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Globus and Service Oriented Architecture

Explore the dynamic world of service-oriented science and grid technologies for collaborative projects, spanning global organizations, with a focus on high-quality resources and concurrent innovation cycles. Learn about the Globus Toolkit v4 and its key capabilities in bridging the gap between applications and resources in distributed environments. Discover how GT4 empowers users to build secure web services, configure authorization structures, and deploy services on remote systems efficiently.

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Globus and Service Oriented Architecture

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  1. Globus and Service Oriented Architecture Ian Foster Computation Institute Argonne National Lab & University of Chicago

  2. My Visits to China • 2000: HPC Asia, Beijing • 2001: CHEP, Beijing • 2004: GCC, Wuhan (& Shanghai) • 2005: Grid projects, Beijing • 2005: CI6016, GCC, Beijing • 2006: GCC, Changsha • 2006: WI-AT, Hong Kong • 2007: GCC, Urumchi, Xinjiang • http://vega.ict.ac.cn/gcc2007

  3. Collaborations Include … • China Grid, China National Grid, CROWN Grid, Shanghai Grid, etc. all build on Globus • Many fruitful discussions (should be more!) • Globus contributions from China, e.g. • Dynamic service deployment (Li Qi et al.) • OGSA-DAI components • Visitors hosted at Argonne and Chicago • From one day to one year duration • Grid Service Markup Language (GSML) • Focus of Haiyan Yu (CAS) visit at present

  4. Globus.Org: November 2006 > ~100accesses

  5. Project focused, globally distributed teams, spanning organizations within and beyond company boundaries Collaborative and Dynamic Each team member/group brings own data, compute, & other resources into the project Distributed and Heterogeneous Access to computing and data resources must be coordinated across the collaboration Data & Computation Intensive Resources must be available to projects with strong QoS, & also reflect enterprise-wide biz priorities Concurrent Innovation Cycles Why Grid (and Globus)? —The Changing Nature of Work IT must adapt to this new reality

  6. Service-Oriented Science People create services (data or functions) … which I discover (& decide whether to trust) … & compose to create a new function ... and then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operatingservices & computers!  I hope that this “someone else” can manage security, reliability, scalability, … ! ! “Service-Oriented Science”, Science, 2005

  7. Tool Tool Workflow Uniform interfaces, security mechanisms, Web service transport, monitoring Registry Credent. DAIS GRAM User Svc User Svc GridFTP Host Env Host Env Approach: Bridging the Application-Resource Gap User App Specialized resources Storage Computers

  8. Globus Toolkit: Open Source Grid Infrastructure Globus Toolkit v4 www.globus.org Data Replication CredentialMgmt Replica Location Grid Telecontrol Protocol Delegation Data Access & Integration Community Scheduling Framework WebMDS Python Runtime Reliable File Transfer CommunityAuthorization Workspace Management Trigger C Runtime Authentication Authorization GridFTP Grid Resource Allocation & Management Index Java Runtime Security Data Mgmt Execution Mgmt Info Services CommonRuntime I. Foster, Globus Toolkit Version 4: Software for Service-Oriented Systems, JCST 21(4), 2006

  9. http://dev.globus.org Guidelines(Apache) Infrastructure(CVS, email,bugzilla, Wiki) Projects Include … dev.globus — Community Driven Improvement of Globus Software, NSF OCI

  10. What GT4 Lets You Do(An Incomplete List) • Build secure & stateful Web services • Web Services core, service authoring tools • Configure distributed authorization structures • Powerful standards-based security tools • Deploy services/run jobs on remote systems • GRAM, virtual workspace, dynamic services • Move data fast & reliably among many sites • GridFTP, RFT, RLS, DRS • Discover and monitor services & resources • MDS

  11. Creating Services:E.g.,Introduce Authoring Tool • Define service • Create skeleton • Discover types • Add operations • Configure security • Modify service  targets GT4 New GT4 servicescreated in five minutes … Introduce: Hastings, Saltz, et al., Ohio State University

  12. User Applications GT4 & Web Services Custom Services Custom WSRF Services GT4WSRF Web Services Registry & Admin GT4 Container(e.g., Apache Axis) WS-A, WSRF, WS-Notification WSDL, SOAP, WS-Security

  13. “server-pull” Shib/SAML Attr Svc authZ SAML/XACML (Permis, CAS) Attribute validation and normalization Attribute-based authZ processing Dynamic PDP-instance creation Delegation of rights resolution Decision-chains rooted at rsrc owner “client-push” authZ SAML (CAS) X509 AC (VOMS) SOAP header or proxycert GT4’s New AuthZ Framework

  14. Examples of Globus-BasedProduction Scientific Grids • APAC (Australia) • China Grid • China National Grid • CROWN Grid • DGrid (Germany) • EGEE • Open Science Grid • Taiwan Grid • TeraGrid • ThaiGrid • UK Natl Grid Service

  15. Example:Earth System Grid • Climate simulation data • Per-collection control • Different user classes • Server-side processing • Implementation (GT) • Portal-based User Registration (PURSE) • PKI, SAML assertions • GridFTP, GRAM, SRM • >4000 users • >100 TB downloaded www.earthsystemgrid.org — DOE OASCR

  16. Under the Covers

  17. Service-Oriented Science& Cancer Biology caBIG: sharing of infrastructure, applications, and data. Data Integration!

  18. Gene Database caArray Protein Database Grid Services Infrastructure (Metadata, Registry, Query, Invocation, Security, etc.) Image Microarray Tool 2 Tool 3 Cancer Bioinformatics Grid Grid-Enabled Client Analytical Service Tool 1 Tool 2 Research Center NCICB Grid Data Service Tool 3 Tool 4 Grid Portal Research Center All Globus-based

  19. caBIG’s Identifier & Data Service Data Model fully incorporates Identifiers >100 Million Object+IDs (re-)generated Integration through simple Java API Works with existingCQL/SQL/XPATH Query Tools WS-Naming Resolution WS-Transfer GET Global Naming&Resolution Through Handle System

  20. Data Service @ uchicago.edu <BPEL Workflow Doc> <Workflow Inputs> BPEL Engine link <Workflow Results> Composing Services:E.g., BPEL Workflow System link Analytic service @ duke.edu link link Analytic service @ osu.edu caBiG: https://cabig.nci.nih.gov/; BPEL work: Ravi Madduri et al.

  21. Opportunitiesfor Future Collaboration • Develop the technology & methodologies required for successful eScience applications • Train students skilled in eScience and international collaboration • Work together on the major scientific and engineering challenges of the 21st Century • Clean energy • Global change & environmental impacts • Health and biomedicine

  22. Thanks! • DOE Office of Science • NSF Office of Cyberinfrastructure • Colleagues at Argonne, U.Chicago, USC/ISI, and elsewhere • Participants in Globus, CEDPS, ESG, OSG, caBIG, TeraGrid, and other projects

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