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The usage of high-level synthesis (HLS) tools for FPGAs has increased significantly over the last years since they matured and allow software programmers to take advantage of reconfigurable hardware technology.
Most HLS tools employ methods to optimize for loops, e. g. by unrolling or pipelining them. But there is hardly any work on the optimization of while loops. This comes at no surprise since most while loops have loop-carried dependences involving the loop condition which result in large recurrence cycles in the dataflow graphs. Therefore typical while loops cannot be parallelized or pipelined.
We propose a novel transformation which allows to optimize while loops nested within a for loop. By interchanging the two loops, it is possible to pipeline (and thereby parallelize) the inner loop, resulting in a reduced execution time. We present two case studies on different hardware platforms and show the speedup factors - compared to a host processor and to an unoptimized hardware implementation - achieved by our while loop optimization method.
Es ist davon auszugehen, dass weltweit etwa die Hälfte der industriell eingesetzten Wärme als Abwärme ungenutzt verloren geht (Quelle: Effiziente Energieversorgung durch Abwärme, Fachmagazin Energy 2.0, April 2012). Vor dem Hintergrund der Nachhaltigkeit und Energieeffizienz ist es eine verantwortungsvolle Aufgabe, diese ungenutzte Energieressource schrittweise zu erschließen. Für die bisherige Vernachlässigung verfügbarer Energiequellen gibt es spezifische Gründe, die erkannt und projektbezogen möglichst ausgeräumt werden müssen. Dazu hat die Hochschule Osnabrück in Kooperation mit dem Kompetenzzentrum Energie und dem Landkreis Osnabrück eine Studie erstellt.
Regionales Wärmekataster Industrie - ReWIn
Diese Konzeptstudie schafft durch eine vorangestellte Recherche der bereits entwickelten Methoden und Technologien zur Abwärmenutzung eine Grundlage zur Potenzialabschätzung und Aufstellung eines Wärmekatasters für den Landkreis Osnabrück.
In der Studie werden für die typisch energieintensiven Branchen des Landkreises methodische Berechnungsansätze mit statistischen, branchenbezogenen Energiekennwerten und vorerst anonymisierten Unternehmensdaten neuartig kombiniert, um eine regionale Potenzialkarte der Abwärme zu erstellen. Die Studie wurde vom Europäischen Fonds für regionale Entwicklung (EFRE) gefördert.
This paper presents an optimized algorithm for estimating static and dynamic gait parameters. We use a marker- and contact-less motion capture system that identifies 20 joints of a person walking along a corridor.
Based on the proposed gait cycle detection basic metrics as walking frequency, step/stride length, and support phases are estimated automatically. Applying a rigid body model, we are capable to calculate static and dynamic gait stability metrics. We conclude with initial results of a clinical study evaluating orthopaedic technical support.
Der Einsatz paralleler Hardware-Architekturen betrifft alle Software-Entwickler und -Entwicklerinnen: vom Supercomputer bis zum eingebetteten System werden Multi- und Manycore-Systeme inzwischen eingesetzt. Die Herausforderungen an das Software Engineering sind vielfältig. Zum einen ist (wieder) ein stärkeres Verständnis für die Hardware notwendig. Ohne eine skalierbare Partitionierung der Software und parallele Algorithmen bleibt die Rechenleistung ungenutzt. Zum anderen stehen neue Programmiersprachen im Vordergrund, die die Ausführung von parallelen Anweisungen ermöglichen.
Dieses Buch betrachtet unterschiedliche Aspekte bei der Entwicklung paralleler Systeme und berücksichtigt dabei auch eingebettete Systeme. Es verbindet Theorie und praktische Anwendung und ist somit für Studierende und Anwender in der Praxis gleichermaßen geeignet. Durch die programmiersprachenunabhängige Darstellung der Algorithmen können sie leicht für die eigene Anwendung angepasst werden. Viele praktische Projekte erleichtern das Selbststudium und vertiefen das Gelernte.
he development of context-aware applications is a difficult and error-prone task. The dynamics of the environmental context combined with the complexity of the applications poses a vast number of possibilities for mistakes during the creation of new applications. Therefore it is important to test applications before they are deployed in a life system. For this reason, this paper proposes a testing tool, which will allow for automatic generation of various test cases from application description documents. Semantic annotations are used to create specific test data for context-aware applications. A test case reduction methodology based on test case diversity investigations ensures scalability of the proposed automated testing approach.
In this experimental work, the quasi static and fatigue properties of a 40 wt.% long carbon fiber reinforced partially aromatic polyamide (Grivory GCL-4H) were investigated. For this purpose, microstructural parameter variations in the form of different thicknesses and different removal directions from injectionmolded plates were evaluated. Mechanical properties decreased by increasing misalignment away from the melt flow direction. By changing the specimen thickness, no change in the general fiber distribution pattern transversal and normal to the axis of melt flow was observed. It has shown that with increasing specimen thickness the quasi static properties along the melt flow direction decreased and vice versa resulting in superior properties normal to the melt flow axis. At around 5 mm, an intersection suggests quasi-isotropic behavior. In addition, the fatigue strength of the material was significantly higher in the flow direction than normal to the flow direction. No change in fatigue life was observed while changing specimen thickness. The Basquin equation seems to describe the effect of stress amplitude on the fatigue strength of this composite. Scanning electron microscopy was used to investigate fracture surfaces of tested specimens. Results show that mechanical properties and morphological structures depend highly on fiber orientation.
With the increasing size and complexity of embedded systems, the impact of software on energy consumption is becoming more important. Previous research focused mainly on energy optimization at the hardware level. However, little research has been carried out regarding energy optimization at the software design level. This paper focuses on the software design level and addresses the gap between software and hardware design for embedded systems. This is achieved by proposing a framework for software design patterns, which takes aspects of power consumption and time behavior of the hardware level into account. We evaluate the expressiveness of the framework by applying it to well-known and novel design patterns. Furthermore, we introduce a dimensionless numerical efficiency factor to make possible energy savings quantifiable.
Due to the resource-constrained nature of embedded systems, it is crucial to support the estimation of their power consumption as early in the development process as possible. Non-functional requirements based on power consumption directly impact the software design, e.g., watt-hour thresholds and expected lifetimes based on battery capacities. Even if software affects hardware behavior directly, these types of requirements are often overlooked by software developers because they are commonly associated with the hardware layer. Modern trends in software engineering such as Model-Driven Development (MDD) can be used in embedded software development to evaluate power consumption-based requirements in early design phases. However, power consumption aspects are currently not sufficiently considered in MDD approaches. In this paper, we present a model-driven approach using Unified Modeling Language profile extensions to model hardware components and their power characteristics. Software m odels are combined with hardware models to achieve a system-wide estimation, including peripheral devices, and to make the power-related impact in early design stages visible. By deriving energy profiles, we provide software developers with valuable feedback, which may be used to identify energy bugs and evaluate power consumption-related requirements. To demonstrate the potential of our approach, we use a sensor node example to evaluate our concept and to identify its energy bugs.
Optimised Nutrient Recovery from Biogas Digestate by Solid/Liquid Separation and Membrane Treatment
(2019)
Anaerobic digestion products of agricultural biogas plants are characterised by high nitrogen, phosphorus, and potassium content. In three scale-up steps, a membrane based digestate treatment process of solid-liquid-separation, ultrafiltration, and reverse osmosis for nutrient recovery was investigated. Lab-scale trials delivered a very good understanding of fluid properties and subsequent ultrafiltration performance, which is the limiting process step in terms of energy demand and operation costs. In semi-technical experiments, optimisation, and design parameters were developed, which were subsequently applied to pilot-scale tests at two full-scale biogas plants. The process optimisation resulted in 50 % energy reduction of the ultrafiltration step. About 36 % of the sludge volume was recovered as dischargeable water, 20 % as solid N/P-fertiliser, and 44 % as liquid N/K-fertiliser.
The simulation of the residual stress field achieved by shot peening cannot be carried out on component-large models. Hence, an efficient unit cell model for the simulation of the shot peening process is developed. The model allows both, the simple inclusion of a pre-stress and the evaluation of the up-arching of the Almen strip. For this purpose, generalized coupling constraints for the periodic boundaries of the unit cell are developed. These allow for displacement and rotation of the coupled boundaries relative to each other. In the coupling constraints, this is accomplished by respective variables, which can either be prescribed to the analysis or read out as a result from the analysis. Hence, the unit cell can expand, shear, bend and twist under driving forces like, e. g., residual stresses or thermal effects. At the same time, deformations of the cell’s periodic boundary pairs are kept congruent by the generalized coupling. The ability to cover expansion is novel regarding known periodic boundary conditions. Also, the application of a generalized unit cell to shot peening is new.
Results obtained with the generalized unit cell are displayed, demonstrating its capabilities: A fundamental analysis of the residual stress field from shot peening shows inhomogeneities at a fatigue relevant level to be inevitable. A validation of the model was done by comparison with experimental Almen strip shot peening tests reported in literature. Shot peening under pre-stress is demonstrated and its results in terms of residual stress are evaluated. The application of the generalized unit cell is not limited to shot peening.
This article proposes the concept of a simulation framework for environmental sensors with multilevel abstraction in agricultural scenarios. The implementation case study is a simulation of a grain-harvesting scenario enabled by LiDAR sensors. Environmental sensor models as well as kinematics and dynamic behavior of machines are based on the robotics simulator Gazebo. Models for powertrain, machine process aggregates and peripheral simulation components are implemented with the help of MATLAB/ Simulink and with the robotics middleware Robot Operating System (ROS). This article deals with the general concept of a multilevel simulation framework and in particular with sensor and environmental modeling.
Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Funktionen
(2018)
Es werden drei Modellierungsansätze zur Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Fahrzeugfunktionen beschrieben. Das Sensorsignal der Distanzmessung wird dabei anhand realer Messwerte oder phänomenologisch und auf der Basis empirisch ermittelter Kennwerte in Abhängigkeit von objekt- und sensorspezifischen Einflussfaktoren abgebildet. Basierend auf den Methoden zur Simulation von Distanzmesssystemen der Open Source Simulationsumgebung Gazebo wurden die Modellierungsansätze als spezifische Sensor- und Umfeldmodelle implementiert. Die Modelle wurden insbesondere für den Einsatz an mobilen landwirtschaftlichen Arbeitsmaschinen und für die Anwendung in der Getreideernte optimiert.
This paper describes the development and test of a novel LiDAR based combine harvester steering system using a harvest scenario and sensor point cloud simulation together with an established simulation toolchain for embedded software development. For a realistic sensor behavior simulation, considering the harvesting environment and the sensor mounting position, a phenomenological approach was chosen to build a multilayer LiDAR model at system level in Gazebo and ROS. A software-in-the-loop simulation of the mechatronic steering system was assembled by interfacing the commercial AppBase framework for point cloud processing and feature detection algorithms together with a machine model and control functions implemented in MATLAB/ Simulink. A test of ECUs in a hardware-in-the-loop simulation and as well as HMI elements in a driver-in-the-loop simulation was achieved by using CAN hardware interfaces and a CANoe based restbus simulation.
Our world and our lives are changing in many ways. Communication, networking, and computing technologies are among the most influential enablers that shape our lives today. Digital data and connected worlds of physical objects, people, and devices are rapidly changing the way we work, travel, socialize, and interact with our surroundings, and they have a profound impact on different domains,such as healthcare, environmental monitoring, urban systems, and control and management applications, among several other areas. Cities currently face an increasing demand for providing services that can have an impact on people’s everyday lives. The CityPulse framework supports smart city service creation by means of a distributed system for semantic discovery, data analytics, and interpretation of large-scale (near-)real-time Internet of Things data and social media data streams. To goal is to break away from silo
applications and enable cross-domain data integration. The CityPulse framework integrates multimodal, mixed quality, uncertain and incomplete data to create reliable, dependable information and continuously adapts data processing techniques to meet the quality of information requirements from end users. Different than existing solutions that mainly offer unified views of the data, the CityPulse framework is also equipped with powerful data analytics modules that perform intelligent data aggregation, event detection, quality
assessment, contextual filtering, and decision support. This paper presents the framework, describes ist components, and demonstrates how they interact to support easy development of custom-made applications for citizens. The benefits and the effectiveness of the framework are demonstrated in a use-case scenario
implementation presented in this paper.
Smart city applications in the Big Data era require not only techniques dedicated to dynamicity handling, but also the ability to take into account contextual information, user preferences and requirements, and real-time events to provide optimal solutions and automatic configuration for the end user. In this paper, we present a specific functionality in the design and implementation of a declarative decision support component that exploits contextual information, user preferences and requirements to automatically provide optimal configurations of smart city applications. The key property of user-centricity of our approach is achieved by enabling users to declaratively specify constraints and preferences on the solutions provided by the smart city application through the Decision Support component, and automatically map these constraints and preferences to provide optimal responses targeting user needs. We showcase the effectiveness and flexibility of our solution in two real usecase scenarios: a multimodal travel planner and a mobile parking application. All the components and algorithms described in this paper have been defined and implemented as part of the Smart City Framework CityPulse.
Process modeling languages help to define and execute processes and workflows. The Business Process Model and Notation (BPMN) 2.0 is used for business processes in commercial areas such as banks, shops, production and supply industry. Due to its flexible notation, BPMN is increasingly being used in non-traditional business process domains like Internet of Things (IoT) and agriculture. However, BPMN does not fit well to scenarios taking place in environments featuring limited, delayed, intermittent or broken connectivity. Communication just exists for BPMN - characteristics of message transfers, their priorities and connectivity parameters are not part of the model. No backup mechanism for communication issues exists, resulting in error-prone and failing processes. This paper introduces resilient BPMN (rBPMN), a valid BPMN extension for process modeling in unreliable communication environments. The meta model addition of opportunistic message flows with Quality of Service (QoS) parameters and connectivity characteristics allows to verify and enhance process robustness at design time. Modeling of explicit or implicit, decision-based alternatives ensures optimal process operation even when connectivity issues occur. In case of no connectivity, locally moved functionality guarantees stable process operation. Evaluation using an agricultural slurry application showed significant robustness enhancements and prevented process failures due to communication issues.
Management of agricultural processes is often troubled by disconnections and data transfer failures. Limited cellular network coverage may prevent information exchange between mobile process participants.
The research projects KOMOBAR and ISOCom designed, implemented und field-tested a delay tolerant platform for robust communication in rural areas and challenging environments. An adaptable combination of infrastructure-based cellular networks and infrastructure-free multihop ad hoc communication (WLAN) leads to a variety of new communication opportunities. Temporal storage and forwarding of data on mobile farm machinery as well as dynamic platform configurations during process runtime strongly enhance reliability and robustness of data transfers.
Ein modulares Framework zur Modellierung, Konfiguration und Regelung von kooperativen Agrarprozessen
(2016)
Die Komplexität vieler Agrarprozesse nimmt aufgrund von technischem Fortschritt, steigenden rechtlichen Anforderungen und Nachweispflichten beständig zu. Prozessketten werden in Kooperation verschiedener Akteure (Landwirt, Lohnunternehmer, Dienstleister, digitaler Vermittler, Behörde) gemeinsam bearbeitet, dokumentiert und geprüft. Ein ökonomisch und ökologisch ressourceneffizientes Management der Prozessausführung stellt eine Herausforderung für alle Akteure dar. Dynamische Prozessveränderungen führen vielfach zu manuellen Eingriffen in die Prozessregelung, die kostenintensive Verzögerungen verursachen. Das Forschungsvorhaben OPeRAte entwirft und evaluiert neu gestaltete Konzepte und Mechanismen zur durchgehenden Organisation und Regelung kooperativer Agrarprozesse. Es werden konfigurierbare und wiederverwendbare Module identifiziert, die sich an Prozessparameter anpassen und in artverwandten Prozessen erneut verwenden lassen. Das OPeRAte-Framework ermöglicht die Zusammenführung aller beteiligten Akteure und Ressourcen (Maschinen, Sensoren, Aktoren, Endgeräte, Server, Daten, etc.) über offene Schnittstellen. Prozessinhaber sollen durch autonome Prozesskonfigurationen und -adaptionen entlastet und durch Visualisierungen zu effizienten Entscheidungen befähigt werden. Die Konzepte dieses Beitrags dienen als Diskussionsgrundlage zur Formulierung von flexiblen und erweiterbaren Lösungsstrategien für die Landtechnik.
For Delay-Tolerant Networks (DTNs) many routing algorithms have been suggested. However, their performance depends heavily on the applied scenario. Especially heterogeneous scenarios featuring known and unknown node movements as well as different kinds of data lead to either poor delivery ratios or exhausted network resources.
To overcome these problems this paper introduces Data-Driven Routing for DTNs. Data is categorized according to its requirements into priority queues. Each queue applies an appropriate DTN routing algorithm that fits the data requirements best. Simulation results show that Data-Driven Routing allows high delivery ratios for time-critical data while saving network resources during the transfer of less time-critical data at the same time.