1. Service Oriented Architectures for R&E networks “Google Mashing everything” Bill St. Arnaud CANARIE Inc – www.canarie.ca Bill.st.arnaud@canarie.ca

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 Application OS Data Application OS Data Network User The application is tightly bound to the OS The network is a mechanism for applications to communicate with each other The network is subservient to the computer

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

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) Grids Networks HPC Databases Instruments

7. Science drivers for SOA for R&E networks 1.Big Science: – CERN, eVLBI, Ocean Observatories 2.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. Instruments Picture of digital sky Knowledge from Data Sensors Picture of earthquake and bridge Wireless networks Personalized Medicine More Diversity, New Devices, New Applications Source: Larry Smarr??

10. SOA and networks

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

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

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

15. Similar initiatives at Cal-IT(2) & UCSD >(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 >www.neptune.washington.edu 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

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

17. CANARIE provides APN resource list to TRIUMF 10G Lightpath WS 1G Interface WS 5G Interface WS 1G Lightpath WS URI: http://canarie_apns/triumf_apn.ws Amsterdam New York Toronto Vancouver Victoria Edmonton Ottawa Geneva Montreal To Fermi To Brookhaven 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

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

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

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

21. DRAC/UCLP Demo Network Norte l DRA C Canarie UCLP Halifax App Ottawa Toronto Montreal The Power of Web services

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 >www.canarie.ca/ccipwww.canarie.ca/ccip

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

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

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

27. 1. E-gun & Linear Accelerator 3. Storage Ring 4. Beamline End Station VESPERS Beamline at the Canadian Light Source  microanalysis with unprecedented sensitivity 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. – 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 SOA for Participatory Design Studio

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 http://www.nytimes.com/2002/11/07/technology/circui ts/07astr.html?todaysheadlines “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 >http://skyserver.sdss.org/en/http://skyserver.sdss.org/en/ >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