Experimental evaluation of foil-supported resilient-pad gas-lubricated thrust bearing

A new type of resilient-pad gas thrust bearing was tested to determine the feasibility of the design. The bearing consists of carbon graphite pads mounted asymmetrically on foil beams. Two bearing configurations were tested at thrust loads from 27 to 80 newtons at speeds to 9000 rpm. The outside diameter of the bearing was 8.9 centimeters

Evaluation of chromium oxide and molybdenum disulfide coatings in self-acting stops of an air-lubricated Rayleigh step thrust bearing

Two coatings for a Rayleigh step thrust bearing were tested when coasting down and stopping under self-acting operation in air. The thrust bearing had an outside diameter of 8.9 cm (3.5 in.), an inside diameter of 5.4 cm (2.1 in.), and nine sectors. The load was 73 N (16.4 lbf). The load pressure was 19.1 kN/per square meter (2.77 lbf/per square inch) on the total thrust bearing area. The chromium oxide coating was good to 150 stops without bearing deterioration, and the molybdenum disulfide coating was good for only four stops before bearing deterioration. The molybdenum disulfide coated bearing failed after nine stops

Cloud Workload Prediction by Means of Simulations

Clouds hide the complexity of maintaining a physical infrastructure with a disadvantage: they also hide their internal workings. Should users need to know about these details e.g., to increase the reliability or performance of their applications, they would need to detect slight behavioural changes in the underlying system. Existing solutions for such purposes offer limited capabilities. This paper proposes a technique for predicting background workload by means of simulations that are providing knowledge of the underlying clouds to support activities like cloud orchestration or workflow enactment. We propose these predictions to select more suitable execution environments for scientific workflows. We validate the proposed prediction approach with a biochemical application

Towards efficient virtual appliance delivery with minimal manageable virtual appliances

Infrastructure as a Service systems use virtual appliances to initiate virtual machines. As virtual appliances encapsulate applications and services with their support environment, their delivery is the most expensive task of the virtual machine creation. Virtual appliance delivery is a well-discussed topic in the field of cloud computing. However, for high efficiency, current techniques require the modification of the underlying IaaS systems. To target the wider adoptability of these delivery solutions, this article proposes the concept of minimal manageable virtual appliances (MMVA) that are capable of updating and configuring their virtual machines without the need to modify IaaS systems. To create MMVAs, we propose to reduce manageable virtual appliances until they become MMVAs. This research also reveals a methodology for appliance developers to incorporate MMVAs in their own appliances to enable their efficient delivery and wider adoptability. Finally, the article evaluates the positive effects of MMVAs on an already existing delivery solution: the Automated Virtual appliance creation Service (AVS). Through experimental evaluation, we present that the application of MMVAs not only increases the adoptability of a delivery solution but it also significantly improves its performance in highly dynamic systems. © 2013 IEEE

Facilitating self-adaptable inter-cloud management

Cloud Computing infrastructures have been developed as individual islands, and mostly proprietary solutions so far. However, as more and more infrastructure providers apply the technology, users face the inevitable question of using multiple infrastructures in parallel. Federated cloud management systems offer a simplified use of these infrastructures by hiding their proprietary solutions. As the infrastructure becomes more complex underneath these systems, the situations (like system failures, handling of load peaks and slopes) that users cannot easily handle, occur more and more frequently. Therefore, federations need to manage these situations autonomously without user interactions. This paper introduces a methodology to autonomously operate cloud federations by controlling their behavior with the help of knowledge management systems. Such systems do not only suggest reactive actions to comply with established Service Level Agreements (SLA) between provider and consumer, but they also find a balance between the fulfillment of established SLAs and resource consumption. The paper adopts rule-based techniques as its knowledge management solution and provides an extensible rule set for federated clouds built on top of multiple infrastructures. © 2012 IEEE