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Various scientific and commercial applications require automated scalability and orchestration on cloud computing resources. However, extending applications with such automated scalability on an individual basis is not feasible. This paper investigates how such automated orchestration can be added to cloud applications without major reengineering of the application code. We suggest a generic architecture for an application level cloud orchestration framework, called MiCADO that supports various application scenarios on multiple heterogeneous federated clouds. Besides the generic architecture description, the paper also presents the first MiCADO reference implementation, and explains how the scalability of the Data Avenue service that is applied for data transfer in WS-PGRADE/gUSE based science gateways, can be improved. Performance evaluation of the implemented scalability based on up and downscaling experiments is presented.

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Fulfilling a service request in highly dynamic service environments may require deploying a service. Therefore, the effectiveness of service deployment systems affects initial service response times. On Infrastructure as a Service (IaaS) cloud systems deployable services are encapsulated in virtual appliances. Services are deployed by instantiating virtual machines with their virtual appliances. The virtual machine instantiation process is highly dependent on the size and availability of the virtual appliance that is maintained by service developers. This article proposes an automated virtual appliance creation service that aids the service developers to create efficiently deployable virtual appliances -in former systems this task was carried out manually by the developer. We present an algorithm that decomposes these appliances in order to replicate the common virtual appliance parts in IaaS systems. These parts are used to reduce the deployment time of the service by rebuilding the virtual appliance of the service on the deployment target site. With the prototype implementation of the proposed algorithms we demonstrate the decomposition and appliance rebuilding algorithms on a complex web service.

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RNAPs (RNA polymerases) are complex molecular machines that contain a highly conserved catalytic site surrounded by conformationally flexible domains. High-throughput mutagenesis in the archaeal model system Methanocaldococcus jannaschii has demonstrated that the nanomechanical properties of one of these domains, the bridge-helix, exert a key regulatory role on the rate of the NAC (nucleotide-addition cycle). Mutations that increase the probability and/or half-life of kink formation in the BH-HC (bridge-helix C-terminal hinge) cause a substantial increase in specific activity ('superactivity'). Fully atomistic molecular dynamics simulations show that kinking of the BH-HC appears to be driven by cation-π interactions and involve amino acid side chains that are exceptionally highly conserved in all prokaryotic and eukaryotic species.

Carbohydrate recognition is a phenomenon critical to a number of biological functions in humans. Understanding the dynamic behaviour of oligosaccharides should help in the discovery of the mechanisms which lead to specific and selective recognition of carbohydrates by proteins. Computer programs which can provide insight into such biological recognition processes have significant potential to contribute to biomedical research if the results of the simulation can prove consistent with the outcome of conventional wet laboratory experiments. In order to validate these simulation tools and support their wider uptake by the bio-scientist research community, high-level easy to use integrated environments are required to run massively parallel simulation workflows. This paper describes how the ProSim Science Gateway, based on the WS-PGRADE Grid portal, has been created to execute and visualise the results of complex parameter sweep workflows for modelling carbohydrate recognition.T. Kiss (B) · G. Terstyanszky · N. Weingarten

SUMMARYMolecular docking simulations have high potential to contribute to a wide area of molecular and biomedical research in various disciplines including molecular biology, drug design, environmental studies and psychology. Conducting large‐scale molecular docking experiments requires a vast amount of computing resources. Several types of distributed computing infrastructures have been investigated and utilized recently to conduct such simulations, including service and desktop grid systems or local clusters. This paper investigates and analyses how Windows Azure‐based cloud resources can be applied for this purpose. A virtual screening experiment framework has been implemented on a Windows Azure‐based cloud using the generic worker concept. Virtual machines can be instantiated in the cloud on demand scaling up the simulations based on the volume of molecules to be docked and the available financial resources. Bioscientists are able to execute the simulations and visualise the results from a high‐level user interface. The paper describes the experiences when implementing the molecular docking application on this novel platform and provides the first benchmarking experiments to evaluate the suitability of the infrastructure for computation intensive simulations. Copyright © 2013 John Wiley & Sons, Ltd.