Due to the steadily increasing number of decentralized generation units, the upcoming smart meter rollout and the expected electrification of the transport sector (e-mobility), grid planning and grid operation at low-voltage (LV) level are facing major challenges. Therefore, many studies, research and demonstration projects on the above topics have been carried out in recent years, and the results and the methods developed have been published. However, the published methods usually cannot be replicated or validated, since the majority of the examination models or the scenarios used are incomprehensible to third parties. There is a lack of uniform grid models that map the German LV grids and can be used for comparative investigations, which are similar to the example of the North American distribution grid models of the IEEE. In contrast to the transmission grid, whose structure is known with high accuracy, suitable grid models for LV grids are difficult to map because of the high number of LV grids and distribution system operators. Furthermore, a detailed description of real LV grids is usually not available in scientific publications for data privacy reasons. For investigations within a research project, the most characteristic synthetic LV grid models have been created, which are based on common settlement structures and usual grid planning principles in Germany. In this work, these LV grid models, and their development are explained in detail. For the first time, comprehensible LV grid models for the middle European area are available to the public, which can be used as a benchmark for further scientific research and method developments. This document is an English version of the paper which was originally written in German1. In addition, this paper discusses a few more aspects especially on the planning process of distribution grids in Germany.

Beamforming performs spatial filtering to preserve the signal from given directions of interest while suppressing interfering signals and noise arriving from other directions. For example, a microphone array equipped with beamforming algorithm could preserve the sound coming from a target speaker and suppress sounds coming from other speakers. Beamformer has been widely used in many applications such as radar, sonar, communication, and acoustic systems. A data-independent beamformer is the beamformer whose coefficients are independent on sensor signals, it normally uses less computation since the coefficients are computed once. Moreover, its coefficients are derived from the well-defined statistical models, then it produces less artifacts. The major drawback of this beamforming class is its limitation to the interference suppression. On the other hand, an adaptive beamformer is a beamformer whose coefficients depend on or adapt to sensor signals. It is capable of suppressing the interference better than a data-independent beamforming but it suffers from either too much distortion of the signal of interest or less noise reduction when the updating rate of coefficients does not synchronize with the changing rate of the noise model. Besides, it is computationally intensive since the coefficients need to be updated frequently. In acoustic applications, the bandwidth of signals of interest extends over several octaves, but we always expect that the characteristic of the beamformer is invariant with regard to the bandwidth of interest. This can be achieved by the so-called broadband beamforming. Since the beam pattern of conventional beamformers depends on the frequency of the signal, it is common to use a dense and uniform array for the broadband beamforming to guarantee some essential performances together, such as frequency-independence, less sensitive to white noise, high directivity factor or high front-to-back ratio. In this dissertation, we mainly focus on the sparse array of which the aim is to use fewer sensors in the array, while simultaneously assuring several important performances of the beamformer. In the past few decades, many design methodologies for sparse arrays have been proposed and were applied in a variety of practical applications. Although good results were presented, there are still some restrictions, such as the number of sensors is large, the designed beam pattern must be fixed, the steering ability is limited and the computational complexity is high. In this work, two novel approaches for the sparse array design taking a hypothesized uniform array as a basis are proposed, that is, one for data-independent beamformers and the another for adaptive beamformers. As an underlying component of the proposed methods, the dissertation introduces some new insights into the uniform array with broadband beamforming. In this context, a function formulating the relations between the sensor coefficients and its beam pattern over frequency is proposed. The function mainly contains the coordinate transform and inverse Fourier transform. Furthermore, from the bijection of the function and broadband beamforming perspective, we propose the lower and upper bounds for the inter-distance of sensors. Within these bounds, the function is a bijective function that can be utilized to design the uniform array with broadband beamforming. For data-independent beamforming, many studies have focused on optimization procedures to seek the sparse array deployment. This dissertation presents an alternative approach to determine the location of sensors. Starting with a weight spectrum of a virtual dense and uniform array, some techniques are used, such as analyzing a weight spectrum to determine the critical sensors, applying the clustering technique to group the sensors into different groups and selecting representative sensors for each group. After the sparse array deployment is specified, the optimization technique is applied to find the beamformer coefficients. The proposed method helps to save the computation time in the design phase and its beamformer performance outperforms other state-of-the-art methods in several aspects such as the higher white noise gain, higher directivity factor or more frequency-independence. For adaptive beamforming, the dissertation attempts to design a versatile sparse microphone array that can be used for different beam patterns. Furthermore, we aim to reduce the number of microphones in the sparse array while ensuring that its performance can continue to compete with a highly dense and uniform array in terms of broadband beamforming. An irregular microphone array in a planar surface with the maximum number of distinct distances between the microphones is proposed. It is demonstrated that the irregular microphone array is well-suited to sparse recovery algorithms that are used to solve underdetermined systems with subject to sparse solutions. Here, a sparse solution is the sound source's spatial spectrum that need to be reconstructed from microphone signals. From the reconstructed sound sources, a method for array interpolation is presented to obtain an interpolated dense and uniform microphone array that performs well with broadband beamforming. In addition, two alternative approaches for generalized sidelobe canceler (GSC) beamformer are proposed. One is the data-independent beamforming variant, the other is the adaptive beamforming variant. The GSC decomposes beamforming into two paths: The upper path is to preserve the desired signal, the lower path is to suppress the desired signal. From a beam pattern viewpoint, we propose an improvement for GSC, that is, instead of using the blocking matrix in the lower path to suppress the desired signal, we design a beamformer that contains the nulls at the look direction and at some other directions. Both approaches are simple beamforming design methods and they can be applied to either sparse array or uniform array. Lastly, a new technique for direction-of-arrival (DOA) estimation based on the annihilating filter is also presented in this dissertation. It is based on the idea of finite rate of innovation to reconstruct the stream of Diracs, that is, identifying an annihilating filter/locator filter for a few uniform samples and the position of the Diracs are then related to the roots of the filter. Here, an annihilating filter is the filter that suppresses the signal, since its coefficient vector is always orthogonal to every frame of signal. In the DOA context, we regard an active source as a Dirac associated with the arrival direction, then the directions of active sources can be derived from the roots of the annihilating filter. However, the DOA obtained by this method is sensitive to noise and the number of DOAs is limited. To address these issues, the dissertation proposes a robust method to design the annihilating filter and to increase the degree-of-freedom of the measurement system (more active sources can be detected) via observing multiple data frames. Furthermore, we also analyze the performance of DOA with diffuse noise and propose an extended multiple signal classification algorithm that takes diffuse noise into account. In the simulation, it shows, that in the case of diffuse noise, only the extended multiple signal classification algorithm can estimate the DOAs properly.

We introduce Property-Driven Design, a tool-flow that guarantees formal soundness be- tween ESL and RTL and thus enables a shift-left of general functional verification by moving HW verification to higher abstraction layers. In addition, by generating a formal Verification IP (VIP) automatically from ESL descriptions, the entry hurdle to formal methods is reduced considerably, opening them to a wider audience, which effectively ‘democratizes’ them. Short feedback cycles reduce time spent on RTL verification and lead to higher-quality designs.

Bees are recognized as an indispensable link in the human food chain and general ecological system. Numerous threats, from pesticides to parasites, endanger bees and frequently lead to hive collapse. The varroa destructor mite is a key threat to bee keeping and the monitoring of hive infestation level is of major concern for effective treatment. Sensors and automation, e.g., as in condition-monitoring and Industry 4.0, with machine learning offer help. In numerous activities a rich variety of sensors have been applied to apiary/hive instrumentation and bee monitoring. Quite recent activities try to extract estimates of varroa infestation level by hive air analysis based on gas sensing and gas sensor systems. In our work in the IndusBee4.0 project [8, 11], an hive-integrated, compact autonomous gas sensing system for varroa infestation level estimation based on low- cost highly integrated gas sensors was conceived and applied. This paper adds to [11] with the first results of a mid-term duration investigation from July to September 2020 until formic acid treatment. For the regarded hive more than 79 % of detection probability based on the SGP30 gas sensor readings have been achieved.

Code coverage analysis plays an important role in the software testing process. More recently, the remarkable effectiveness of coverage feedback has triggered a broad interest in feedback-guided fuzzing. In this work, we discuss static instrumentation techniques for binary-level coverage analysis without compiler support. We show that the proposed techniques are precise, efficient, and transparent significantly beyond the state of the art. We implement these techniques into two tools, namely, Spedi and bcov. Both tools are open source and publicly available. Spedi shows that the disassembly and function identification of stripped binaries can be highly accurate without resort to any external information. We build on these important results in bcov where we statically instrument x86-64 ELF binaries to track code coverage. However, improving efficiency and scaling to large real-world software required an orchestrated effort combining several techniques. First, we bring a well-known probe pruning technique, for the first time, to binary-level instrumentation and effectively leverage its notion of superblocks to reduce overhead. Second, we introduce sliced microexecution, a robust technique for jump table analysis which improves CFG precision and enables us to instrument jump table entries. Additionally, smaller instructions in x86-64 pose a challenge for inserting detours. To address this challenge, we aggressively exploit padding bytes. Also, we introduce a greedy scheme to systematically host detours in neighboring basic blocks. We evaluate bcov on a corpus of 95 binaries compiled from eight popular and well-tested packages like FFmpeg and LLVM. Two instrumentation policies, with different edge-level precision, are used to patch all functions in this corpus - over 1.6 million functions. Our precise policy has average performance and memory overheads of 14% and 22%, respectively. Instrumented binaries do not introduce any test regressions. The reported coverage is highly accurate with an average F-score of 99.86%. Finally, our jump table analysis is comparable to that of IDA Pro on gcc binaries and outperforms it on clang binaries. Our work demonstrates that static instrumentation can offer unique advantages in comparison to established methods like compiler instrumentation and dynamic binary instrumentation. It also opens the door for many interesting applications of static instrumentation, which can go well beyond coverage analysis.

Mit dem Vorhandensein elektrischer Energie und moderner Sensorik an elektrisch unterstützten Fahrrädern eröffnen sich neue Möglichkeiten der Entwicklung von Fahrerassistenzsystemen am Pedelec zur Erhöhung der Sicherheit und des Fahrkomforts. Die Leistungsfähigkeit solcher Systeme kann durch die Nutzung von Inertialsensorik weiter gesteigert werden. Jedoch müssen solche Sensoren, vor allem bei sicherheitsrelevanten Assistenzsystemen, zuverlässige, robuste und plausible Sensordaten liefern. Hieraus ergibt sich das Thema dieser Arbeit: die Evaluation von Inertialsensorik für Fahrerassistenzsysteme am Pedelec anhand systematischer Untersuchung der Fahrdynamik. Durch simulative und experimentelle Untersuchungen der MEMS-Sensorik und der Fahrdynamik, basierend auf Testkatalogen, werden die Anforderungen an Inertialsensorik abgeleitet und die Störbarkeit der Drehrate analysiert. Dabei führt die Betrachtung verschiedener Sensortypen, Fahrszenarien und Anbaupositionen zu der Erkenntnis, dass bspw. die Anbauposition am Sattelrohr und in der Antriebseinheit besonders geeignet sind. Vor allem der betrachtete Automotive-MEMS-Sensor liefert auch bei potentiell kritischen Vibrationen bei einer Fahrt über Kopfsteinpflaster oder über Treppenstufen sowie bei Bremsenquietschen zuverlässig plausible Sensordaten. Zusätzlich zeigt eine Betrachtung der Auswirkungen von Sensorfehlern auf eine Datenfusion, d.h. der Berechnung der Raumwinkel, dass vor allem die Minimierung des Offset-Fehlers, bspw. durch eine Langzeitkorrektur, sinnvoll erscheint und resultierende Winkelfehler minimieren kann. Die Untersuchung der Fahrdynamik betrachtet insbesondere das Fahrszenario (kritische) Kurvenfahrt. Anhand der Fahrdaten zahlreicher Pedelec-Nutzer werden eine Methode zur Erkennung von Kurvenfahrten sowie theoretische Ansätze zur Vermeidung einer kritischen Kurvenfahrt durch einen aktiven Lenkeingriff realisiert.

Multicore processors and Multiprocessor System-on-Chip (MPSoC) have become essential in Real-Time Systems (RTS) and Mixed-Criticality Systems (MCS) because of their additional computing capabilities that help reduce Size, Weight, and Power (SWaP), required wiring, and associated costs. In distributed systems, a single shared multicore or MPSoC node executes several applications, possibly of different criticality levels. However, there is interference between applications due to contention in shared resources such as CPU core, cache, memory, and network. Existing allocation and scheduling methods for RTS and MCS often rely on implicit assumptions of the constant availability of individual resources, especially the CPU, to provide guaranteed progress of tasks. Most existing approaches aim to resolve contention in only a specific shared resource or a set of specific shared resources. Moreover, they handle a limited number of events such as task arrivals and task completions. In distributed RTS and MCS with several nodes, each having multiple resources, if the applications, resource availability, or system configurations change, obtaining assumptions about resources becomes complicated. Thus, it is challenging to meet end-to-end constraints by considering each node, resource, or application individually. Such RTS and MCS need global resource management to coordinate and dynamically adapt system-wide allocation of resources. In addition, the resource management can dynamically adapt applications to changing availability of resources and maintains a system-wide (global) view of resources and applications. The overall aim of global resource management is twofold. Firstly, it must ensure real-time applications meet their end-to-end deadlines even in the presence of faults and changing environmental conditions. Secondly, it must provide efficient resource utilization to improve the Quality of Service (QoS) of co-executing Best-Effort (BE) (or non-critical) applications. A single fault in global resource management can render it useless. In the worst case, the resource management can make faulty decisions leading to a deadline miss in real-time applications. With the advent of Industry 4.0, cloud computing, and Internet-of-Things (IoT), it has become essential to combine stringent real-time constraints and reliability requirements with the need for an open-world assumption and ensure that the global resource management does not become an inviting target for attackers. In this dissertation, we propose a domain-independent global resource management framework for distributed RTS and MCS consisting of heterogeneous nodes based on multicore processors or MPSoC. We initially developed the framework with the French Aerospace Lab -- ONERA and Thales Research & Technology during the DREAMS project and later extended it during SECREDAS and other internal projects. Unlike previous resource management frameworks RTS and MCS, we consider both safety and security for the framework itself. To enable real-time industries to use cloud computing and enter a new market segment -- real-time operation as a cloud-based service, we propose a Real-Time-Cloud (RT-Cloud) based on global resource management for hosting RTS and MCS. Finally, we present a mixed-criticality avionics use case for evaluating the capabilities of the global resource management framework in handling permanent core failures and temporal overload condition, and a railway use case to motivate the use of RT-Cloud with global resource management.

Ethernet has become an established communication technology in industrial automation. This was possible thanks to the tremendous technological advances and enhancements of Ethernet such as increasing the link-speed, integrating the full-duplex transmission and the use of switches. However these enhancements were still not enough for certain high deterministic industrial applications such as motion control, which requires cycle time below one millisecond and jitter or delay deviation below one microsecond. To meet these high timing requirements, machine and plant manufacturers had to extend the standard Ethernet with real-time capability. As a result, vendor-specific and non-IEEE standard-compliant "Industrial Ethernet" (IE) solutions have emerged. The IEEE Time-Sensitive Networking (TSN) Task Group specifies new IEEE-conformant functionalities and mechanisms to enable the determinism missing from Ethernet. Standard-compliant systems are very attractive to the industry because they guarantee investment security and sustainable solutions. TSN is considered therefore to be an opportunity to increase the performance of established Industrial-Ethernet systems and to move forward to Industry 4.0, which require standard mechanisms. The challenge remains, however, for the Industrial Ethernet organizations to combine their protocols with the TSN standards without running the risk of creating incompatible technologies. TSN specifies 9 standards and enhancements that handle multiple communication aspects. In this thesis, the evaluation of the use of TSN in industrial real-time communication is restricted to four deterministic standards: IEEE802.1AS-Rev, IEEE802.1Qbu IEEE802.3br and IEEE802.1Qbv. The specification of these TSN sub-standards was finished at an early research stage of the thesis and hardware prototypes were available. Integrating TSN into the Industrial-Ethernet protocols is considered a substantial strategical challenge for the industry. The benefits, limits and risks are too complex to estimate without a thorough investigation. The large number of Standard enhancements makes it hard to select the required/appropriate functionalities. In order to cover all real-time classes in the automation [9], four established Industrial-Ethernet protocols have been selected for evaluation and combination with TSN as well as other performance relevant communication features. The objectives of this thesis are to (1) Provide theoretical, simulation and experimental evaluation-methodologies for the timing performance analysis of the deterministic TSN-standards mentioned above. Multiple test-plans are specified to evaluate the performance and compatibility of early version TSN-prototypes from different providers. (2) Investigate multiple approaches and deduce migration strategies to integrate these features into the established Industrial-Ethernet protocols: Sercos III, Profinet IRT, Profinet RT and Ethernet/IP. A scenario of coexistence of time-critical traffic with other traffic in a TSN-network proves that the timing performance for highly deterministic applications, e.g. motion-control, can only be guaranteed by the TSN scheduling algorithm IEEE802.1Qbv. Based on a requirements survey of highly deterministic industrial applications, multiple network scenarios and experiments are presented. The results are summarized into two case studies. The first case study shows that TSN alone is not enough to meet these requirements. The second case study investigates the benefits of additional mechanisms (Gigabit link-speed, minimum cycle time modeling, frame forwarding mechanisms, frame structure, topology migration, etc.) in combination with the TSN features. An implementation prototype of the proposed system and a simulation case study are used for the evaluation of the approach. The prototype is used for the evaluation and validation of the simulation model. Due to given scalability constraints of the prototype (no cut-through functionalities, limited number of TSN-prototypes, etc…), a realistic simulation model, using the network simulation tool OMNEST / OMNeT++, is conducted. The obtained evaluation results show that a minimum cycle time ≤1 ms and a maximum jitter ≤1 μs can be achieved with the presented approaches.

Durch den wachsenden Anteil an Erzeugungsanlagen und leistungsstarken Verbrauchern aus dem Verkehr- und Wärmesektor kommen Niederspannungsnetze immer näher an ihre Betriebsgrenzen. Da für die Niederspannungsnetze bisher keine Messwerterfassung vorgesehen war, können Netzbetreiber Grenzverletzungen nicht erkennen. Um dieses zu ändern, werden deutsche Anschlussnutzer in Zukunft flächendeckend mit modernen Messeinrichtungen oder intelligenten Messsystemen (auch als Smart Meter bezeichnet) ausgestattet sein. Diese sind in der Lage über eine Kommunikationseinheit, das Smart-Meter-Gateway, Messdaten an die Netzbetreiber zu senden. Werden Messdaten aber als personenbezogene Netzzustandsdaten deklariert, so ist aus Datenschutzgründen eine Erhebung dieser Daten weitgehend untersagt. Ziel dieser Arbeit ist es eine Zustandsschätzung zu entwickeln, die auch bei niedrigredundanter Messwertaufnahme für den Netzbetrieb von Niederspannungsnetzen anwendbare Ergebnisse liefert. Neben geeigneten Algorithmen zur Zustandsschätzung ist dazu die Generierung von Ersatzwerten im Fokus. Die Untersuchungen und Erkenntnisse dieser Arbeit tragen dazu bei, den Verteilnetzbetreibern bei den maßgeblichen Entscheidungen in Bezug auf die Zustandsschätzung in Niederspannungsnetzen zu unterstützen. Erst wenn Niederspannungsnetze mit Hilfe der Zustandsschätzung beobachtbar sind, können darauf aufbauende Konzepte zur Regelung entwickelt werden, um die Energiewende zu unterstützen.

In dieser Arbeit wird ein formales Modell zur Beschreibung von hardwarenaher Software vorgestellt: Die Programmnetzliste. Die Programmnetzliste (PN) besteht aus Instruktionszellen die in einem gerichteten azyklischen Graph verbunden sind und dabei alle Ausführungspfade des betrachteten Programms beinhaltet. Die einzelnen Instruktionszellen repräsentieren eine Instruktion oder eine Instruktionssequenz. Die PN verfügt über eine explizite Darstellung des Programmablaufs und eine implizite Modellierung des Datenpfads und ist als Modell für die Verifikation von Software nutzbar. Die Software wird dabei auf Maschinencode-Level betrachtet. Die Modellgenerierung besteht aus wenigen und gut automatisierbaren Schritten. Als Grundlage dient ein – ggf. unvollständiger – Kontrollfluss Graph (CFG), der aus der Software generiert werden kann. Die Modellgenerierung besteht aus zwei Schritten. Der erste Schritt ist die Erzeugung des expliziten Programmablaufs, indem der CFG abgerollt wird. Dabei wird ein sogenannter Execution-Graph (EXG) erzeugt, der alle möglichen Ausführungspfade des betrachteten Programms beinhaltet. Um dieses Modell so kompakt wie möglich zu halten, werden unterschiedliche Techniken verwendet – wie das Zusammenführen gemeinsamer Pfade und das Erkennen von “toten” Verzweigungen im Programm, die an der entsprechenden Stelle niemals ausgeführt werden. Im Anschluss wird im zweiten Schritt der Execution-Graph in die Programmnetzliste (PN) übersetzt. Dabei werden alle Knoten im EXG durch eine entsprechende Instruktionszelle ersetzt. Die Kanten des Graphen entsprechen dabei dem Programmzustand. Der Programmzustand setzt sich aus den Variablen im Speicher wie auch dem Architekturzustand des unterliegenden Prozessors zusammen. Ergänzt wird der Programmzustand in der Programmnetzliste um ein sogenanntes Active-Bit, welches es ermöglicht den aktiven Pfad in der Netzliste zu markieren. Das ist notwendig, da die Software immer nur einen Pfad gleichzeitig ausführen kann, aber die PN alle möglichen Pfade beinhaltet. Auf der Programmnetzliste können dann mit Hilfe von Hardware Property Checkern basierend auf BMC oder IPC diverse Eigenschaften bewiesen werden. Zusätzlich wird die Programmnetzliste um die Fähigkeit zur Interruptmodellierung erweitert.