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Collaborative Research Center SFB 876 - Providing Information by Resource-Constrained Data Analysis

The collaborative research center SFB876 brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.

RTCSA Best Student Paper Award in Hakodate


The joint work on "Analysis of Deadline Miss Rates for Uniprocessor Fixed-Priority Scheduling" by Kuan-Hsun Chen, Georg von der Brüggen and Jian-Jia Chen was awarded the RTCSA Best Student Paper Award. The conference, which took place this August in Hakodate, Japan, focuses on the technology of embedded and real-time systems as well as their emerging applications. The paper is a direct result of the research done in the CRC project B2.


Timeliness is an important feature for many embedded systems. Although soft real-time embedded systems can tolerate and allow certain deadline misses, it is still important to quantify them to justify whether the considered systems are acceptable. In this paper, we provide a way to safely over-approximate the expected deadline miss rate for a specific sporadic real-time task under fixed-priority preemptive scheduling in uniprocessor systems. Our approach is compatible with the existing results in the literature that calculate the probability of deadline misses either based on the convolution-based approaches or analytically. We demonstrate our approach by considering randomly generated task sets with an execution behavior that simulates jobs that are subjected to soft errors incurred by hardware transient faults under a given fault rate. To empirically gather the deadline miss rates, we implemented an event-based simulator with a fault-injection module and release the scripts. With extensive simulations under different fault rates, we evaluate the efficiency and the pessimism of our approach. The evaluation results show that our approach is effective to derive an upper bound of the expected deadline miss rate and efficient with respect to the required computation time.

Christoph Borchert receives the "2018 Carter PhD Dissertation Award" during the Conference "Dependable Systems and Networks" (DSN 2018)


The 2018 William C. Carter PhD Dissertation Award in Dependability has been awarded to Christoph Borchert for his disseration "Aspect-Oriented Technology for Dependable Operating Systems" done at the Technische Universität Dortmund, Germany. Christoph will be presenting his dissertation at the 2018 International Conference on Dependable Systems and Networks (DSN) in Luxembourg in late June.


Modern computer devices exhibit transient hardware faults that disturb the electrical behavior but do not cause permanent physical damage to the devices. Transient faults are caused by a multitude of sources, such as fluctuation of the supply voltage, electromagnetic interference, and radiation from the natural environment. Therefore, dependable computer systems must incorporate methods of fault tolerance to cope with transient faults. Software-implemented fault tolerance represents a promising approach that does not need expensive hardware redundancy for reducing the probability of failure to an acceptable level.

This thesis focuses on software-implemented fault tolerance for operating systems because they are the most critical pieces of software in a computer system: All computer programs depend on the integrity of the operating system. However, the C/C++ source code of common operating systems tends to be already exceedingly complex, so that a manual extension by fault tolerance is no viable solution. Thus, this thesis proposes a generic solution based on Aspect-Oriented Programming (AOP).

To evaluate AOP as a means to improve the dependability of operating systems, this thesis presents the design and implementation of a library of aspect-oriented fault-tolerance mechanisms. These mechanisms constitute separate program modules that can be integrated automatically into common off-the-shelf operating systems using a compiler for the AOP language. Thus, the aspect-oriented approach facilitates improving the dependability of large-scale software systems without affecting the maintainability of the source code. The library allows choosing between several error-detection and error-correction schemes, and provides wait-free synchronization for handling asynchronous and multi-threaded operating-system code.

This thesis evaluates the aspect-oriented approach to fault tolerance on the basis of two off-the-shelf operating systems. Furthermore, the evaluation also considers one user-level program for protection, as the library of fault-tolerance mechanisms is highly generic and transparent and, thus, not limited to operating systems. Exhaustive fault-injection experiments show an excellent trade-off between runtime overhead and fault tolerance, which can be adjusted and optimized by fine-grained selective placement of the fault-tolerance mechanisms. Finally, this thesis provides evidence for the effectiveness of the approach in detecting and correcting radiation-induced hardware faults: High-energy particle radiation experiments confirm improvements in fault tolerance by almost 80 percent.

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