Analysis of Real-Time Capabilities of Dynamic Scheduled System

This PhD-thesis explores different real-time scheduling approaches to effectively utilize industrial real-time applications on multicore or manycore platforms. The proposed scheduling policy is named the Time-Triggered Constant Phase scheduler for handling periodic tasks, which determines time windows for each computation and communication in advance by using the dependent task model

Decision Support Systems in the Context of Cyber-Physical Systems: Influencing Factors and Challenges for the Adoption in Production Scheduling

Cyber-physical systems promise a complete networking of all actors and resources involved in production and thus an improved availability of information. In this context decision support systems enable appropriate processing and presentation of the captured data. In particular, production scheduling could benefit from this, since it is responsible for the short-term planning and control of released orders. Since decision support systems and cyber-physical systems together are not yet widely used in production scheduling, the aim of this research study is to analyze the adoption of these technologies. In order to do so, we conducted a qualitative interview study with experts on production scheduling. Thereby, we identified eleven influencing factors and 22 related challenges, which affect the adoption of decision support systems in production scheduling in the context of cyber-physical systems. The results help to explain the adoption and can serve as a starting point for the development of those systems

Time Triggered Scheduling Analysis for Real-Time Applications on Multicore Platforms

REACTION 2014. 3rd International Workshop on Real-time and Distributed Computing in Emerging Applications. Rome, Italy. December 2nd, 2014.Scheduling of real-time applications for multicore platforms has become an important research topic. For analyzing the timing satisfactions of real-time tasks, most researches in the literature assume independent tasks. However, industrial applications are usually with fully tangled dependencies among the tasks. Independence of the tasks provides a very nice abstraction, whereas dependent structures due to the tangled executions of the tasks are closer to the real systems. This paper studies the scheduling policies and the schedulabil-ity analysis based on independent tasks by hiding the execution dependencies with additional timing parameters. Our scheduling policy relates to the well-known periodic task model, but in contrast, tasks are able to communicate with each other. A feasible task set requires an analysis for each core and the communication infrastructure, which can be performed indi-vidually by decoupling computation from communication in a distributed system. By using a Time-Triggered Constant Phase (TTCP) scheduler, each task receives certain time-slots in the hyper-period of the task set, which ensures a time-predictable communication impact. In this paper, we provide several algorithms to derive the time-slot for each task. Further, we found a fast heuristic algorithm to calculate the time-slot for each task, which is capable to reach a core utilization of 90% by considering typical industrial applications. Finally, experiments show the effectiveness of our heuristic and the performance in different settings.Publicad

The effect of wavefront aberrations in atom interferometry

Wavefront aberrations are one of the largest uncertainty factors in present atom interferometers. We present a detailed numerical and experimental analysis of this effect based on measured aberrations from optical windows. By placing windows into the Raman beam path of our atomic gravimeter, we verify for the first time the induced bias in very good agreement with theory. Our method can be used to reduce the uncertainty in atomic gravimeters by one order of magnitude resulting in an error of less than $3\times 10^{-10}\,g$ and it is suitable in a wide variety of atom interferometers with thermal or ultra cold atoms. We discuss the limitations of our method, potential improvements and its role in future generation experiments.Comment: Applied Physics B, 201

Using Distributed Ledger Technologies to Support Complex Supply Chains

The concept of blockchain, as part of distributed ledger technologies, has gained a lot of interest recently, especially in cryptocurrencies. With the addition of other technical capabilities, e.g., smart contracts and oracles, this interest has spread to other areas as well and affects a wide variety of business processes such as supply chain processes. However, in research, the wide variety of processes finds inadequate consideration to date. In this research paper, we provide an overview of the state of the art of distributed ledger technologies in supply chains and point out future research topics. Therefore, we conducted a structured literature review, systematized potential application areas in supply chain processes, and showed that research gaps exist. To address the research gaps, we derived open research questions, whereby conducting design studies to deal with the practical problems in the application areas plays a central role

Mobile quantum gravity sensor with unprecedented stability

Changes of surface gravity on Earth are of great interest in geodesy, earth sciences and natural resource exploration. They are indicative of Earth system's mass redistributions and vertical surface motion, and are usually measured with falling corner-cube- and superconducting gravimeters (FCCG and SCG). Here we report on absolute gravity measurements with a mobile quantum gravimeter based on atom interferometry. The measurements were conducted in Germany and Sweden over periods of several days with simultaneous SCG and FCCG comparisons. They show the best-reported performance of mobile atomic gravimeters to date with an accuracy of 39 nm/s^2, long-term stability of 0,5 nm/s^2 and short-term noise of 96 nm/s^2/(Hz)^1/2. These measurements highlight the unique properties of atomic sensors. The achieved level of performance in a transportable instrument enables new applications in geodesy and related Fields, such as continuous absolute gravity monitoring with a single instrument under rough environmental conditions

Decision Support Systems in the Context of Cyber-Physical Systems: Influencing Factors and Challenges for the Adoption in Production Scheduling

Cyber-physical systems promise a complete networking of all actors and resources involved in production and thus an improved availability of information. In this context decision support systems enable appropriate processing and presentation of the captured data. In particular, production scheduling could benefit from this, since it is responsible for the short-term planning and control of released orders. Since decision support systems and cyber-physical systems together are not yet widely used in production scheduling, the aim of this research study is to analyse the adoption of these technologies. In order to do so, we conducted a qualitative interview study with experts on production scheduling. Thereby, we identified eleven influencing factors and 22 related challenges, which affect the adoption of decision support systems in production scheduling in the context of cyber-physical systems. We further discuss and assess the identified influencing factors based on the interview study. The results help to explain and improve the adoption of those systems and can serve as a starting point for their development