Universität Stuttgart
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Item Open Access Eine OSLC-Plattform zur Unterstützung der Situationserkennung in Workflows(2015) Jansa, PaulDas 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.Item Open Access Inferring object hypotheses based on feature motion from different sources(2015) Fuchs, SteffenPerception 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.Item Open Access Robust Quasi-Newton methods for partitioned fluid-structure simulations(2015) Scheufele, KlaudiusIn 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.Item Open Access Control-plane consistency in software-defined networking: distributed controller synchronization using the ISIS² toolkit(2015) Strauß, JanSoftware-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.Item Open Access Design and implementation of TOSCA Service Templates for provisioning and executing bone simulation in cloud environments(2015) Dehghanipour, MarziehRecent 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.Item Open Access Lastbalancierungsverfahren für dynamische und heterogene Linked-Cell Molekülsimulation(2015) Hirschmann, SteffenIn 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.Item Open Access 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.Item Open Access Supporting multi-tenancy in Relational Database Management Systems for OLTP-style software as a service applications(2015) Schiller, Oliver; Mitschang, Bernhard (Prof. Dr.-Ing. habil.)The consolidation of multiple tenants onto a single relational database management system (RDBMS) instance, commonly referred to as multi-tenancy, turned out being beneficial since it supports improving the profit margin of the provider and allows lowering service fees, by what the service attracts more tenants. So far, existing solutions create the required multi-tenancy support on top of a traditional RDBMS implementation, i. e., they implement data isolation between tenants, per-tenant customization and further tenant-centric data management features in application logic. This is complex, error-prone and often reimplements efforts the RDBMS already offers. Moreover, this approach disables some optimization opportunities in the RDBMS and represents a conceptual misstep with Separation of Concerns in mind. For the points mentioned, an RDBMS that provides support for the development and operation of a multi-tenant software as a service (SaaS) offering is compelling. In this thesis, we contribute to a multi-tenant RDBMS for OLTP-style SaaS applications by extending a traditional disk-oriented RDBMS architecture with multi-tenancy support. For this purpose, we primarily extend an RDBMS by introducing tenants as first-class database objects and establishing tenant contexts to isolate tenants logically. Using these extensions, we address tenant-aware schema management, for which we present a schema inheritance concept that is tailored to the needs of multi-tenant SaaS applications. Thereafter, we evaluate different storage concepts to store a tenant’s tuples with respect to their scalability. Next, we contribute an architecture of a multi-tenant RDBMS cluster for OLTP-style SaaS applications. At that, we focus on a partitioning solution which is aligned to tenants and allows obtaining independently manageable pieces. To balance load in the proposed cluster architecture, we present a live database migration approach, whose design favors low migration overhead and provides minimal interruption of service.Item Open Access Design and implementation of a domain specific language for defining ECM workloads in elastic cloud environments using TOSCA(2015) Kukhtichev, SergeyEach year the volume of the content produced by enterprises increases by 35%-50%. Most of this information is stored by companies as unstructured data. Organizations implement Enterprise Content Management (ECM) to structure content and to mitigate legal risks. ECM includes strategies and tools for increasing the effectiveness of content management. Using the right ECM components is one of the factors for successful implementation of ECM. There is a gap between business customers who implement ECM strategies and ECM architects and cloud providers, who create and deploy ECM solutions. On the one side, there are no generally accepted terms, which precisely describe the ECM domain. Different developers of the ECM systems could use the same name for ECM components, which implement different functionality, or they could use different names for ECM components with similar functionality. On the other side, each customer has unique workloads for Enterprise Content Management. ECM architects have to define these workloads and deploy an ECM solution that will fulfill the customer's requirements. The goal of the Thesis is to develop a DSL for ECM domain, which will be understandable by business customers, ECM architects and cloud providers. The language should define terms and workloads that are related to the ECM domain. The business customers should be able to create a description of the requirements to ECM solution using a language that they understand. The ECM architect should be able to define the ECM related terms and associated workloads from the customer's description, design a topology, and publish it in a specialized catalog. The cloud provider should be able to map the high level topology to the exact infrastructure.Item Open Access Packet scheduling algorithms for a software-defined manufacturing environment(2015) Roy Chowdhury, SujataWith the vision of Industry 4.0, Internet of things (IoT) and Internet of Services (IoS) are making their way to the modern manufacturing systems and industrial automation. As a consequence, modern day manufacturing systems need wider product variation and customization to meet the customer's demands and survive in the competitive markets. Traditional, dedicated systems like assembly lines cannot adapt the rapidly changing requirement of today's manufacturing industries. A flexible and highly scalable infrastructure is needed to support such systems. However, most of the applications in manufacturing systems require strict QoS guarantees. For instance, time-sensitive networks like in industrial automation and smart factories need hard real-time guarantees. Deterministic networks with bounded delay and jitter are essential requirement for such systems. To support such systems, non-deterministic queueing delay has to be eliminated from the network. To this end, we present Time-Sensitive Software-Defined Networks (TSSDN) with a logically centralized controller which computes transmission schedules based on the global view of the network. SDN control logic computes optimized transmission schedules for the end hosts to avoid in network queueing delay. To compute transmission schedules, we present Integer Linear Programming and Routing and Scheduling Algorithms with heuristics that schedule and route unicast and multicast flows. Our evaluations show that it is possible to compute near optimal transmission schedules for TSSDN and bound network delays and jitter.