Vol. 31 · No. 1

This article describes the process of defining and implementing new components to exchange data between two real GRID-based platforms for breast cancer diagnosis. This highly collaborative work in development phase pretends to allow communication between middleware, namely TRENCADIS and DRI, in different virtual organizations. On the one hand, TRENCADIS is a Service-Oriented Architecture in which the usage of resources is represented with Grid services based on the Open Grid Service Architecture specification (OGSA).On the other hand, DRI is a software platform aimed at reducing the cost of hosting digital repositories of arbitrary nature on Grid infrastructures. TRENCADIS has been deployed in the Dr. Peset Hospital (Valencia, Spain) and DRI has been deployed in the S ao Jo ao Hospital (Porto, Portugal). The final objective of this work in progress is to share medical images and its associated metadata among geographically distributed research institutions, while maintaining confidentiality and privacy of data.

We present an infrastructure in which HPC resources from the Amazon Web Services public cloud are combined with specific grid resources at Ibergrid. The integration is done transparently for the GridWay users through a daemon which permanently monitors the pool of available resources and submitted jobs, managing virtual instances for satisfying the demand under budget restrictions. The study has been proved with a specific application from the Xmipp package, which performs image processing from electron microscopy data and requires heavy high-throughput computing offering parallelization capabilities. The application was ported successfully for such a hybrid framework with the help of the MPI-Start package. Some preliminary results from test runs are presented for a controlled sample of thousand input images. Some inconveniences and troublesome aspects of the deployment are also reported.

The design of enhanced fusion devices constitutes a key element for the development of fusion as a commercial source of energy. Stellarator optimization presents high computational requirements because of the complexity of the numerical methods needed as well as the size of the solution space regarding all the possible configurations satisfying the characteristics of a feasible reactor. The size of the solution space does not allow to explore every single feasible configuration. Hence, a metaheuristic approach is used to achieve optimized configurations without evaluating the whole solution space. In this paper we present a distributed algorithm that mimics the foraging behaviour of bees. This behaviour has manifested its efficiency in dealing with complex problems.

During the last years, the cloud computing technology has emerged as a new way to obtain computing resources on demand in a very dynamic fashion and only paying for what you consume. Nowadays, there are several hosting providers which follow this approach, offering resources with different capabilities, prices and SLAs. Therefore, depending on the users' preferences and the application requirements, a resource provider can fit better with them than another one. In this paper, we present an architecture for federating clouds, aggregating resources from different providers, deciding which resources and providers are the best for the users' interests, and coordinating the application deployment in the selected resources giving to the user the impression that a single cloud is used.

In this article we present the strategies foreseen to foster the usage of the Iberian production infrastructure by regional scientific communities. The main focus is on describing the user support mechanisms implemented through a cooperative effort from the Portuguese and Spanish user support teams, and on the services and tools offered to the regional user communities for their use and customization, to foster VO production user activity within the Iberian region.

The establishment of agreements between users and the entities which manage the Grid resources is still a challenging task. On the one hand, an entity in charge of dealing with the communication with the users is needed, with the aim of signing resource usage contracts and also implementing some renegotiation techniques, among others. On the other hand, some mechanisms should be implemented which decide if the QoS requested could be achieved and, in such case, ensuring that the QoS agreement is provided. One way of increasing the probability of achieving the agreed QoS is by performing meta-scheduling of jobs in advance, that is, jobs are scheduled some time before they are actually executed. In this way, it becomes more likely that the appropriate resources are available to run the jobs when needed. So, this paper presents a framework built on top of Globus and the GridWay meta-scheduler to provide QoS by means of performing meta-scheduling in advance. Thanks to this, QoS requirements of jobs are met (i.e. jobs are finished within a deadline). Apart from that, the mechanisms needed to manage the communication between the users and the system are presented and implemented through SLA contracts based on the WS-Agreement specification.

Migrating traditional scientific applications to computational Grids requires programming tools that can help programmers update application behaviour to this kind of platforms. Computational Grids are particularly suited for long running scientific applications, but they are also more prone to faults than desktop machines. The AspectGrid framework aims to develop methodologies and tools that can help Grid-enable scientific applications, particularly focusing on techniques based on aspect-oriented programming. In this paper we present the aspect-oriented approach taken in the AspectGrid framework to address faults in computational Grids. In the proposed approach, scientific applications are enhanced with fault-tolerance capability by plugging additional modules. The proposed technique is portable across operating systems and minimises the changes required to base applications.

Security on Grid computing is often an afterthought. However assessing security of middleware systems is of the utmost importance because they manage critical resources owned by different organizations. To fulfill this objective we use First Principles Vulnerability Assessment (FPVA), an innovative analystic-centric (manual) methodology that goes beyond current automated vulnerability tools. FPVA involves several stages for characterizing the analyzed system and its components. Based on the evaluation of several middleware systems, we have found that there is a gap between the initial and the last stages of FPVA, which is filled with the security practitioner expertise. We claim that this expertise is likely to be systematically codified in order to be able to automatically indicate which, and why, components should be assessed. In this paper we introduce key elements of our approach: Vulnerability graphs, Vulnerability Graph Analyzer, and a Knowledge Base of security configurations.

This paper describes the architecture for transparently using several different Cloud Resources from with the graphical Kepler Worklfow environment. This architecture was proven to work by implementing and using it in practice within the FP7 EUFORIA project. The clouds supported are the Open Source cloud OpenNEbula (ONE) environment and the commercial Amazon Elastic Compute Cloud (EC2). Subsequently, these clouds are compared regarding their cost-effectiveness, which covers a performance examination but also the comparison of the commercial against a scientific cloud provider.

The European Grid Initiative (EGI) provides a sustainable pan-European Grid computing infrastructure for e-Science based on a network of regional and national Grids. The middleware driving this production infrastructure is constantly adapted to the changing needs of the EGI Community by deploying new features and phasing out other features and components that are no longer needed. Unlike previous e-Infrastructure projects, EGI does not develop its own middleware solution, but instead sources the required components from Technology Providers and integrates them in the Unified Middleware Distribution (UMD). In order to guarantee a high quality and reliable operation of the infrastructure, all UMD software must undergo a release process that covers the definition of the functional, performance and quality requirements, the verification of those requirements and testing in production environments.

The current middleware stacks provide varying support for the Message Passing Interface (MPI) programming paradigm. Users face a complex and heterogeneous environment where too many low level details have to be specified to execute even the simplest parallel jobs. MPI-Start is a tool that provides an interoperable MPI execution framework across the different middleware implementations to abstract the user interfaces from the underlying middleware and to allow users to execute parallel applications in a uniform way, thus bridging the gap between HPC and HTC. In this work we present the latest developments in MPI-Start and how it can be integrated in the different middleware stacks available as part of EMI, providing a unified user experience for MPI jobs.

PireGrid citepiregrid (Project Number EFA35/08) is an INTERREG IV A project which has two main objectives, namely the deployment of a production Grid Computing infrastructure in the regions of Aragon, Aquitaine and Midi-Pyrenees and the achievement of successful cases in execution of applications from small and medium size companies of the named regions, in order to demonstrate its usage of these emerging technologies to the companies. In the framework of this project we present Optiweb, which is the first successful porting of an application from Schnell Software citeschnell company, and the process followed to adapt it to a web interface and its transparent execution in a gLite grid infrastructure.

For a long time grid has been used practically only by large projects which can afford to have fine-tuned sophisticated interfaces for the researchers involved on these projects. Grid has the potential to be a key instrument for a wide variety of scientific topics which require to perform many calculations, for example to explore complex system dynamics as function of parameters. The reduced size of the research groups and the diversity of problems makes unsuitable to develop specific interfaces in most of the instances while the cumbersome grid shell commands are a barrier that requires a significant amount of determination to overcome. Web4Grid interface is intended to be a user-friendly web where grid users can submit their jobs and recover the results on an automatic way. Besides the interface provides the capability to monitor the existing jobs and to check the (local) grid status (load, number of free cores available, ...). Web4Grid interface does not require specific grid usage training nor any knowledge about the middleware behind it.

In this paper we present X2R, a system for integrating heterogeneous data sources in an ontological knowledge base. The main goal of the system is to create a unified view of information stored in relational, XML and LDAP data sources within an organization, expressed in RDF using a common ontology and valid according to a prescribed set of integrity constraints. X2R supports a wide range of source schemas and target ontologies by allowing the user to define potentially complex transformations of data between the original data source and the unified knowledge base. A rich set of integrity constraint primitives has been provided to ensure the quality of the unified data set. They are also leveraged in a novel approach towards semantic optimization of SPARQL queries.

Breast cancer (B-cancer) detection is still complex and challenging problem, and in that case, we propose and evaluate a four-step approach to segment and detect B-cancer disease. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively slow and inaccurate in some cases. Providing automatic, fast, and accurate image-processing-and artificial intelligence-based solutions for that task can be of great realistic significance. The presented approach itself scans the whole mammogram and performs filtering, segmentation, features extraction, and detection in a succession mode. The feasibility of the proposed approach was explored on 32 commonly virulent images, and the recognition rate achieved in the detection step is 100