Grid Component Model Research Articles

Bringing Coq into the World of GCM Distributed Applications

Among all programming paradigms, component-based engineering stands as one of the most followed approaches for real world software development. Its emphasis on clean separation of concerns and reusability makes it appealing for both industrial and research purposes. The Grid Component Model (GCM) endorses this approach in the context of distributed systems by providing all the means to define, compose and dynamically reconfigure component-based applications. While structural reconfiguration is one of the key features of GCM applications, this ability to evolve at runtime poses several challenges w.r.t reliability. In this paper we present Mefresa, a framework for reasoning on the structure of GCM applications. This contribution comes in the form of a formal specification mechanized in the Coq Proof Assistant. Our aim is to demonstrate the benefits of interactive theorem proving for the reasoning on software architectures. We provide a configuration and reconfiguration language for the safe instantiation of distributed systems.

Process-driven biometric identification by means of autonomic grid components

Today’s business applications are increasingly process driven, meaning that the main application logic is executed by a dedicate process engine. In addition, component-oriented software development has been attracting attention for building complex distributed applications. In this paper, we present the experiences gained from building a process-driven biometric identification application that makes use of grid infrastructures via the Grid Component Model (GCM). GCM, besides guaranteeing access to grid resources, supports autonomic management of notable parallel composite components. This feature is exploited within our biometric identification application to ensure real-time identification of fingerprints. Therefore, we briefly introduce theGCMframework and the process engine used, and we describe the implementation of the application by means of autonomicGCMcomponents. Finally, we summarise the results, experiences and lessons learned focusing on the integration of autonomic GCM components and the process-driven approach.

Component-based approach for programming and running scientific applications on grids and clouds

This paper presents an approach to programming and running scientific applications on grid and cloud infrastructures based on two principles: the first one is to follow a component-based programming model, the second is to apply a flexible technology which allows for virtualization of the underlying infrastructure. The solutions described in this paper include high-level composition and deployment consisting of a scripting-based environment and a manager system based on an architecture description language (ADL), a dynamically managed pool of component containers, and interoperability with other component models such as Grid Component Model (GCM). We demonstrate how the proposed methodology can be implemented by combining the unique features of the Common Component Architecture (CCA) model together with the H2O resource sharing platform, resulting in the MOCCA component framework. Applications and tests include data mining using the Weka library, Monte Carlo simulation of the formation of clusters of gold atoms, as well as a set of synthetic benchmarks. The conclusion is that the component approach to scientific applications can be successfully applied to both grid and cloud infrastructures.

GCM: a grid extension to Fractal for autonomous distributed components

This article presents an extension of the Fractal component model targeted at programming applications to be run on computing grids: the grid component model (GCM). First, to address the problem of deployment of components on the grid, deployment strategies have been defined. Then, as grid applications often result from the composition of a lot of parallel (sometimes identical) components, composition mechanisms to support collective communications on a set of components are introduced. Finally, because of the constantly evolving environment and requirements for grid applications, the GCM defines a set of features intended to support component autonomicity. All these aspects are developed in this paper with the challenging objective to ease the programming of grid applications, while allowing GCM components to also be the unit of deployment and management.