The majority of compute resources in todays scientific grids are based on Unix and Unix-like operating systems. In this world, user and user-group management are based around the concepts of a numeric 'user ID' and 'group ID' that are local to the resource. In contrast, grid concepts of user and group management are centered around globally assigned identifiers and VO membership, structures that are independent of any specific resource. At the fabric boundary, these 'grid identities' have to be translated to Unix user IDs. New job submission methodologies, such as job-execution web services, community-deployed local schedulers, and the late binding of user jobs in a grid-wide overlay network of 'pilot jobs', push this fabric boundary ever further down into the resource. gLExec, a light-weight (and thereby auditable) credential mapping and authorization system, addresses these issues. It can be run both on fabric boundary, as part of an execution web service, and on the worker node in a late-binding scenario. In this contribution we describe the rationale for gLExec, how it interacts with the site authorization and credential mapping frameworks such as LCAS, LCMAPS and GUMS, and how it can be used to improve site control and traceability in a pilot-job system.

https://iopscience.iop.org/article/10.1088/1742-6596/119/6/062032/pdf

gLExec: gluing grid computing to the Unix world

With the increasing size and complexity, adaptability is among the most badly needed properties in today’s Grid systems. Adaptability refers to the degree to which adjustments in practices, processes, or structures of systems are possible to projected or actual changes of their environment.

https://www.springer.com/cda/content/document/cda_downloaddocument/9780387279350-c2.pdf?SGWID=0-0-45-326607-p77146844

On Adaptability in Grid Systems

The Open Science Grid (OSG) and the Enabling Grids for E-sciencE (EGEE) have a common security model, based on Public Key Infrastructure. Grid resources grant access to users because of their membership in a Virtual Organization (VO), rather than on personal identity. Users push VO membership information to resources in the form of identity attributes, thus declaring that resources will be consumed on behalf of a specific group inside the organizational structure of the VO. Resources contact an access policies repository, centralized at each site, to grant the appropriate privileges for that VO group. Before the work in this paper, despite the commonality of the model, OSG and EGEE used different protocols for the communication between resources and the policy repositories. Hence, middleware developed for one Grid could not naturally be deployed on the other Grid, since the authorization module of the middleware would have to be enhanced to support the other Grid's communication protocol. In addition, maintenance and support for different authorization call-out protocols represents a duplication of effort for our relatively small community. To address these issues, OSG and EGEE initiated a joint project on authorization interoperability. The project defined a common communication protocol and attribute identity profile for authorization call-out and provided implementation and integration with major Grid middleware. The activity had resonance with middleware development communities, such as the Globus Toolkit and Condor, who decided to join the collaboration and contribute requirements and software. In this paper, we discuss the main elements of the profile, its implementation, and deployment in EGEE and OSG. We focus in particular on the operations of the authorization infrastructures of both Grids.

/pdf/xacml-profile-and-implementation-for-authorization-381eeocsfo.pdf

XACML profile and implementation for authorization interoperability between OSG and EGEE

A system (2) for updating an operating system image, includes a client device (4) using a current image version of the operating system image (6) and adapted for sending an information (8) about said current image version (6) to a boot server (12), a database (10) adapted to store information (14) about different image versions of said operating system image (12) used by said client device (4), and said boot server (12) adapted to access said database (10) to retrieve an information (14) about said different versions of said operating system image (12), to compare the information (8) about the current version (6) and the information (14) about the different versions (12) for determining an updated image version of said operating system (6, 12) for said client device (4). The client device (4) sends the information (8) about the current version of the operating system image (6) embedded in a Dynamic Host Configuration Protocol (DHCP) option packet (28).

System and a method for updating an operating system image

Large distributed computer systems have been successfully employed to solve modern scientific problems that were previously impracticable. Tools exist to bind together notably underutilized high speed computers and sizable storage resources, creating architectures that provide performance and capacity that scales with the quantity of resources invested. In various forms such as Internet computing, desktop grids, and even "big iron " grids, users and administrators find it difficult, however, to obtain aggregate systems that are more reliable than their underlying components and simple to utilize in concert. In this work, we will propose a model for controlling complex distributed systems and its application to the construction of scientific repositories.

/pdf/overdrive-controllers-for-distributed-scientific-computation-45gi7l9iw5.pdf

Overdrive Controllers for Distributed Scientific Computation

We present a framework for the co-ordinated, autonomic management of multiple clusters in a compute center and their integration into a Grid environment. Site autonomy and the automation of administrative tasks are prime aspects in this framework. The system behavior is continuously monitored in a steering cycle and appropriate actions are taken to resolve any problems. All presented components have been implemented in the course of the EU project DataGrid: The Lemon monitoring components, the FT fault-tolerance mechanism, the quattor system for software installation and configuration, the RMS job and resource management system, and the Gridification scheme that integrates clusters into the Grid.

/pdf/autonomic-management-of-large-clusters-and-their-integration-4ln9vgrv5p.pdf

Autonomic Management of Large Clusters and Their Integration into the Grid

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Autonomic Management of Large Clusters and Their Integration into the Grid