e-Science e-Business e-Government and their Technologies Introduction

1. e-Science e-Business e-Government and their TechnologiesIntroduction Bryan Carpenter, Geoffrey Fox, Marlon Pierce Pervasive Technology Laboratories Indiana University Bloomington IN 47404 January 12 2004 dbcarpen@indiana.edu gcf@indiana.edu mpierce@cs.indiana.edu http://www.grid2004.org/spring2004

2. Class Structure • Grading based on mixture of homework and a single final project • Up to 2 students can collaborate together on final project • Homework 70% Final Project 30% grade • NO midterm or final • Homework will mainly be programming based but there may be reports either in final or one or two homework assignments • Reports will use Internet, book and “Gap Analysis”

3. What are we doing • This is a semester-long course on Grids (viewed as technologies and infrastructure) and the application – mainly to science but also to business and government • We will assume a basic knowledge of the Java language and then interweave 6 topic areas – first four cover technologies that will be used by students • 1) Advanced Java: including networking, Java Server Pages and perhaps servlets • 2) XML: Specification, Tools, Linkage to Java • 3) Web Services: Basic Ideas, WSDL, Axis and Tomcat • 4)Grid Systems: GT3/Cogkit, Gateway, XSOAP, Portlet • 5) Advanced Technology Discussions: CORBA as istory, OGSA-DAI, security, Semantic Grid, Workflow • 6) Applications: Bioinformatics, Particle Physics, Engineering, Crises, Computing-on-demand Grid, Earth Science

4. Course Topics 1 and 2 : Background/Core • Advanced Java Programming • We will assume basic Java programming proficiency • We will cover Java client/server, three-tiered and network programming. • Ancillary but interesting Java topics to be covered include Apache Ant, XML-Beans, and Java Message Service • XML and XML Schema • We will provide introductory material. • Necessary to understand Web Service standards • Examples include RDF (semantic web) and SOAP (Web services) • XML Tools • XML Databases (Xindice, Sleepycat) • Search: XPath, XQuery

5. Course Topics 3 and 4: Web and Grid Services • Overview Material • Grid and Web Service Architectures • Basic Web Service Standards • WSDL, SOAP: structure and definitions • Building services in Java: Apache Axis • Advanced Web Services: Emerging capabilities • WS-ReliableMessaging, WS-Security, WS-Transaction • Computational Grids • Globus Toolkit 2 • Java COG Kit for Globus programming • Grids Meet Web Services • Open Grid Service Architecture/Infrastructure • Implementations: GSX from Indiana University • The Semantic Grid: Information Models for Describing Resources • RDF, DAML-OIL, and OWL

6. Grid Computing: Making The Global Infrastructure a Reality • Based on work done in preparing book edited withFran Berman andAnthony J.G. Hey, • ISBN: 0-470-85319-0 • Hardcover 1080 Pages • Published March 2003 • http://www.grid2002.org

7. Other • See the webcast in an Oracle technology serieshttp://webevents.broadcast.com/techtarget/Oracle/100303/index.asp?loc=10 • See also the “Gap Analysis”http://grids.ucs.indiana.edu/ptliupages/publications/GapAnalysis30June03v2.pdf • We can send you nicely printed versions of this • End of this is a good collection of references and it gives both a general survey of current Grids and specific examples from UK • Appendix with more details is:http://grids.ucs.indiana.edu/ptliupages/publications/Appendix30June03.pdf • See also GlobusWorld http://www.globusworld.org/ • and the Grid Forum http://www.gridforum.org

8. e-moreorlessanything and the Grid • e-Business captures an emerging view of corporations as dynamic virtual organizations linking employees, customers and stakeholders across the world. • The growing use of outsourcing is one example • e-Science is the similar vision for scientific research with international participation in large accelerators, satellites or distributed gene analyses. • The Grid integrates the best of the Web, traditional enterprise software, high performance computing and Peer-to-peer systems to provide the information technology e-infrastructure for e-moreorlessanything. • A deluge of data of unprecedented and inevitable size must be managed and understood. • People, computers, data and instruments must be linked. • On demand assignment of experts, computers, networks and storage resources must be supported

9. So what is a Grid? • Supporting human decision making with a network of at least four large computers, perhaps six or eight small computers, and a great assortment of disc files and magnetic tape units - not to mention remote consoles and teletype stations - all churning away. (Licklider 1960) • Coordinated resource sharing and problem solving in dynamic multi-institutional virtual organizations • Infrastructure that will provide us with the ability to dynamically link together resources as an ensemble to support the execution of large-scale, resource-intensive, and distributed applications. • Realizing thirty year dream of science fiction writers that have spun yarns featuring worldwide networks of interconnected computers that behave as a single entity.

10. What is a High Performance Computer? • We might wish to consider three classes of multi-node computers • 1) Classic MPP with microsecond latency and scalable internode bandwidth (tcomm/tcalc ~ 10 or so) • 2) Classic Cluster which can vary from configurations like 1) to 3) but typically have millisecond latency and modest bandwidth • 3) Classic Grid or distributed systems of computers around the network • Latencies of inter-node communication – 100’s of milliseconds but can have good bandwidth • All have same peak CPU performance but synchronization costs increase as one goes from 1) to 3) • Cost of system (dollars per gigaflop) decreases by factors of 2 at each step from 1) to 2) to 3) • One should NOT use classic MPP if class 2) or 3) suffices unless some security or data issues dominates over cost-performance • One should not use a Grid as a true parallel computer – it can link parallel computers together for convenient access etc.

11. e-Science • e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it. This is a major UK Program • e-Science reflects growing importance of international laboratories, satellites and sensors and their integrated analysis by distributed teams • CyberInfrastructure is the analogous US initiative Grid Technology supports e-Science and CyberInfrastructure It is software (middeleware) built on top of networks

12. Global Terabit Research Network • The Grid software and resources run on top of high performance global networks

13. USA Network

14. Terabit Networks • Network performance will increase faster than Moore’s law – partly because optical fiber has almost unlimited bandwidth and partly because there are many old networks to be replaced • Home dial-ups (56kbit)  DSL/Cable Modem (2 megabits/sec)  FTTP (Fiber to the Premise at gigabit performance) • 2006 Goal of Global Terabit Research NetworkInternational: National Backbone: Organization;: Optical Desktop: Copper Desktop is1000:1000:100:10:1 Gigabit/sec

15. e-Business and (Virtual) Organizations • Enterprise Grid supports information system for an organization; includes “university computer center”, “(digital) library”, sales, marketing, manufacturing … • Outsourcing Grid links different parts of an enterprise together (Gridsourcing) • Manufacturing plants with designers • Animators with electronic game or film designers and producers • Coaches with aspiring players (e-NCAA or e-NFL etc.) • Customer Grid links businesses and their customers as in many web sites such as amazon.com • e-Multimedia can use secure peer-to-peer Grids to link creators, distributors and consumers of digital music, games and films respecting rights • Distance education Grid links teacher at one place, students all over the place, mentors and graders; shared curriculum, homework, live classes …

16. e-Defense and e-Crisis • Grids support Command and Control and provide Global Situational Awareness • Link commanders and frontline troops to themselves and to archival and real-time data; link to what-if simulations • Dynamic heterogeneous wired and wireless networks • Security and fault tolerance essential • System of Systems; Grid of Grids • The command and information infrastructure of each ship is a Grid; each fleet is linked together by a Grid; the President is informed by and informs the national defense Grid • Grids must be heterogeneous and federated • Crisis Management and Response enabled by a Grid linking sensors, disaster managers, and first responders with decision support

17. Classes of Computing Grid Applications • Running “Pleasing Parallel Jobs” as in United Devices, Entropia (Desktop Grid) “cycle stealing systems” • Can be managed (“inside” the enterprise as in Condor) or more informal (as in SETI@Home) • Computing-on-demand in Industry where jobs spawned are perhaps very large (SAP, Oracle …) • Support distributed file systems as in Legion (Avaki), Globus with (web-enhanced) UNIX programming paradigm • Particle Physics will run some 30,000 simultaneous jobs this way • Pipelinedapplications linking data/instruments, compute, visualization • Seamless Access where Grid portals allow one to choose oneof multiple resources with a common interfaces

18. Utility Computing • An important business application of Grids is utility computing • Namely support a pool of computers to be assigned as needed to take-up extra demand • Pool shared between multiple applications • One can say this application is common in academia where different simulations share resources while in industry we have • Web Servers • Financial Modeling • Data-mining • Simulation response to crisis like forest fire or earthquake • Architecture is “Farm of Grid Services” connected to Internet not cluster of computers connected to each other

19. Program AComputer 1 Program ZComputer 26 Program AComputer 27 Program ZComputer 52 Spares PoolComputer 1 Program A PoolComputer N <52 Program Z Resources-on-demand • Computing-on-demand uses dynamically assigned (shared) pool of resources to support excess demand in flexible cost-effective fashion Static Assignment with redundancy Dynamic on-demand Assignment

20. Some Important Styles of Grids • Computational Grids were origin of concepts and link computers across the globe – high latency stops this from being used as parallel machine • Knowledge and Information Grids link sensors and information repositories as in Virtual Observatories or BioInformatics • More detail on next slide • Education Grids link teachers, learners, parents as a VO with learning tools, distant lectures etc. • e-Science Grids link multidisciplinary researchers across laboratories and universities • Community Grids focus on Grids involving large numbers of peers rather than focusing on linking major resources – links Grid and Peer-to-peer network concepts • Semantic Grid links Grid, and AI community with Semantic web (ontology/meta-data enriched resources) and Agent concepts

21. Information/Knowledge Grids • Distributed (10’s to 1000’s) of data sources (instruments, file systems, curated databases …) • Data Deluge: 1 (now) to 100’s petabytes/year (2012) • Moore’s law for Sensors • Possible filters assigned dynamically (on-demand) • Run image processing algorithm on telescope image • Run Gene sequencing algorithm on compiled data • Needs decision support front end with “what-if” simulations • Metadata (provenance) critical to annotate data • Integrate across experiments as in multi-wavelength astronomy Data Deluge comes from pixels/year available

22. 2.4 Petabytes Today

23. RepositoriesFederated Databases Sensor Nets Streaming Data Database Database SERVOGrid for e-Geoscience ? Analysis and Visualization Discovery Services Closely Coupled Compute Nodes Loosely Coupled Filters SERVOGrid – Solid Earth Research Virtual Observatory will link Australia, Japan, USA ……

24. SERVOGrid Requirements • Seamless Access to Data repositories and large scale computers • Integration of multiple data sources including sensors, databases, file systems with analysis system • Including filtered OGSA-DAI (Grid database access) • Rich meta-data generation and access with SERVOGrid specific Schema extending openGIS (Geography as a Web service) standards and using Semantic Grid • Portalswith component model for user interfaces and web control of all capabilities • Collaboration to support world-wide work • Basic Grid tools: workflow and notification

25. DAME In flight data ~5000 engines ~ Gigabyte per aircraft per Engine per transatlantic flight Global Network Such as SITA Ground Station Airline Engine Health (Data) Center Maintenance Centre Internet, e-mail, pager Rolls Royce and UK e-Science ProgramDistributed Aircraft Maintenance Environment

26. It takes a distributed virtual organization to design, simulate and build a complex system like an aircraft NASA Aerospace Engineering Grid

27. Virtual Observatory Astronomy GridIntegrate Experiments Radio Far-Infrared Visible Dust Map Visible + X-ray Galaxy Density Map

28. e-Chemistry LaboratoryExperiments-on-demand Grid-enabled Output Streams Grid Resources

29. CERN LHC Data Analysis Grid

30. Portal Services SystemServices SystemServices Application Service Middleware SystemServices SystemServices SystemServices Raw (HPC) Resources Database Typical Grid Architecture Each Blob is a Computer Program! UserServices “Core”Grid

31. Sources of Grid Technology • Grids support distributed collaboratories or virtual organizations integrating concepts from • The Web • Agents • Distributed Objects(CORBA Java/Jini COM) • Globus, Legion, Condor, NetSolve, Ninf and other High Performance Computing activities • Peer-to-peer Networks • With perhaps the Web and P2P networks being the most important for “Information Grids” and Globus for “Compute Grids”

32. The Essence of Grid Technology? • We will start from the Web view and assert that basic paradigm is • Meta-data rich Web Services communicating via messages • These have some basic support from some runtime such as .NET, Jini (pure Java), Apache Tomcat+Axis (Web Service toolkit), Enterprise JavaBeans, WebSphere (IBM) or GT3 (Globus Toolkit 3) • These are the distributed equivalent of operating system functions as in UNIX Shell • Called Hosting Environment or platform • W3C standard WSDL defines IDL (Interface standard) for Web Services

33. Meta-data • Meta-data is usually thought of as “data about data” • The Semantic Web is at its simplest considered as adding meta-data to web pages • For example, the hospital web-page has meta-data telling you its location, phone-number, specialties which can be used to automate Google-style searches to allow planning of disease/accident treatment from web • Modern trend (Semantic Grid) is meta-data about web-services e.g. specify details of interface and useage • Such as that a bioinformatics service is free or bandwidth input is of limited amount • Provenance – history and ownership – of data very important

34. PortalService Security Catalog A typical Web Service • In principle, services can be in any language (Fortran .. Java .. Perl .. Python) and the interfaces can be method calls, Java RMI Messages, CGI Web invocations, totally compiled away (inlining) • The simplest implementations involve XML messages (SOAP) and programs written in net friendly languages like Java and Python PaymentCredit Card Web Services WSDL interfaces Warehouse Shipping control WSDL interfaces Web Services

35. Services and Distributed Objects • A web service is a computer program running on either the local or remote machine with a set of well defined interfaces (ports) specified in XML (WSDL) • Web Services (WS) have many similarities with Distributed Object (DO) technology but there are some (important) technical and religious points (not easy to distinguish) • CORBA Java COM are typical DO technologies • Agents are typically SOA (Service Oriented Architecture) • Both involve distributed entities but Web Services are more loosely coupled • WS interact with messages; DO with RPC (Remote Procedure Call) • DO have “factories”; WS manage instances internally and interaction-specific state not exposed and hence need not be managed • DO have explicit state (statefull services); WS use context in the messages to link interactions (statefull interactions) • Claim: DO’s do NOT scale; WS build on experience (with CORBA) and do scale

36. UDDI or WSIL WSFL WSDL SOAP or RMI HTTP or SMTP or IIOP or RMTP TCP/IP Physical Network Details of Web Service Protocol Stack • UDDIfinds where programs are • remote (distributed) programs are just Web Services • (not clearly a great success) • WSFL links programs together(under revision as BPEL) • WSDL defines interface (methods, parameters, data formats) • SOAPdefines structure of message including serialization of information • HTTP is negotiation/transport protocol • TCP/IPis layers 3-4 of OSI • Physical Network is layer 1 of OSI

37. Database Database Classic Grid Architecture Resources Content Access Composition Middle TierBrokers Service Providers Netsolve Security Collaboration Computing Middle Tier becomes Web Services Clients Users and Devices

38. Grid Services for the Education Process • “Learning Object” XML standards already exist • Registration • Performance (grading) • Authoring of Curriculum • Online laboratories for real and virtual instruments • Homework submission • Quizzesof various types (multiple choice, random parameters) • Assessment data access and analysis • Synchronous Delivery of Curricula including Audio/Video Conferencing and other synchronous collaborative tools as Web Services • Scheduling of courses and mentoring sessions • Asynchronous access, data-mining and knowledge discovery • Learning Plan agents to guide students and teachers

39. Grid Learning Model • Education and Research Grids share some services both for content and “process” • For example collaboration services are largely identical • Research will use much larger simulation engines to get high resolution results • Maybe a researcher uses a CAVE to visualize; education a Macintosh • But both can share data services but run through different filters to select for precision (research) or pedagogical value (education) • Education has “digital textbook” frontend to resources of the research Grid • Both use same workflow technologies to link services together

40. Streaming Data Field Trip Data Sensors RepositoriesFederated Databases Database Database SERVOGrid for e-Education ? Analysis and Visualization Discovery Services Loosely Coupled Filters Coarse grain simulations

41. Some Observations • “Traditional “ Grids manage and share asynchronous resources in a rather centralized fashion • Peer-to-peer networks are “just like” Grids with different implementations of message-based services like registration and look-up • Collaboration systems like WebEx/Placeware (Application sharing) or Polycom (audio/video conferencing) can be viewed as Grids • Computers are fast and getting faster. One can afford many strategies that used to be unrealistic including rich usually XML based messaging • Web Services interact with messages • Everything (including applications like PowerPoint) will be a Web Service? • Grids, P2P Networks, Collaborative Environments are (will be) managed message-linked Web Services

42. Database Database Event/MessageBrokers Event/MessageBrokers Event/MessageBrokers Peer to Peer Grid Peers Service FacingWeb Service Interfaces Peers User FacingWeb Service Interfaces A democratic organization Peer to Peer Grid

43. System and Application Services? • There are generic Grid system services: security, collaboration, persistent storage, universal access • OGSA (Open Grid Service Architecture) is implementing these as extended Web Services • An Application Web Service is a capability used either by another service or by a user • It has input and output ports – data is from sensors or other services • Consider Satellite-based Sensor Operations as a Web Service • Satellite management (with a web front end) • Each tracking station is a service • Image Processing is a pipeline of filters – which can be grouped into different services • Data storage is an important system service • Big services built hierarchically from “basic” services • Portalsare the user (web browser) interfaces to Web services

44. Satellite Science Grid Environment

45. What is Happening? • Grid ideas are being developed in (at least) three communities • Web Service – W3C, OASIS • Grid Forum (High Performance Computing, e-Science) • Service Standards are being debated • Grid Operational Infrastructure is being deployed • Grid Architecture and core software being developed • Particular System Services are being developed “centrally” – OGSA framework for this in • Lots of fields are setting domain specific standards and building domain specific services • There is a lot of hype • Grids are viewed differently in different areas • Largely “computing-on-demand” in industry (IBM, Oracle, HP, Sun) • Largely distributed collaboratories in academia

46. Not OGSA specific services Domain - More specialized services: data Possibly OGSA replication, workflow, etc., etc. Broadly applicable services: registry, OGSA Environment authorization, monitoring, data access, etc., etc. OGSI on Web Services Hosting Environment for WS Given to us from on high Network OGSA OGSI & Hosting Environments • Start with Web Services in a hosting environment • Add OGSI to get a Grid service and a component model • Add OGSA to get Interoperable Grid “correcting” differences in base platform and adding key functionalities

47. Technical Activities of Note • Look at different styles of Grids such as Autonomic(Robust Reliable Resilient) • New Grid architectures hard due to investment required • Critical Services Such as • Security – build message based not connection based • Notification – event services • Metadata – Use Semantic Web, provenance • Databases and repositories – instruments, sensors • Computing – Submit job, scheduling, distributed file systems • Visualization, Computational Steering • Fabric and Service Management • Network performance • Program the Grid – Workflow • Access the Grid – Portals, Grid Computing Environments

48. 1) Types of Grid R3 Lightweight P2P Federation and Interoperability 2) Core Infrastructure and Hosting Environment Service Management Component Model Service wrapper/Invocation Messaging 3) Security Services Certificate Authority Authentication Authorization Policy 4) Workflow Services and Programming Model Enactment Engines (Runtime) Languages and Programming Compiler Composition/Development 5) Notification Services 6) Metadata and Information Services Basic including Registry Semantically rich Services and meta-data Information Aggregation (events) Provenance 7) Information Grid Services OGSA-DAI/DAIT Integration with compute resources P2P and database models 8) Compute/File Grid Services Job Submission Job Planning Scheduling Management Access to Remote Files, Storage and Computers Replica (cache) Management Virtual Data Parallel Computing 9) Other services including Grid Shell Accounting Fabric Management Visualization Data-mining and Computational Steering Collaboration 10) Portals and Problem Solving Environments 11) Network Services Performance Reservation Operations Issues and Types of Grid Services

49. Remote Grid Service Remote Grid Service 1: Plan Execution 4: Job Submittal Data Data 10: Job Status 1: Job Management Service (Grid Service Interface to user or program client) 2: Schedule and control Execution 8: VirtualData 3: Access to Remote Computers 6: File and Storage Access 7: CacheDataReplicas 5: Data Transfer Technology Components of (Services in)a Computing Grid 9: Grid MPI

50. Application WS WS linking to user and Other WS (data sources) Typicalcodes Approach • Build on e-Science methodology and Grid technology • Science applications with multi-scale models, scalable parallelism, data assimilation as key issues • Data-driven models for earthquakes, climate, environment ….. • Use existing code/database technology (SQL/Fortran/C++) linked to “Application Web/OGSA services” • XML specification of models, computational steering, scale supported at “Web Service” level as don’t need “high performance” here • Allows use of Semantic Grid technology