is able to answer proportionally more queries per second. It will also be shown that the lightweight heuristics for partitioning the graph produce a relatively good balancing of the vertices on the worker-nodes and can be executed in an online-fashion, resulting in similar performance when compared to a traditional hash-partitioning while providing far superior edge-locality.
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    Design and implementation of TOSCA Service Templates for provisioning and executing bone simulation in cloud environments
    (2015) Dehghanipour, Marzieh
    Recent years have shown an increasing trend to move applications and services into cloud infrastructures. Cloud-based applications typically consist of distributed components which are connected and communicate with each other. Automating the deployment and management of these components is one of the major challenges in IT world. The OASIS TOSCA standard provides a meta-model for describing the structure of composite cloud-based applications, which provides automation for deployment and management of these applications. TOSCA-based applications may be executed via the OpenTOSCA (a run-time environment for TOSCA-based applications) environment, which has been developed by the University of Stuttgart. Simulation applications deal with heterogeneous and huge data sources. Adequate data management and data provisioning for these applications are some of the most significant challenges for simulation applications. SIMPL is a framework which provides a generic approach for data management and data provisioning in simulation applications. SIMPL frees users to deal with any low-level details of data sources and corresponding data management operations. Both the TOSCA standard and the SIMPL framework are based on workflows. The first goal of this master's thesis is to combine the TOSCA standard with the SIMPL framework in order to enable the generic data provisioning and data management approach offered by SIMPL as an integral part of the TOSCA standard. A further and main part of this work is to design and implement TOSCA Service Templates for provisioning and executing bone simulations in cloud environments. Different variants of a TOSCA Service Template realizing a bone simulation in a cloud-native way have to be developed and implemented. In other words, a SaaS solution for PANDAS bone simulation is provided in the scope of this master's thesis with the help of TOSCA and SIMPL technologies.
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    Distributed stream processing in a global sensor grid for scientific simulations
    (2015) Benzing, Andreas; Rothermel, Kurt (Prof. Dr. rer. nat)
    With today's large number of sensors available all around the globe, an enormous amount of measurements has become available for integration into applications. Especially scientific simulations of environmental phenomena can greatly benefit from detailed information about the physical world. The problem with integrating data from sensors to simulations is to automate the monitoring of geographical regions for interesting data and the provision of continuous data streams from identified regions. Current simulation setups use hard coded information about sensors or even manual data transfer using external memory to bring data from sensors to simulations. This solution is very robust, but adding new sensors to a simulation requires manual setup of the sensor interaction and changing the source code of the simulation, therefore incurring extremely high cost. Manual transmission allows an operator to drop obvious outliers but prohibits real-time operation due to the long delay between measurement and simulation. For more generic applications that operate on sensor data, these problems have been partially solved by approaches that decouple the sensing from the application, thereby allowing for the automation of the sensing process. However, these solutions focus on small scale wireless sensor networks rather than the global scale and therefore optimize for the lifetime of these networks instead of providing high-resolution data streams. In order to provide sensor data for scientific simulations, two tasks are required: i) continuous monitoring of sensors to trigger simulations and ii) high-resolution measurement streams of the simulated area during the simulation. Since a simulation is not aware of the deployed sensors, the sensing interface must work without an explicit specification of individual sensors. Instead, the interface must work only on the geographical region, sensor type, and the resolution used by the simulation. The challenges in these tasks are to efficiently identify relevant sensors from the large number of sources around the globe, to detect when the current measurements are of relevance, and to scale data stream distribution to a potentially large number of simulations. Furthermore, the process must adapt to complex network structures and dynamic network conditions as found in the Internet. The Global Sensor Grid (GSG) presented in this thesis attempts to close this gap by approaching three core problems: First, a distributed aggregation scheme has been developed which allows for the monitoring of geographic areas for sensor data of interest. The reuse of partial aggregates thereby ensures highly efficient operation and alleviates the sensor sources from individually providing numerous clients with measurements. Second, the distribution of data streams at different resolutions is achieved by using a network of brokers which preprocess raw measurements to provide the requested data. The load of high-resolution streams is thereby spread across all brokers in the GSG to achieve scalability. Third, the network usage is actively minimized by adapting to the structure of the underlying network. This optimization enables the reduction of redundant data transfers on physical links and a dynamic modification of the data streams to react to changing load situations.
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    Wohin mit der Arbeit?: Fehlertoleranz durch gezielte Workflow-Replikation
    (2015) Geiger, Chris
    In den letzten zehn Jahren hat die Anzahl der mobilen Endgeräte ein enormes Wachstum erlebt. Jeder zweite Mensch in Deutschland verwendet ein mobiles Endgerät, sei es um E-Mails zu schreiben, im Internet zu surfen, oder gar um die eigens entwickelten Apps auszuführen. Um irgendeine Art von Anwendung erfolgreich ausführen zu können, muss diese Prozesse ausführen. Meist ist das nicht nur ein Prozess sondern tausende, oder gar zehn tausende. Die Anwendung muss also einen Workflow, eine Verkettung von Prozessen, ausführen. Die einzelnen Prozesse des Workflows rufen meistens einen Service auf, um ihre Funktion zu erfüllen und die gewünschten Daten zu erhalten. Dieser Service kann über das Internet, direkt über Bluetooth, oder über ein anderes Netzwerk erreichbar sein. Da heutzutage die meisten Anwendungen auch von unterwegs ausgeführt werden, ergeben sich neue Probleme. Das mobile Endgerät könnte die Verbindung zum Netz verlieren, wodurch der gerade auszuführende Prozess keine Verbindung mehr zum erforderlichen Service herstellen könnte. Auch ein leerer Akku würde die weitere Ausführung des Workflows unmöglich machen. Um die weitere Ausführung eines Workflows dennoch zu gewährleisten, werden Replikate des Workflows auf andere mobile Endgeräte, sowie feste Instanzen, zum Beispiel Server, verteilt. Da eine optimale Verteilung der Replikate unter realen Bedingungen nicht in einer akzeptablen Zeit zu berechnen ist, werden andere Lösungsansätze gesucht. Diese Arbeit soll Heuristiken einführen, die sich dieses Problems annehmen und somit zur hohen Verfügbarkeit von Workflows beitragen. Diese Heuristiken sollen eine möglichst effiziente Verteilung der Replikate in einer kurzen Zeit erzielen.