Ignacio Blanquer

Dynamic Management of Virtual Infrastructures

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.

Creating virtual storages and searching DICOM medical images through a grid middleware based in OGSA

Most medical imaging departments of hospital and primary care services in developed countries have migrated in the last years to full digital storing, management and processing. The availability of clinical medical images is larger than ever, but the exploitation of its intrinsic knowledge is poor. Hospitals, clinics and primary care centres store the information locally with a poor degree of interoperability. Although current archiving, flow-control and processing means and protocols of PACS are successful for reporting and patient follow-up, the archiving systems are not designed to exchange interesting cases, to search by medical content or to aggregate epidemiological information. This article presents a Middleware based on Grid Technologies that addresses the problem of sharing, transferring and processing DICOM medical images in a distributed environment. It tackles the problem of incompatibilities by providing a virtual storage that builds-up virtual repositories integrating different individual and incompatible storages providing global searching, progressive transmission, automatic encryption and pseudo-anonimisation and a hook to remote processing services. Users from a virtual organisation can share the cases that arc relevant for their topic of research, epidemiological study or even deeper analysis of a complex individual case. The article describes the architecture, the technologies used, the problems faced and the solutions proposed, and the results in the form of a brief performance analysis and several snapshots.

CodeCloud: A Platform to Enable Execution of Programming Models on the Clouds

This paper presents a platform that supports the execution of scientic applications covering dierent programming models (such as Master/Slave, Parallel/MPI, MapReduce and Workows) on Cloud infrastructures. The platform includes i) a high-level declarative language to express the requirements of the applications featuring software customization at runtime; ii) an approach based on virtual containers to encapsulate the logic of the dierent programming models; iii) an infrastructure manager to interact with dierent IaaS backends; iv) a conguration software to dynamically congure the provisioned resources and v) a catalog and repository of virtual machine images. By using this platform, an application developer can adapt, deploy and execute parallel applications agnostic to the cloud backend.

Supporting biodiversity studies with the EUBrazilOpenBio Hybrid Data Infrastructure

EUBrazilOpenBio is a collaborative initiative addressing strategic barriers in biodiversity research by integrating open access data and user‐friendly tools widely available in Brazil and Europe. The project deploys the EU‐Brazil Hybrid Data Infrastructure that allows the sharing of hardware, software and data on‐demand. This infrastructure provides access to several integrated services and resources to seamlessly aggregate taxonomic, biodiversity and climate data, used by processing services implementing checklist cross‐mapping and ecological niche modelling. A Virtual Research Environment was created to provide users with a single entry point to processing and data resources. This article describes the architecture, demonstration use cases and some experimental results and validation. Copyright

A parallel implementation of the k nearest neighbours classifier in three levels: threads, MPI processes and the grid

The work described in this paper tackles the problem of data mining and classification of large amounts of data using the K nearest neighbours classifier (KNN) [1]. The large computing demand of this process is solved with a parallel computing implementation specially designed to work in Grid environments of multiprocessor computer farms. The different parallel computing approaches (intra-node, inter-node and inter-organisations) are not sufficient by themselves to face the computing demand of such a big problem. Instead of using parallel techniques separately, we propose to combine the three of them considering the parallelism grain of the different parts of the problem. The main purpose is to complete a 1 month-CPU job in a few hours. The technologies that are being used are the EGEE Grid Computing Infrastructure running the Large Hadron Collider Computing Grid (LCG 2.6) middleware [3], MPI [4] [5] and POSIX [6] threads. Finally, we compare the results obtained with the most popular and used tools to understand the importance of this strategy.

Programming Ecological Niche Modeling Workflows in the Cloud

In the last decades biology scientists have relied on their own resources and tools to run the experiments and store the results of the analysis. However, the explosion of big data and the growing availability of computational methods find an obstacle in the lack of computational and storage resources. Cloud computing platforms are emerging as potential solution to overcome these limitations, but adaptation of the applications to enable scientific users to benefit from resources acquired on demand is a complex process requiring multidisciplinary expertise. The EUBrazilOpenBio initiative is implementing an e-Infrastructure that provides biodiversity community with a rich set of computational and data resources exploiting existing cloud technologies from EU and Brazil. This paper presents the implementation of one of the two use cases selected, the environmental niche modeling by means of implementing such workflow through the COMPSs framework and its deployment on the EUBrazil OpenBio platform. The proposed approach has been evaluated on a Cloud test bed managed by the VENUS-C middleware.

Service monitoring and differentiation techniques for resource allocation in the grid, on the basis of the level of service

The study of meta-scheduling of jobs in the Grid has been a recurrent topic on the literature. Many tools have been developed for allocating the jobs to the most appropriate resources according to specific application needs while balancing the workload among resources. However, few of them focus on evaluating the level of service attained by providers of Grid services. On the contrary, Grid generally offers best-effort service to all the applications. Without Quality of Service (QoS), the jobs are executed without any guarantee on the execution time or throughput. Also, the support for qualitative attributes, such as security, is limited to the information provided by the resources. The uncertainty on the final performance is an issue that affects user satisfaction, reducing the interest of Grid infrastructures. In this paper, we present GRIDIFF, a software architecture that covers all necessary steps to integrate QoS into the process of allocating resources for the execution of jobs in the Grid. GRIDIFF has been used in practice to differentiate the resources according to the fulfillment of the 100% of the QoS considering three groups with failure rates of 9.1%, 13.3% and 64.1%, respectively. Scalability has been evaluated through simulation in up to 7000 nodes that can handle up to 250 monitoring agents per node.

Cloud Services Representation using SLA Composition

SLA-aware Cloud platforms need mechanisms to represent, store and retrieve Cloud services. Usually services changes between different platforms, custom models are built to capture this information and ad-hoc implementations used to store and retrieve it. This paper propose a generic methodology for the representation of Cloud services. This methodology uses the WS-Agreement specification for capturing and manipulation arbitrary services using SLA fragments. SLA fragments are composed on the fly in response to user request. A SLA composition algorithm enables a prototype implementation of the methodology in a SLA-aware Cloud platform. This methodology provides the genericity, extensibility and flexibility to unify the modeling of Cloud services. Finally a use case provides a quantitative measure of the utility provided by the methodology from a Cloud user and Cloud provider point of view.

A platform to deploy customized scientific virtual infrastructures on the cloud

This paper presents a software platform to dynamically deploy complex scientific virtual computing infrastructures, on top of Infrastructure as a Service Clouds. The platform orchestrates different services to provision the virtual computing resources. It dynamically installs the appropriate software to satisfy the requirements of a researcher, both on public and on‐premise Clouds. The platform provides a web interface to enable the users to easily manage the life cycle of virtual infrastructures. It enables users to define infrastructures, share them with other users, deploy and relinquish them, add or remove resources dynamically, create and share application recipes, and so on. The paper also describes three case studies to deploy complex infrastructures, namely, a Hadoop cluster, a single‐node to perform Next Generation Sequencing and a gateway for users to access the European Grid Infrastructure. This platform promotes a better use of on‐premise hardware resources of a research center by allocating the computing resources just‐in‐time to the specific life time of the virtual infrastructures as well as the deployment of the very same infrastructures on a public Cloud. Copyright

Assessing the Usability of a Science Gateway for Medical Knowledge Bases with TRENCADIS

Biomedical applications are often built on top of knowledge bases that contain medical images and clinical reports. Currently, these bases are being used to improve diagnosis, research and teaching, but in many cases, the infrastructure required has a prohibitive cost for many medical centres. However, resources can be attached from existing e-Science infrastructures. Therefore, many efforts have been made to establish best practices that allow the use of such infrastructures. However, e-Science relies on open, distributed, collaborative environments, built on top of very specialized technologies, such as Grid and Cloud computing, which require reasonable technical skills for their usage. Therefore, science gateways have become essential tools that assist users in interacting with e-Science applications. This paper describes TRENCADIS, a technology that supports the creation and operation of virtual knowledge bases. To this end, it provides developers with components and APIs for building secure data services that can be annotated and queried through ontology templates, based on DICOM and DICOM-SR. This technology was used in this paper to build a gateway for assisting diagnosis and research in breast cancer. We also present here the results of a study conducted to evaluate the gateway, from the point of view of the usability perceived by a group of physicians and radiologists.