Integrated analysis of error detection and recovery

An integrated modeling and analysis of error detection and recovery is presented. When fault latency and/or error latency exist, the system may suffer from multiple faults or error propagations which seriously deteriorate the fault-tolerant capability. Several detection models that enable analysis of the effect of detection mechanisms on the subsequent error handling operations and the overall system reliability were developed. Following detection of the faulty unit and reconfiguration of the system, the contaminated processes or tasks have to be recovered. The strategies of error recovery employed depend on the detection mechanisms and the available redundancy. Several recovery methods including the rollback recovery are considered. The recovery overhead is evaluated as an index of the capabilities of the detection and reconfiguration mechanisms

Measurements, Models, Systems and Design

531 s.

Autonomous Recovery Of Reconfigurable Logic Devices Using Priority Escalation Of Slack

Field Programmable Gate Array (FPGA) devices offer a suitable platform for survivable hardware architectures in mission-critical systems. In this dissertation, active dynamic redundancy-based fault-handling techniques are proposed which exploit the dynamic partial reconfiguration capability of SRAM-based FPGAs. Self-adaptation is realized by employing reconfiguration in detection, diagnosis, and recovery phases. To extend these concepts to semiconductor aging and process variation in the deep submicron era, resilient adaptable processing systems are sought to maintain quality and throughput requirements despite the vulnerabilities of the underlying computational devices. A new approach to autonomous fault-handling which addresses these goals is developed using only a uniplex hardware arrangement. It operates by observing a health metric to achieve Fault Demotion using Recon- figurable Slack (FaDReS). Here an autonomous fault isolation scheme is employed which neither requires test vectors nor suspends the computational throughput, but instead observes the value of a health metric based on runtime input. The deterministic flow of the fault isolation scheme guarantees success in a bounded number of reconfigurations of the FPGA fabric. FaDReS is then extended to the Priority Using Resource Escalation (PURE) online redundancy scheme which considers fault-isolation latency and throughput trade-offs under a dynamic spare arrangement. While deep-submicron designs introduce new challenges, use of adaptive techniques are seen to provide several promising avenues for improving resilience. The scheme developed is demonstrated by hardware design of various signal processing circuits and their implementation on a Xilinx Virtex-4 FPGA device. These include a Discrete Cosine Transform (DCT) core, Motion Estimation (ME) engine, Finite Impulse Response (FIR) Filter, Support Vector Machine (SVM), and Advanced Encryption Standard (AES) blocks in addition to MCNC benchmark circuits. A iii significant reduction in power consumption is achieved ranging from 83% for low motion-activity scenes to 12.5% for high motion activity video scenes in a novel ME engine configuration. For a typical benchmark video sequence, PURE is shown to maintain a PSNR baseline near 32dB. The diagnosability, reconfiguration latency, and resource overhead of each approach is analyzed. Compared to previous alternatives, PURE maintains a PSNR within a difference of 4.02dB to 6.67dB from the fault-free baseline by escalating healthy resources to higher-priority signal processing functions. The results indicate the benefits of priority-aware resiliency over conventional redundancy approaches in terms of fault-recovery, power consumption, and resource-area requirements. Together, these provide a broad range of strategies to achieve autonomous recovery of reconfigurable logic devices under a variety of constraints, operating conditions, and optimization criteria

Wavelet Theory

The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editor’s personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior

Seismic Assessment of Geothermal Potential - Concept and ApplicationCase Study of the German Continental Deep Drilling Site (KTB)

Geothermal reservoirs can embody safe, accessible and stable sources of renewable and environmentally friendly energy. In order to access and extract this energy, drilling of deep wells connected with vast financial investments is unavoidable. Thorough predrilling exploration followed by simulations of heat extraction can help to assess the site’s geothermal energy potential and thus lower the risk of possible financial losses. Extraction of heat enclosed in the deep rock can be simulated with a two-well geothermal system. Through one of the wells cool water is being injected into the reservoir, where it is heating up while travelling towards the production well. If certain conditions are fulfilled, water pumped to the surface carries the amount of energy sufficient for geothermal power production. With simulations of such geothermal systems it is possible to predict their profitability and sustainability. The extensive amount of scientific experiments performed during the Continental Deep Drilling Program (KTB) within the years 1985-1996 yielded a wide database of miscellaneous information concerning the continental crystalline crust. This and the fact that temperatures up to 265°C were measured in the KTB drill hole were the motives to choose the KTB site as case study representative for geothermal reservoirs located in crystalline environments.Geothermische Reservoire verkörpern Quellen erneuerbarer, sicherer und jahreszeitenunabhängiger Energie. Um diese Energie zu erreichen ist das Abteufen von tiefen Bohrlöchern unvermeidlich, was jedoch mit erheblichen finanziellen Kosten verbunden ist. Sorgfältige geophysikalische Untersuchungen und anschließende Simulationen der Wärmegewinnung können bei der Beurteilung des geothermischen Potentials der Lokation behilflich sein und somit das Risiko finanzieller Verluste senken. Extraktion von Wärme aus dem tiefen Gestein kann mit Hilfe geohydrothermaler Dubletten simuliert werden. Durch eine der Bohrungen wird das kühle Wasser in das Reservoir eingeführt, wo es sich auf dem Weg zum dem Produktions-Bohrloch erhitzt. Sind bestimmte Vorausetzungen erfüllt, kann das zur Oberfläche gepumpte Wasser eine ausreichende Menge an Energie zur geothermischen Stromerzeugung mit sich führen. Mit Simulationen solcher Geothermieanlagen ist es möglich ihre Rentabilität und Nachhaltigkeit vorherzusagen. Die zahlreichen wissenschaftlichen Experimente, die innerhalb des Projektes der Kontinentalen Tiefbohrung (KTB) in den Jahren 1985-1996 durchgeführt wurden, ergaben eine umfangreiche Datenbank. Dies und die Tatsache, dass Temperaturen bis zu 265°C in dem KTB Bohrloch gemessen wurden, waren die Beweggründe die KTB Lokation repräsentativ für geothermische Reservoire in kristallinem Gestein zu wählen