eScience eBusiness eGovernment and their Technologies Introduction

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e-Science e-Business e-Government and their
TechnologiesIntroduction

• Bryan Carpenter, Geoffrey Fox, Marlon Pierce
• Pervasive Technology Laboratories
• Indiana University Bloomington IN 47401
• January 12 2004
• dbcarpen_at_indiana.edu
• gcf_at_indiana.edu
• mpierce_at_cs.indiana.edu
• http//www.grid2004.org/spring2004

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Course Topics Background/Core

• 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
• XML/Java Programming
• XML Databases (Xindice, Sleepycat)
• XPath, XQuery

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Course Topics 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

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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
• Advanced Java including networking, Java Server
  Pages and perhaps servlets
• XML Specification, Tools, Linkage to Java
• Web Services Basic Ideas, WSDL, Axis and Tomcat
• Grid Systems GT3/Cogkit, Gateway, XSOAP, Portlet
• Advanced Technology Surveys CORBA as history,
  OGSA-DAI, security, Semantic Grid, Workflow
• Applications Bioinformatics, Particle Physics,
  Engineering, Crises, Computing-on-demand Grid,
  Earth Science

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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

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Other

• See the webcast in an Oracle technology
  serieshttp//webevents.broadcast.com/techtarget/O
  racle/100303/index.asp?loc10
• See also the Gap Analysishttp//grids.ucs.india
  na.edu/ptliupages/publications/GapAnalysis30June03
  v2.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 ishttp//grids.ucs.in
  diana.edu/ptliupages/publications/Appendix30June03
  .pdf
• See also GlobusWorld http//www.globusworld.org/
• and the Grid Forum http//www.gridforum.org

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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

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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.

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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 100s 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.

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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
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Global Terabit Research Network

• The Grid software and resources run on top of
  high performance global networks

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USA Network
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Terabit Networks

• Network performance will increase faster than
  Moores 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
  is10001000100101 Gigabit/sec

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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

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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

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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_at_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
• Pipelined applications linking data/instruments,
  compute, visualization
• Seamless Access where Grid portals allow one to
  choose one of multiple resources with a common
  interfaces

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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 his application is common in academia where
  different simulations share resources
• 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

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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
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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

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Information/Knowledge Grids

• Distributed (10s to 1000s) of data sources
  (instruments, file systems, curated databases )
• Data Deluge 1 (now) to 100s petabytes/year
  (2012)
• Moores 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
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2.4 Petabytes Today
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SERVOGrid Solid Earth Research Virtual
Observatory will link Australia, Japan, USA
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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
• Portals with component model for user interfaces
  and web control of all capabilities
• Collaboration to support world-wide work
• Basic Grid tools workflow and notification

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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
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NASA Aerospace Engineering Grid
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Virtual Observatory Astronomy GridIntegrate
Experiments
Radio
Far-Infrared
Visible
Dust Map
Visible X-ray
Galaxy Density Map
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e-Chemistry LaboratoryExperiments-on-demand
Grid-enabled Output Streams
Grid Resources
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CERN LHC Data Analysis Grid
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Typical Grid Architecture
UserServices
CoreGrid
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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

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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
  TomcatAxis (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

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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

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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
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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 DOs do NOT scale WS build on experience
  (with CORBA) and do scale

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Details of Web Service Protocol Stack

• UDDI finds where programs are
• remote (distributed) programs are just Web
  Services
• (not a great success)
• WSFL links programs together(under revision as
  BPEL4WS)
• WSDL defines interface (methods, parameters, data
  formats)
• SOAP defines structure of message including
  serialization of information
• HTTP is negotiation/transport protocol
• TCP/IP is layers 3-4 of OSI
• Physical Network is layer 1 of OSI

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Classic Grid Architecture
Resources
Content Access
Composition
Middle TierBrokers Service Providers
Netsolve
Security
Collaboration
Computing
Middle Tier becomes Web Services
Clients
Users and Devices
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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
• Quizzes of 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

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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

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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

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Peer to Peer Grid
Peers
Service FacingWeb Service Interfaces
Peers
User FacingWeb Service Interfaces
Peer to Peer Grid
A democratic organization
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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
• Portals are the user (web browser) interfaces to
  Web services

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Satellite Science Grid Environment
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What is Happening?

• Grid ideas are being developed in (at least) two
  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

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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

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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

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Issues and Types of Grid Services

• 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

• 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

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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
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Approach
Application WS

• 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 dont need high performance here
• Allows use of Semantic Grid technology

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UserServices
GridComputingEnvironments
CoreGrid
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Why we can dream of using HTTP and that slow stuff

• We have at least three tiers in computing
  environment
• Client (user portal)
• Middle Tier (Web Servers/brokers)
• Back end (databases, files, computers etc.)
• In Grid programming, we use HTTP (and used to use
  CORBA and Java RMI) in middle tier ONLY to
  manipulate a proxy for real job
• Proxy holds metadata
• Control communication in middle tier only uses
  metadata
• Real (data transfer) high performance
  communication in back end

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Virtualization

• The Grid could and sometimes does virtualize
  various concepts should do more
• Location URI (Universal Resource Identifier)
  virtualizes URL (WSAddressing goes further)
• Replica management (caching) virtualizes file
  location generalized by GriPhyn virtual data
  concept
• Protocol message transport and WSDL bindings
  virtualize transport protocol as a QoS request
• P2P or Publish-subscribe messaging virtualizes
  matching of source and destination services
• Semantic Grid virtualizes Knowledge as a
  meta-data query
• Brokering virtualizes resource allocation
• Virtualization implies all references can be
  indirect and needs powerful mapping (look-up)
  services -- metadata

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Integration of Data and Filters

• One has the OGSA-DAI Data repository interface
  combined with WSDL of the (Perl, Fortran, Python
  ) filter
• User only sees WSDL not data syntax
• Some non-trivial issues as to where the filtering
  compute power is
• Microsoft says filter next to data

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SERVOGrid Complexity Computing Environment
Parallel SimulationService
DatabaseService
ComputeService
Sensor Service
Middle Tier with XML Interfaces
ApplicationService-1
XML Meta-dataService
ApplicationService-2
CCE Control Portal Aggregation
ComplexitySimulationService
ApplicationService-3
Users
VisualizationService
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OGSA-DAIGrid Services
AnalysisControl Visualize
Grid
Data
Filter
This Type of Grid integrates with Parallel
computing Multiple HPC facilities but only use
one at a time Many simultaneous data sources and
sinks
HPC Simulation
Grid Data Assimilation
Other Gridand Web Services
Distributed Filters massage data For simulation
SERVOGrid (Complexity) Computing Model
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Two-level Programming I

• The paradigm implicitly assumes a two-level
  Programming Model
• We make a Service (same as a distributed object
  or computer program running on a remote
  computer) using conventional technologies
• C Java or Fortran Monte Carlo module
• Data streaming from a sensor or Satellite
• Specialized (JDBC) database access
• Such services accept and produce data from users
  files and databases
• The Grid is built by coordinating such services
  assuming we have solved problem of programming
  the service

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Two-level Programming II

• The Grid is discussing the composition of
  distributed services with the runtime interfaces
  to Grid as opposed to UNIX pipes/data streams
• Familiar from use of UNIX Shell, PERL or Python
  scripts to produce real applications from core
  programs
• Such interpretative environments are the single
  processor analog of Grid Programming
• Some projects like GrADS from Rice University are
  looking at integration between service and
  composition levels but dominant effort looks at
  each level separately

58
Conclusions

• Grids are inevitable and pervasive
• Can expect Web Services and Grids to merge with a
  common set of general principles but different
  implementations with different scaling and
  functionality trade-offs
• e-Science will grow in importance as Science
  grows as an international team sport affects
  scientists and organizations
• Enough is known that one can start today
• We will be flooded with data, information and
  purported knowledge
• One should be learning about Grids understanding
  relevant Web and Grid standards and developing
  new domain specific standards
• Note many existing (standards) efforts assume
  client-server and not a brokered service model
  these will need to change!