Scientific computing applications usually need huge amounts of computational power. The cloud provides interesting high-performance computing solutions, with its promise of virtually infinite resources on demand. However, migrating scientific computing problems to clouds and the re-creation of software environment on the vendor-supplied OS and cloud instances is often a laborious task. It is also assumed that the scientist who is performing the experiments has significant knowledge of computer science, cloud computing and the migration procedure, which is often not true. Considering these obstacles, we have designed a tool suite that migrates the complete software environment directly to the cloud. The developed desktop-to-cloud-migration (D2CM) tool supports transformation and migration of virtual machine images, reusable deployment description and life-cycle management for applications to be hosted on Amazon Cloud or compatible infrastructure such as Eucalyptus. The paper also presents an electrochemical case study and computational experiments targeted at designing modern supercapacitors. These experiments have extensively used the tool in drawing domain specific results. Detailed analysis of the case showed that D2CM tool not only simplifies the migration procedure for the scientists, but also helps them in optimizing the calculations and compute clusters, by providing them a new dimension -- cost-to-value of computational experiments.
VIRTU framework @cite_6 is a framework for configuration, deployment, and management of the life-cycle of distributed virtual environments. It provides users the ability to manage and configure application stacks on such environments by assembling building blocks consisting of operating system and application together with installation and configuration files. This framework is interesting for us because it deals with the deployment of distributed environments that large-scale scientific computing experiments most often require, with the main difference that it is not designed for Cloud, but rather for deploying virtual machines and applications on existing hardware.
@cite_6
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The recent developments in virtualization change completely the panorama of the Hardware OS deployment. New bottlenecks arise in the deployment of application stacks, where IT industry will spend most of the time to assure automation. VIRTU tool aims at managing, configuring and testing distributed ground applications of space systems on a virtualized environment, based on open tools and cross virtualization support. This tool is a spin-off of previous activities performed by the European Space Operations Center (ESOC) and thus it covers the original needs from the ground data systems infrastructure division of the European Space Agency. VIRTU is a testing oriented solution. Its ability to group several virtual machines in an assembly provides the means to easily deploy a full testing infrastructure, including the client server relationships. The possibility of making on-demand request of the testing infrastructure will provide some infrastructure optimizations, specially having in mind that ESA maintains Ground Control software of various missions, and each mission cam potentially have a different set of System baselines and last up to 15 years. The matrix array of supported system combinations is therefore enormous and any improvement on the process provides substantial benefits to ESA, by reducing the effort and schedule of each maintenance activity. The ESOC's case study focuses on the development and validation activities of infrastructure or mission Ground Systems solutions. The Ground Systems solutions are typically composed of distributed systems that could take advantage of virtualized environments for testing purposes. Virtualization is used as way to optimize maintenance for tasks such as testing new releases and patches, test different system's configurations and replicate tests. The main benefits identified are related to deployment test environment and the possibility to have on-demand infrastructure. In this paper, we present a hierarchical smart resource coordination and reconfiguration framework for distributed systems. We view the coordination problem as one of context aware resource reconfiguration. The fundamental unit in this hierarchy is a Fault Containment Unit (FCU) that provides run-time fault-tolerance by deciding on the best alternative course of action when a failure occurs. FCUs are composed hierarchically and are responsible for dynamically reconfiguring failing FCUs at lower levels. When such a reconfiguration is not possible, FCUs propagate the failure upward for resolution. We evaluate the effectiveness of our framework in a people tracking application using a network of cameras. The task for our multi-camera network is to allocate pairs of cameras that localize a subject optimally given the current run-time context. The system automatically derives policies for switching between camera pairs that enable robust tracking while being attentive to certain performance measures. Our approach is unique in that we model the dynamics in the scene and the camera network configuration steers the policies to provide robust tracking. This paper studies an evolutionary game theoretic framework for adaptive and stable application deployment in clouds. The framework, called Cielo, aids cloud operators to adapt the resource allocation to applications and their locations to the operational conditions in a cloud (e.g., workload and resource availability) with respect to multiple conflicting objectives (e.g., response time and power consumption). Moreover, Cielo theoretically guarantees that each application performs an evolutionarily stable deployment strategy, which is an equilibrium solution under given operational conditions. Simulation results verify this theoretical analysis, applications seek equilibria to perform adaptive and evolutionarily stable deployment strategies. Cielo outperforms well-known existing heuristics. Cloud infrastructures are becoming an appropriate solution to address the computational needs of scientific applications. However, the use of public or on-premises Infrastructure as a Service (IaaS) clouds requires users to have non-trivial system administration skills. Resource provisioning systems provide facilities to choose the most suitable Virtual Machine Images (VMI) and basic configuration of multiple instances and subnetworks. Other tasks such as the configuration of cluster services, computational frameworks or specific applications are not trivial on the cloud, and normally users have to manually select the VMI that best fits, including undesired additional services and software packages. This paper presents a set of components that ease the access and the usability of IaaS clouds by automating the VMI selection, deployment, configuration, software installation, monitoring and update of Virtual Appliances. It supports APIs from a large number of virtual platforms, making user applications cloud-agnostic. In addition it integrates a contextualization system to enable the installation and configuration of all the user required applications providing the user with a fully functional infrastructure. Therefore, golden VMIs and configuration recipes can be easily reused across different deployments. Moreover, the contextualization agent included in the framework supports horizontal (increase decrease the number of resources) and vertical (increase decrease resources within a running Virtual Machine) by properly reconfiguring the software installed, considering the configuration of the multiple resources running. This paves the way for automatic virtual infrastructure deployment, customization and elastic modification at runtime for IaaS clouds.