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In order to ensure interoperability between middleware and authorization infrastructures used in the Open Science Grid (OSG) and the Enabling Grids for E-science (EGEE) projects, an Authorization Interoperability activity was initiated in 2006. The interoperability goal was met in two phases: firstly, agreeing on a common authorization query interface and protocol with an associated profile that ensures standardized use of attributes and obligations; and secondly implementing, testing, and deploying on OSG and EGEE, middleware that supports the interoperability protocol and profile. The activity has involved people from OSG, EGEE, the Globus Toolkit project, and the Condor project. This paper presents a summary of the agreed-upon protocol, profile and the software components involved.

In recent years, several new storage technologies, such as Lustre, Hadoop, OrangeFS, and BlueArc, have emerged. While several groups have run benchmarks to characterize them under a variety of configurations, more work is needed to evaluate these technologies for the use cases of scientific computing on Grid clusters and Cloud facilities. This paper discusses our evaluation of the technologies as deployed on a test bed at FermiCloud, one of the Fermilab infrastructure-as-a-service Cloud facilities. The test bed consists of 4 server-class nodes with 40 TB of disk space and up to 50 virtual machine clients, some running on the storage server nodes themselves. With this configuration, the evaluation compares the performance of some of these technologies when deployed on virtual machines and on "bare metal" nodes. In addition to running standard benchmarks such as IOZone to check the sanity of our installation, we have run I/O intensive tests using physics-analysis applications. This paper presents how the storage solutions perform in a variety of realistic use cases of scientific computing. One interesting difference among the storage systems tested is found in a decrease in total read throughput with increasing number of client processes, which occurs in some implementations but not others.

A neural map algorithm has been employed to control a five-joint pneumatic robot arm and gripper through feedback from two video cameras. The pneumatically driven robot arm (SoftArm) employed in this investigation shares essential mechanical characteristics with skeletal muscle systems. To control the position of the arm, 200 neurons formed a network representing the three-dimensional workspace embedded in a four-dimensional system of coordinates from the two cameras, and learned a three-dimensional set of pressures corresponding to the end effector positions, as well as a set of 3/spl times/4 Jacobian matrices for interpolating between these positions. The gripper orientation was achieved through adaptation of a 1/spl times/4 Jacobian matrix for a fourth joint. Because of the properties of the rubber-tube actuators of the SoftArm, the position as a function of supplied pressure is nonlinear, nonseparable, and exhibits hysteresis. Nevertheless, through the neural network learning algorithm the position could be controlled to an accuracy of about one pixel (/spl sim/3 mm) after 200 learning steps and the orientation could be controlled to two pixels after 800 learning steps. This was achieved through employment of a linear correction algorithm using the Jacobian matrices mentioned above. Applications of repeated corrections in each positioning and grasping step leads to a very robust control algorithm since the Jacobians learned by the network have to satisfy the weak requirement that the Jacobian yields a reduction of the distance between gripper and target. The neural network employed in the control of the SoftArm bears close analogies to a network which successfully models visual brain maps. It is concluded, therefore, from this fact and from the close analogy between the SoftArm and natural muscle systems that the successful solution of the control problem has implications for biological visuo-motor control. >

A method by which an LDAP directory can be searched using XQuery is described. The strategy behind the tool consists of four steps. First the XQuery script is examined and relevant XPath expressions are extracted, determined to be sufficient to define all information needed to perform the query. Then the XPath expressions are converted into their equivalent LDAP search filters by use of the published LDAP schema of the service, and search requests are made to the LDAP host. The search results are then merged and converted to an XML document that conforms to the hierarchy of the LDAP schema. Finally, the XQuery script is executed on the working XML document by conventional means. Examples are given of application of the tool in the Open Science Grid, which for discovery purposes operates an LDAP server that contains Glue schema-based information on site configuration and authorization policies. The XQuery scripts compactly replace hundreds of lines of custom python code that relied on the unix ldapsearch utility. Installation of the tool is available through the Virtual Data Toolkit.

The Authorization Interoperability activity was initiated in 2006 to foster interoperability between middleware and authorization infrastructures deployed in the Open Science Grid (OSG) and the Enabling Grids for E-sciencE (EGEE) projects. This activity delivered a common authorization protocol and a set of libraries that implement that protocol. In addition, a set of the most common Grid gateways, or Policy Enforcement Points (Globus Toolkit v4 Gatekeeper, GridFTP, dCache, etc.) and site authorization services, or Policy Decision Points (LCAS/LCMAPS, SCAS, GUMS, etc.) have been integrated with these libraries. At this time, various software providers, including the Globus Toolkit v5, BeStMan, and the Site AuthoriZation service (SAZ), are integrating the authorization interoperability protocol with their products. In addition, as more and more software supports the same protocol, the community is converging on LCMAPS as a common module for identity attribute parsing and authorization call-out. This paper presents this effort, discusses the status of adoption of the common protocol and projects the community work on authorization in the near future.

The non-Markovian Fokker-Planck equation in the energy variable for a system with a driving force is employed to find the escape rate of a particle in a potential well. The energy-dependent diffusion coefficient is the integral of the spectral densities of the applied force and the velocity of the system. The escape-rate formula is applied to resonant activation of a Josephson junction by a microwave driving current with a good comparison to experimental results.

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.

The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information pool is disorganized, it is a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation, and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by loosely coupled or fully decoupled middleware.

We describe a new algorithm for vector quantization and control. The algorithm, in addition to generating a discrete representation of input data by means of Voronoi polyhedra, also generates a tesselation associated with these polyhedra. The tesselation corresponds to a graph which connects neighbouring Voronoi polyhedra and, hence, reflects neighborhood relationships of the embedding space of the data. The algorithm can be extended to approximate through ‘training’ arbitrary functions defined on the data points. The tesselation allows one to speed up the ‘training’ through cooperative learning involving nearest, next-nearest, etc. Voronoi polyhedra, reducing the range of cooperation progressively during training. The algorithm produces a table look-up program, assigning optimally tables to inputs and generating rapidly optimal table entries. The entries can be complex data structures, e.g., combinations of scalars, vectors, and tensors. The use of the algorithm has been demonstrated for time series prediction, surpassing existing algorithms, and for visuo-motor control of an industrial robot, e.g., for precise end effector position control. We will attempt to demonstrate by the time of the lecture also an application of the algorithm for visuo-motor control of a pneumatically driven robot arm, a Bridgestone ‘RUBBERTUATOR’. This light-weight robot, capable of compliant motion, can be operated in contact with humans. The presented algorithm can acquire the complex response characteristics of this arm through training and, thereby, allows accurate and swift control of pneumatic robot motion.

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid (OSG) and the Worldwide LHC Computing Grid Collaboration (WLCG). FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the OSG, EGEE, and the WLCG. Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure - the successes and the problems.