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Service Oriented Architectures for R&E networks “Google Mashing everything”

Service Oriented Architectures for R&E networks “Google Mashing everything”

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Service Oriented Architectures for R&E networks “Google Mashing everything”

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  1. Service Oriented Architectures for R&E networks“Google Mashing everything” Bill St. Arnaud CANARIE Inc –

  2. Google mashing • Google as developed a web service for Google Maps that allows users to overlay any geographical data • A powerful example of SOA and web services • No more using maps as GIFs or JPEGs, or using proprietary mapping software • Users can also create a workflow of their geographical data overlaid onto Google Maps and offer that as a web service to others

  3. Today’s Network & OS The network is subservient to the computer The application is tightly bound to the OS Network Application Application User User OS OS The network is a mechanism for applications to communicate with each other Data Data

  4. SOA Network Application and data exist on the network and are uncoupled from any specific machine or location SOA SOA Network OS OS The computer is subservient to the network Application and Data SOA SOA SOA SOA OS OS OS OS Data Data Data Data

  5. SOA (Web 2) versus Web 1 • Web 1: • HTML is the composition language of Web 1 • Its power is the ability to incorporate links to other web pages and in turn be linked to by others • Frontpage (and others) allow HTML editing • Human grammar and sentences provides the semantic structure of a web page between the various elements including hyberlinks • Apache (and others) convert HTML script into working web page accessible via HTTP • Web 2: (SOA) • XML is the composition language • Its power is the ability to incorporate links to other web pages and in turn be linked by others • BPEL provides the “semantic” structure between various web services • Resulting BPEL script is also a web service which can be linked to by others • Apache/Axis (.Net, Wepshere) convert XML into working web services accessible via SOAP (mostly via HTTP)

  6. The big picture Integrative Science E-Science or E-Research Cyber-infrastructure SOA: (web services, workflow, security, etc) Networks Grids HPC Instruments Databases

  7. Science drivers for SOA for R&E networks • Big Science: • CERN, eVLBI, Ocean Observatories • Integrative Science: • Increasing interests by researchers into multi-disciplinary science as opposed to reductionism • Need to link sensors, instruments and databases from different fields to extract new knowledge • Examples: • York University is connecting smog sensors along freeways and correlating with large population health data to predict consequence of traffic congestion on public living near the freeway • Neptune undersea network to investigate algae blooms that precede major undersea earthquakes

  8. New Integrative Science Source: Office of Integrative Activities NSF

  9. Picture ofearthquakeand bridge Sensors More Diversity, New Devices, New Applications Personalized Medicine Picture ofdigital sky Wireless networks Knowledge from Data Instruments Source: Larry Smarr??

  10. SOA and networks

  11. GENI-Network Virtualization Source: Network Virtualization web site

  12. GENI + SOA = UCLP APN Instrument WS Parent Lightpath WS Substrate Router Substrate Switch GMPLS Daemon WS Child Lightpath WS (may run over IP Ethernet, MPLS, etc Virtual Router WS Wireless Sensor Network Timeslice WS

  13. GENI is a subset of UCLP • Parent or root lightpath = substrate link • Child lightpath (SONET, MPLS, IP tunnel) = virtual link • Router = substrate router • Virtual or blade router = virtual router • APN = virtual end to end system linking processes (time slices), instruments, storage, etc • No equivalency to switch or virtual switch in GENI • SOA Web service can represent time slice, instrument or other process • UCLP allows user to configure their own APNs using BPEL • Change topology, bandwidth etc • APNs can be made up of layer 1 to 3 virtual links connecting instruments, routers or switches

  14. Extending the network into the application APN extends into computer to specific processes zzzz:410:0:1 Instrument Web service or software process User A xxxx:410:0:1 xxxx:410:0:4 Virtual Router WS xxxx:410:0:2 Single Computer or WS instance of an orchestration Routing daemon Web service xxxx:410:0:3 xxxx:410:0:5 DWDM Network Web service or software process Interface Card or port yyyy:410:0:1 VPN Links User B

  15. Similar initiatives at Cal-IT(2) & UCSD • A real-time data grid system • Multi-disciplinary data being integrated • Multiple Sensor types being adapted • Real-time data virtualization enabled • Discovery & access through metadata supported • (Laboratory for the Ocean Observatory • Knowledge Integration Grid) • Integrate Instruments & Sensors • (Real Time Data Sources) • Into a LambdaGrid • Computing Environment • With Web Services Interfaces • New OptIPuter Application Driver: • Gigabit Fibers on the Ocean Floor • • Goal: Prototype Cyberinfrastructure for NSF ORION •

  16. SURFnet APN resources advertised to CANARIE Amsterdam YEG YUL New York YVR Geneva YOW Winnipeg YYZ ONS TRIUMF YCG Halifax OME MAN LAN HDX STAR LIGHT HDX Pwave HDX APN Resource List CreationView by CANARIE staff Lightpath Object Creation CANARIE ONS Network Resources 1 Toronto Edmonton Chicago is hidden 2 CANARIE OME Network Resources ONS Montreal ONS ONS Vancouver BCnet Toronto Ottawa Edmonton Chicgao 3 MAN LAN HDX 4 New York Chicago Seattle Toronto STAR LIGHT HDX 5 Ottawa Amsterdam Vancouver Edmonton Montreal To Fermi Victoria New York Geneva New APN Resource list composition To Brookhaven

  17. CANARIE provides APN resource list to TRIUMF 1G Interface WS URI: http://canarie_apns/ 5G Interface WS 10G Lightpath WS 1G Lightpath WS Toronto Ottawa Amsterdam Vancouver Edmonton Montreal To Fermi Victoria New York Geneva NOTE: This resource element is actually an aggregation of several elements on CANARIE network. The exposed WS may actually be a BPEL composition of the underlying WS elements To Brookhaven

  18. TRIUMF GUI harvests other APNs from UoVic, UoT, etc TRIUMF Tier 1 1G Interface WS UoToronto Physics Tier 2 5G Interface WS UBC Physics UA Physics UoT Physics 10G Lightpath WS External links or APNs UoVictoria Physics Tier 2 UdM Physics TRIUMF APN UoT APN Carleton Physics Toronto Amsterdam Vancouver Edmonton Montreal UoV APN Ottawa Victoria CA*net 4 New York Geneav Chicago FERMI Tier 1 Note: Typical View on TRIUMF UCLP GUI CERN Tier 0 Brookhaven Tier 1

  19. TRIUMF/HEPnet Lightpath Object Composition GUI UBC Campus CWDM Lightpath Object UoVic Campus 802.11 Lightpath Object TRIUMF APN Toronto Ottawa Amsterdam Vancouver Edmonton Montreal To Fermi Victoria New York Geneva UoVic TRIUMF To Brookhaven Vancouver Victoria Lightpath Object for 2 Gbp Tiier 2between TRIUMF and UoVic Composition Window

  20. UoVic Physics UCLPv2 GUI or workflow tool adds Router WS to lightpath object UoVic Physics router resource CLI interface exposed as a WS Resource Window UoVic TRIUMF Vancouver Victoria Lightpath Object for 2 Gbp Tiier 2between TRIUMF and UoVic Created by TRIUMF/Hepnet UoVic TRIUMF Vancouver

  21. DRAC/UCLP Demo Network Nortel DRAC The Power of Web services Canarie UCLP Montreal Ottawa App App Halifax Toronto

  22. SOA Applications

  23. CANARIE’s i-Infrastructure program • To adapt Service Oriented Architectures (SOA) to process control, instrumentation systems and sensor networks • Applications include manufacturing, oil and gas, power systems, water, building management systems, environmental control systems, etc • Built upon CANARIE’s initial work on User Controlled LightPaths (UCLP) • Start with large science research facilities such as Neptune, Canada Light Source and then expand into industrial applications •

  24. Internet Typical Large system today VPN USER Firewall Process Process Process DMAS Process Process SONET/DWDM Instrument Pod SONET/DWDM Layer 3 switch/router Layer 2 switch Sensor Sensor Instrument Instrument Sensor

  25. CA*net 4 Lightpath CA*net 4 Process WS** Process Service Oriented Architectures WS* VPN HPC WS* USER Process Process Data Management System WS** WS Process Process WS LAN Instrument Pod LAN Web service Interface *CANARIE UCLP **New web services WS* WS* WS Layer 2/3 switch Sensor Sensor Instrument Instrument Sensor

  26. Science user perspective WS* CANARIE UCLP WS AAA process WS HPC Process WS** WS** WS* New Web service WS* Lightpath WS** New development WS* ONS15454 NLR or CA*net 4 USER with WSFL binding software WS** Log Archive Process 2 DMAS WS** Log Archive Process 1 WS* LAN UDDI or WSIL service registry Science Pod WS* LAN Sensor/Instrument WS** User defined WSFL bindings

  27. VESPERS Beamline at the Canadian Light Source 1. E-gun & Linear Accelerator • microanalysis with unprecedented sensitivity 4. Beamline End Station 3. Storage Ring Courtesy of CLSI

  28. UCLP-Enabled Virtual Design Studio 3D digital construction of the Salk Institute Michael Jemtrud Konstantin Privalov James Hayes Nicolas Valenzuela Carleton Immersive Media Studio Carleton University , School of Architecture, Ottawa (Canada)

  29. SOA for Participatory Design Studio • Service provides are • network resources (UCLP) • devices (cameras, displays, rendering computers) • software (MAYA) • Provisioning for a PDS session requires • finding a configuration of network resources, devices and software that meets the user’s needs • SOA will monitor session • Does not transport high definition signal • Demo illustrates how end users can establish UCLP connections without knowing details

  30. Other SOA Network Projects • Design Service-Oriented Architecture (SOA) and build Web Services for linking research data to scholarly publications • Web services control of undersea HDTV camera – Neptue • SOA for military real time simulation

  31. Amateurs discover most Supernovas “Nasa and amateur scientists nightly harvest about 1,000 images, which are shared with other amateur astronomers over the Internet. Together, they analyze the pictures for previously undiscovered supernovas, the remains of collapsed stars. “ “Over 58 supernovas have been discovered” “While most amateur astronomers use computers to enhance a hobby, the advances in technology are also blurring the distinctions between professionals and sophisticated amateurs.”

  32. Sloan Digital SkyServer • • Large database of astronomical data and images • Available to scientists, students and public • XML and Java web services interfaces

  33. Conclusions • SOA & Cyber-Infrastructure will fundamentally transform science and IT • Better get prepared and learn as much as possible and learn about CI and SOA • Web services • Resource discovery and consumption • Publishing services • Workflow and orchestration • SOA platforms – OGSA, .NET,. Websphere • Commercialization potentials of integrative science and CI are significantly greater than with traditional science