Comparison of advanced authorisation infrastructures for grid computing

The widespread use of grid technology and distributed compute power, with all its inherent benefits, will only be established if the use of that technology can be guaranteed efficient and secure. The predominant method for currently enforcing security is through the use of public key infrastructures (PKI) to support authentication and the use of access control lists (ACL) to support authorisation. These systems alone do not provide enough fine-grained control over the restriction of user rights, necessary in a dynamic grid environment. This paper compares the implementation and experiences of using the current standard for grid authorisation with Globus - the grid security infrastructure (GSI) - with the role-based access control (RBAC) authorisation infrastructure PERMIS. The suitability of these security infrastructures for integration with regard to existing grid technology is presented based upon experiences within the JISC-funded DyVOSE project

AstroGrid-D: Grid Technology for Astronomical Science

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites, and advanced applications for specific scientific purposes, such as a connection to robotic telescopes. We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.Comment: 14 pages, 12 figures Subjects: data analysis, image processing, robotic telescopes, simulations, grid. Accepted for publication in New Astronom

TOWARDS INSTITUTIONAL INFRASTRUCTURES FOR E-SCIENCE: The Scope of the Challenge

The three-fold purpose of this Report to the Joint Information Systems Committee (JISC) of the Research Councils (UK) is to: • articulate the nature and significance of the non-technological issues that will bear on the practical effectiveness of the hardware and software infrastructures that are being created to enable collaborations in e- Science; • characterise succinctly the fundamental sources of the organisational and institutional challenges that need to be addressed in regard to defining terms, rights and responsibilities of the collaborating parties, and to illustrate these by reference to the limited experience gained to date in regard to intellectual property, liability, privacy, and security and competition policy issues affecting scientific research organisations; and • propose approaches for arriving at institutional mechanisms whose establishment would generate workable, specific arrangements facilitating collaboration in e-Science; and, that also might serve to meet similar needs in other spheres such as e- Learning, e-Government, e-Commerce, e-Healthcare. In carrying out these tasks, the report examines developments in enhanced computer-mediated telecommunication networks and digital information technologies, and recent advances in technologies of collaboration. It considers the economic and legal aspects of scientific collaboration, with attention to interactions between formal contracting and 'private ordering' arrangements that rest upon research community norms. It offers definitions of e-Science, virtual laboratories, collaboratories, and develops a taxonomy of collaborative e-Science activities which is implemented to classify British e-Science pilot projects and contrast these with US collaboratory projects funded during the 1990s. The approach to facilitating inter-organizational participation in collaborative projects rests upon the development of a modular structure of contractual clauses that permit flexibility and experience-based learning.

Analysis of current middleware used in peer-to-peer and grid implementations for enhancement by catallactic mechanisms

This deliverable describes the work done in task 3.1, Middleware analysis: Analysis of current middleware used in peer-to-peer and grid implementations for enhancement by catallactic mechanisms from work package 3, Middleware Implementation. The document is divided in four parts: The introduction with application scenarios and middleware requirements, Catnets middleware architecture, evaluation of existing middleware toolkits, and conclusions. -- Die Arbeit definiert Anforderungen an Grid und Peer-to-Peer Middleware Architekturen und analysiert diese auf ihre Eignung für die prototypische Umsetzung der Katallaxie. Eine Middleware-Architektur für die Umsetzung der Katallaxie in Application Layer Netzwerken wird vorgestellt.Grid Computing

State of the Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly suited to general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems five different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix.

Data Grid tutorials with hands-on experience

Grid technologies are more and more used in scientific as well as in industrial environments but often documentation and the correct usage are either not sufficient or not too well understood. Comprehensive training with hands-on experience helps people first to understand the technology and second to use it in a correct and efficient way. We have organised and run several training sessions in different locations all over the world and provide our experience. The major factors of success are a solid base of theoretical lectures and, more dominantly, a facility that allows for practical Grid exercises during and possibly after tutorial sessions

Grid service-based e-learning systems architecures

E-Learning has been a topic of increasing interest in recent years, due mainly to the fact that content and tool support can now be offered at a widely affordable level. As a result, many elearning platforms and systems have been developed. Client-server, peer-to-peer and recently Web services architectures often form the basis. Major drawbacks of these architectures are their limitations in terms of scalability and the availability and distribution of resources. This chapter investigates grid architectures in the context of e-learning as a proposed answer for this problem. The principles and technologies of Grid architectures are discussed and illustrated using learning technology scenarios and systems

State-of-the-Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly useful for general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems four different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix