Availability Analysis of Redundant and Replicated Cloud Services with Bayesian Networks

Due to the growing complexity of modern data centers, failures are not uncommon any more. Therefore, fault tolerance mechanisms play a vital role in fulfilling the availability requirements. Multiple availability models have been proposed to assess compute systems, among which Bayesian network models have gained popularity in industry and research due to its powerful modeling formalism. In particular, this work focuses on assessing the availability of redundant and replicated cloud computing services with Bayesian networks. So far, research on availability has only focused on modeling either infrastructure or communication failures in Bayesian networks, but have not considered both simultaneously. This work addresses practical modeling challenges of assessing the availability of large-scale redundant and replicated services with Bayesian networks, including cascading and common-cause failures from the surrounding infrastructure and communication network. In order to ease the modeling task, this paper introduces a high-level modeling formalism to build such a Bayesian network automatically. Performance evaluations demonstrate the feasibility of the presented Bayesian network approach to assess the availability of large-scale redundant and replicated services. This model is not only applicable in the domain of cloud computing it can also be applied for general cases of local and geo-distributed systems.Comment: 16 pages, 12 figures, journa

Process behavior and product quality in fertilizer manufacturing using continuous hopper transfer pan granulation—Experimental investigations

Fertilizers are commonly used to improve the soil quality in both conventional and organic agriculture. One such fertilizer is dolomite for which soil application in granulated form is advantageous. These granules are commonly produced from ground dolomite powder in continuous pan transfer granulators. During production, the granulator’s operation parameters affect the granules’ properties and thereby also the overall performance of the fertilizer. To ensure product granules of certain specifications and an efficient overall production, process control and intensification approaches based on mathematical models can be applied. However, the latter require high-quality quantitative experimental data describing the effects of process operation parameters on the granule properties. Therefore, in this article, such data is presented for a lab-scale experimental setup. Investigations were carried out into how variations in binder spray rate, binder composition, feed powder flow rate, pan inclination angle, and angular velocity affect particle size distribution, mechanical stability, and humidity. Furthermore, in contrast to existing work samples from both, pan granules and product granules are analyzed. The influence of operation parameter variations on the differences between both, also known as trajectory separation, is described quantitatively. The results obtained indicate an increase in the average particle size with increasing binder flow rate to feed rate and increasing binder concentration and the inclination angle of the pan. Compressive strength varied significantly depending on the operating parameters. Significant differences in properties were observed for the product and the intermediate (pan) samples. In fact, for some operation parameters, e.g., binder feed rate, the magnitude of the separation effect strongly depends on the specific value of the operation parameter. The presented concise data will enable future mathematical modeling of the pan granulation process, e.g., using the framework of population balance equations

Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins

Stability of Combined Continuous Granulation and Agglomeration Processes in a Fluidized Bed with Sieve-Mill-Recycle

Particle formation in fluidized beds is widely applied in an industrial context for the solidification of liquids and size enlargement of granular materials. The two main size-enlargement mechanisms are layering growth and agglomeration. For continuous process configurations with sieve-mill-recycle and layering growth only, the occurrence of undesired self-sustained oscillations in the particle size distribution under certain process conditions is well-known. This contribution investigates the stability of the practically relevant process with additional particle agglomeration by means of a model-based numerical bifurcation analysis. It is shown that the occurrence of stable limit cycles is inhibited by an increased rate of particle agglomeration for a variety of different process conditions and different agglomeration kinetics. These results enhance the understanding of the agglomeration and layering growth dynamics and are relevant for the process design and operation

Helping a bio-inspired tactile sensor system to focus on the essential

Hellbach S, Otto M, Dürr V. Helping a bio-inspired tactile sensor system to focus on the essential. In: Proc. Int. Conf. Intell. Robot. Appl. IEEE; 2011: 24-33.Insects use their antennae (feelers) as near-range sensors for orientation, object localization and communication. This paper presents further developments for an approach for an active tactile sensor system. This includes a hardware construction as well as a software implementationfor interpreting the sensor readings. The discussed tactile sensor is able to detect an obstacle and its location. Furthermore the material properties of the obstacles are classied by application of neural networks. The focus of this paper lies in the development of a method which allows to determine automatically the part of the input data which is actually needed to fulll the classication task. For that, non-negative matrix factorization is evaluated by quantifying the trade-off between classication accuracy and input (and network) dimension

Stability of Combined Continuous Granulation and Agglomeration Processes in a Fluidized Bed with Sieve-Mill-Recycle

Particle formation in fluidized beds is widely applied in an industrial context for the solidification of liquids and size enlargement of granular materials. The two main size-enlargement mechanisms are layering growth and agglomeration. For continuous process configurations with sieve-mill-recycle and layering growth only, the occurrence of undesired self-sustained oscillations in the particle size distribution under certain process conditions is well-known. This contribution investigates the stability of the practically relevant process with additional particle agglomeration by means of a model-based numerical bifurcation analysis. It is shown that the occurrence of stable limit cycles is inhibited by an increased rate of particle agglomeration for a variety of different process conditions and different agglomeration kinetics. These results enhance the understanding of the agglomeration and layering growth dynamics and are relevant for the process design and operation