1.
Grid Technology Implications for ACES and SERVOGrid Brisbane Australia June
Geoffrey Fox
Marlon Pierce
Community Grids Lab
Indiana University

2. What is Grid Technology?
Grids support distributed collaboratories or virtual organizations integrating concepts from
The Web
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 being the most important for “Information Grids” and Globus for “Compute Grids”
Information Grids are basis of SERVOGrid
Organization includes People, Computers, Observational Data and results of thought and data processing

3. Paradigms Protocols Platforms and Hosting
We can start from the Web view where the basic Grid 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

4. Taxonomy of Grid Functionalities
Name of Grid Type
Description of Grid Functionality
Compute/File Grid
Run multiple jobs with distributed compute and data resources (Global “UNIX Shell”)
Desktop Grid
“Internet Computing” and “Cycle Scavenging” with secure sandbox on large numbers of untrusted computers
Information Grid
Grid service access to distributed information, data and knowledge repositories
Complexity or Hybrid Grid
Hybrid combination of Information and Compute/File Grid emphasizing integration of experimental data, filters and simulations
Campus Grid
Grid supporting University community computing
Enterprise Grid
Grid supporting a company’s enterprise infrastructure
Note: Term Data Grid not used consistently in community so avoided

5. SERVOGrid Caricature Database Repositories Federated Databases
Closely Coupled Compute Nodes
Analysis and Visualization
Repositories Federated Databases
Sensor Nets
Streaming Data
Loosely Coupled Filters

6. SERVOGrid (Complexity)Computing Model
Data
Filter
Data
Filter
OGSA-DAI Grid Services
Analysis Control
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
Grid Data
Assimilation
HPC
Simulation
Filter
Data
Other Grid and Web Services
Distributed Filters
massage data
For simulation
Data
Filter
SERVOGrid (Complexity)Computing Model

7. Taxonomy of Grid Operational Style
Name of Grid Style
Description of Grid Operational or Architectural Style
Semantic Grid
Integration of Grid and Semantic Web meta-data and ontology technologies
Peer-to-peer Grid
Grid built with peer-to-peer mechanisms
Lightweight Grid
Grid designed for rapid deployment and minimum life-cycle support costs
Collaboration Grid
Grid supporting collaborative tools like the Access Grid, whiteboard and shared applications.
R3 or Autonomic Grid
Fault tolerant and self-healing Grid
Robust Reliable Resilient R3

8. SERVOGrid Grid 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
Rich meta-data generation and access with SERVOGrid specific Schema extending industry standards
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

9. What is a Web Service I
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)
In principle, computer program can be in any language (Fortran .. Java .. Perl .. Python) and the interfaces can be implemented in any way what so ever
Interfaces can be method calls, Java RMI Messages, CGI Web invocations, totally compiled away (inlining) but
The simplest implementations involve XML messages (SOAP) and programs written in net friendly languages like Java and Python
Web Services separate the meaning of a port (message) interface from its implementation
Enhances/Enables Re-usable component model of ANY electronic resource

10. Raw Resources Clients Raw Data Raw Data Render to XML Display Format
(Virtual) XML Data Interface
Web Service (WS) WS WS WS
etc.
XML WS to WS Interfaces WS
(Virtual) XML Knowledge (User) Interface
Render to XML Display Format
(Virtual) XML Rendering Interface
Clients

11. What are System and Application Services?
There are generic Grid system services: security, collaboration, workflow, notification
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

12. Application Web Services`
Filter1 WS
Filter2 WS
Filter3 WS
Workflow builds as multiple Filter Web Services
Prog1 WS
Prog2 WS
or as multiple interdisciplinary Programs
Data Analysis WS
Simulation WS
Visualization WS
Note Service model integrates sensors, sensor analysis, simulations and people
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 users, sensors or other services
Big services built hierarchically using workflow from “basic” services
Sensor Data as a Web service (WS)
Data Analysis WS
Sensor Management WS
Visualization WS
Simulation WS

13. Grid Politics
There is a Global Grid Forum meeting 3 times per year with about 700 attendees per meeting
Exchange information and define standards for “everything” not done in W3C and OASIS
e.g. Grid Service, Security, What is a Job, Database, Computer, How to build portals ….
There is a large project called Globus developing software largely for “compute/file” Grids
There are some 50 Grid projects (mainly in Europe and USA) developing software and applications as well as installing infrastructure
Some are “deployment”: EDG NMI VDT …..
There are related initiatives called CyberInfrastructure (NSF USA) and e-Science (UK)
There is a proposed OMII (Open Middleware Infrastructure Institute) – an international Alliance of separately funded projects with common coordination

14. OGSA/OGSI Top Level View
Web Services and OGSI
Broadly applicable services: registry,
authorization, monitoring, data
access, etc., etc.
Hosting Environment
Models for resources
& other entities
More specialized services: data
replication, workflow, etc., etc.
Domain -
specific services
Other
models
Network
OGSA is the set of “core” Grid services
Stuff you can’t live without
If you built a Grid you would need to invent these things

15. OGSI Open Grid Service Interface
It is a “component model” for web services.
It defines a set of behavior patterns that each OGSI service must exhibit.
Every “Grid Service” portType extends a common base type.
Defines an introspection model for the service
You can query it (in a standard way) to discover
What methods/messages a port understands
What other port types does the service provide?
If the service is “stateful” what is the current state?
A set of standard portTypes for
Message subscription and notification
Service collections
Each service is identified by a URI called the “Grid Service Handle”
GSHs are bound dynamically to Grid Services References (typically wsdl docs)
A GSR may be transient. GSHs are fixed.
Handle map services translate GSHs into GSRs.

16. 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 nuggets accept and produce data from users files and databases
The Grid is built by coordinating such nuggets assuming we have solved problem of programming the nugget
Nugget
Data

17. Two-level Programming II
The Grid is discussing the linkage and distribution of the nuggets with the only addition runtime interfaces to Grid as opposed to UNIX 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 and this tends to be called workflow
Workflow is the composition of multiple services (programs) together to make a new service
Includes “Software Bus”, “Application Integration”, “Co-ordination Languages” etc.
Nugget1
Nugget2
Nugget3
Nugget4

18. Workflow Workflow has at least 4 parts
“Programming Environment” – typically GUI to drag and drop services and their linkages (familiar from AVS etc. which was workflow for visualization)
Language – from XML to extended Python
Compiler – converting Language into executable
Runtime controlling flow of information and notification events
Can use Python, Mathematica, Matlab, JavaSpaces, IBM BPEL4WS, DoE CCA etc.
Don’t think current systems are very near “what we will want” but expect much progress over next 3 years and plenty of systems to work with
Metadata critical to tell you how to combine services in a sensible way – so workflow engines must interface with metadata service

19. e-Science and the Data Deluge Particle Physics
2006/7: First pp collisions at TeV energies at the Large Hadron Collider at CERN in Geneva
ATLAS/CMS Experiments involve physicists from 200 organizations in US, EU, Asia
Need to store,access, process, analyse 10 Petabytes/yr with 200 Teraflop/s distributed computation
Building hierarchical Grid infrastructure to distribute data and computation
Many 10’s of million $ funding for global particle physics Grid – GryPhyN, PPDataGrid, iVDGL, EU DataGrid, EU DataTag, UK GridPP projects
Need Exabytes and Petaflop/s by 2015

20. Astronomy and its Data Deluge
Virtual Observatories – NVO, AVO, AstroGrid
Store all wavelengths, need distributed joins
NVO 500 TB/yr from 2004
Laser Interferometer Gravitational Observatory
Search for direct evidence for gravitational waves
LIGO 250 TB/yr, random streaming from 2002
VISTA Visible and IR Survey Telescope in 2004
250 GB/night, 100 TB/yr, Petabytes in 10 yrs
New phase of astronomy, storing, searching and analysing Petabytes of data
The total area of astronomical telescopes in m2, and CCDs measured in Gigapixels, over the last 25 years. The number of pixels and the data double every year.

21. Engineering, Chemistry, Environmental BioInformatics and Medical Applications
Real-Time Industrial Health Monitoring
UK DAME project for Rolls Royce Aero Engines
1 GB sensor data/flight, 100,000 engine hours/day
Combinatorial Chemistry – experiments on demand
Earth Observation
ESA satellites generate 100 GB/day
NASA 15 PB by 2007
Bioinformatics
Tens of TB of high value curated data
Medical Images to Information
100 MB/mammogram, UK 3M/yr, US 26M/yr

22. Importance of Metadata
Metadata is ‘data about data’
e.g. cataloges, indices, directory structures
Librarians work with books which have same basic ‘schema’
e.g. title, author(s), publisher, date, etc
Need for hierarchical, community-based approach to defining metadata and schemas
e.g. CML, SERVOGridML ……..
Metadata important for interoperability of databases/federated archives, and for construction of intelligent search agents
Grid and Semantic Web communities should provide core infrastructure for generating, storing and access to meta-data

23. Simulation Output as Digital Library
Digital Libraries usually for archiving of text, audio and video data
Scientific data require transformation, data-mining and visualisation tools
For distributed collaborations need simulation output to be available as new kind of digital library, complete with catalogues and finding aids as well as data itself

24. Emergence of a new research methodology?
Traditional scientific methodologies are theory and experiment
Last half of 20th century saw emergence of scientific simulation as a third methodology
This century will see emergence of a fourth methodology - collection-based research
scientists will reduce, mine and sift data ‘published’ in ways not possible with paper journals with their tables and graphs

25. OGSA-DAI (Malcolm Atkinson Edinburgh) UK e-Science Grid Core Programme
Development of Data Access and Integration Services for OGSA
- Access to XML Databases -
- Access to Relational Databases -
- Distributed Query Processing -
- XML Schema Support for e-Science -
Project details

26. DAI Key Services Integrated Structured Data Transport
GridDataService GDS Access to data & DB operations
GridDataServiceFactory GDSF Makes GDS & GDSF
GridDataServiceRegistry GDSR Discovery of GDS(F) & Data
GridDataTranslationService GDTS Translates or Transforms Data
GridDataTransportDepot GDTD Data transport with persistence
Integrated Structured Data Transport
Relational & XML models supported
Role-based Authorisation
Binary structured files (later)

27. Interface transparency: one GDS supports multiple database types
Relational database
Client
XML database
Grid Data Service
Client
Client
Directory / File system

28. 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 DB
Filter
WSDL
Of Filter
OGSA-DAI
Interface

29. 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
OGSI on Web Services
Broadly applicable services: registry,
authorization, monitoring, data
access, etc., etc.
Hosting Environment for WS
Models for resources
& other entities
More specialized services: data
replication, workflow, etc., etc.
Domain -
specific services
Other
models
Network
OGSA
Environment
Possibly OGSA
Not OGSA
Given to us from on high

30. Permeating Principles and Policies
Meta-data rich Message-linked Web Services as the permeating paradigm
“User” Component Model such as “Enterprise JavaBean (EJB)” or .NET.
Service Management framework including a possible Factory mechanism
High level Invocation Framework describing how you interact with system components.
This could for example be used to allow the system to built from either W3C or GGF style (OGSI) Web Services and to protect the user from changes in their specifications.
Security is a service but the need for fine grain selective authorization encourages
Policy context that sets the rules for each particular Grid.
Currently OGSA supports policies for routing, security and resource use.
The Grid Fabric or set of resources needs mechanisms to manage them. This includes automatic recording of meta-data and configuration of software.
Quality of service (QoS) for the Network and this implies performance monitoring and bandwidth reservation services.
Challenging as end-to-end and not just backbone QoS is needed.
Messaging systems like MQSeries from IBM provide robustness from asynchronous delivery and can abstract destination and allow customization of content such as converting between different interface specifications.
Messaging is built on transport mechanisms which can be used to support mechanisms to implement QoS and to virtualize ports

31. Virtualization
The Grid could and sometimes does virtualize various concepts
Location: URI (Universal Resource Identifier) virtualizes URL
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 references can be indirect

32. Interfaces and Functionality and Semantics I
The Grid platform tries to minimize detail in protocols and maximize detail in interfaces to enhance scaling
However rich meta-data and semantics are critical for correct and interesting operation
Put as much semantic interpretation as you can into specific services
Lack of Semantic interoperation is in fact main weakness of today’s Grids and Web services
Everything becomes a service whether system or application level
There are some very important “Global Services”
Discovery (look up) and Registration of service metadata
Workflow
MetaSchedulers

33. Interfaces and Functionality and Semantics II
There are many other generally important services
OGSA-DAI The Database Service
Portal Service linked to by WSRP (Web services for Remote Portals)
Notification of events
Job submission
Provenance – interpret meta-data about history of data
File Interfaces
Sensor service – satellites …
Visualization
Basic brokering/scheduling

34. Web Services as a Portlet
Each Web Service naturally has a user interface specified as “just another port”
Customizable for universal access
This gives each Web Service a Portlet view specified (in XML as always) by WSRP (Web services for Remote Portals)
So component model for resources “automatically” gives a component model for user interfaces
When you build your application, you define portlet at same time
Application as a WS General Application Ports Interface with other Web Services
Application or Content source
WSDL
Web Service W P S R
User Face of Web Service WSRP Ports define WS as a Portlet
Web Services have other ports (Grid Service) to be OGSI compliant

35. Online Knowledge Center built from Portlets
A set of UI Components
Web Services provide a component model for the middleware (see large “common component architecture” effort in Dept. of Energy)
Should match each WSDL component with a corresponding user interface component
Thus one “must use” a component model for the portal with again an XML specification (portalML) of portal component

36. proxy credential manager, submission, monitoring
Sample page with
several portlets:
proxy credential manager,
submission, monitoring

37. Administer Grid Portal
Provide information
about application
and
host parameters
Select application
to edit

38. Categories of Worldwide Grid Services to be exploited by SERVOGrid
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

39. What should SERVOGrid do ?
Make use of Grid technologies and architecture from around the world
Coordinate with broad community through Global Grid Forum and OMII
Decide on domain specific standards SERVOGridML
Agree on particular approach within choices in international suite (use GT3 or not?, use portlets or not?, choose meta-data technology) and define SERVOGrid community practice
Develop software system infrastructure and applications specific to solid earth science
Worry about network interconnection between earthquake scientists and sensors

40. Proposed OMII Activities: Central Gaps: Gaps in Grid Styles and Execution Environment
Need for both robust (fault tolerant) and lightweight (suitable for small groups) Grid styles identified
Peer-to-peer style supports smaller decentralized virtual organizations
Note opportunities for modern middleware ideas to be used – lightweight, message-based
Note that Enterprise JavaBeans not optimized for Science which has high volume dataflow
Federated Grid Architecture natural for integration of heterogeneous functionality, style and security
Bioinformatics and other fields require integration of Information and Compute/File Grids

41. Overlapping Heterogeneous
Dynamic light-weight Peer-to-peer
Collaboration Training Grid
Enterprise Grid
Students
Information Grid
Compute Grid R2 R1
Campus Grid
Teacher
Overlapping Heterogeneous
Dynamic Grid Islands

42. (b) Federated OGSA Grid
(a) Layered OGSA Grid
Core
Service
Application
OGSA Interface
OGSA Mediation
Core
Service
Appl.
Grid-1
Grid-2
OGSA or non OGSA Interface-2
OGSA or non OGSA Interface-1
(b) Federated OGSA Grid

43. Many Gaps in Generic Services
Some gaps like Workflow and Notification are to make production versions of current projects
Just in UK workflow from DAME, DiscoveryNet, EDG, Geodise, ICENI, myGrid, Unicore plus Cardiff, NEReSC ….
RGMA and Semantic Grid offer improved meta-data and Information services compared to UDDI and MDS (Globus)
Need comprehensive federated Information service
Security requires architecture supporting dynamic fine-grain authorization
UK e-Science has pioneered Information Grids but gap is continuation of OGSA-DAI, integration with other services and P2P decentralized models
Functionality of Compute/File Grids quite advanced but services probably not robust enough for LCG or Campus Grids

44. Gaps in Other Grid services
Portals and User Interfaces – Noted gap that many not using Grid Computing Environment “best practice” with component based user-interfaces matching component-based middleware
Programming Models (using workflow runtime)
Fabric Management (should be integrated with central service management and Information system), Computational Steering, Visualization, Datamining, Accounting, Gridmake, Debugging, Semantic Grid tools (consistent with Information system), Collaboration, provenance
Application-specific services
Note new production central Infrastructure can support both research and production services of this type