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Title: ServiceOriented Science Scaling Science Services


1
Service-Oriented ScienceScaling Science Services
Ian Foster Argonne National Laboratory University
of Chicago Univa Corporation
APAC Conference, September 28, 2005 iGrid
Workshop, September 27, 2005
2
Two Questions
  • How do we scale the number of scientists
    benefiting from computational techniques?
  • What should be the role of infrastructure
    providers in enabling this scaling?

3
Computational Science
Computation joins theory experiment as a
third mode of scientific enquiry
Program data
PC or Supercomputer
  • Increasingly sophisticated computational
    approaches
  • Monolithic programs, databases
  • Inflexible hard to evolve
  • Mismatch with reality of diverse distributed
    teams, resources, approaches

Genbank
4
Decompose over the Network
Service-Oriented Architecture
  • Clients can then integrate dynamically
  • Select compose services
  • Select best of breed providers
  • Publish result as a new service
  • Need not know implementation details
  • Note complements, not replaces, HPC

5
For ExampleVirtual Observatories
Surveys Observatories Missions
Survey and Mission Archives
Digital libraries
Numerical Sims
6
Having Decomposed, Integrate
  • For example
  • Registries
  • Value-added services
  • Workflows
  • Issues
  • Description
  • Discovery
  • Composition
  • Adaptation evolution
  • Qualities of service security, performance,
    reliability,

7
Example Value Added ServicePUMA
PUMA Knowledge Base Information about proteins
analyzed against 2 million gene sequences
Analysis on Grid Involves millions of BLAST,
BLOCKS, and other processes
Natalia Maltsev et al.
8
SOA Silo-Oriented Architecture?
  • What about dynamic behaviors?
  • Time-varying load
  • Dynamically instantiated services
  • What about operating costs?
  • Software deployment maintenance
  • Security other concerns

9
We Need to Decompose in Two Dimensions
10
We Need to Decompose in Two Dimensions
11
Decomposition EnablesOn-Demand Provisioning
  • Aggregateresources
  • Deliver toservices
  • Separate production consumption
  • Issues
  • Discovery
  • Composition
  • Qualities of service

Provision New Worker Process
SAP GlobusWorld Demo IPC Internet Pricing
Configurator
12
The Globus-BasedLIGO Data Grid
LIGO Gravitational Wave Observatory
Birmingham
Replicating gt1 Terabyte/day to 8 sites gt30
million replicas so far MTBF 1 month
www.globus.org/solutions
13
Decomposition EnablesSeparation of Concerns
Roles
S1
User
S2
D
S3
14
Scaling Up
  • Sometimes through heroism you can
    makesomething work. However, understandingwhy
    it worked, abstracting it, making it aprimitive
    is the key to getting to the nextorder of
    magnitude of scale. Robert Calderbank
  • ? We want to scale the number,
    robustness, performance of services

15
Identifying Primitives(1) Taking Services
Seriously
  • Model the world as a collection of services
  • Computations, computers, instruments, storage,
    data, communities, agreements,
  • Focus on what these things have in common
  • E.g., lifecycle management
  • Negotiation, deployment/creation, modeling,
    monitoring, management, termination
  • E.g., security
  • Authentication, authorization, audit,
  • ? Web Services-based Grid infrastructure

I. Foster, S. Tuecke, Describing the Elephant
The Many Faces of IT as Service, ACM Queue, 2005
16
Identifying Primitives(2) Interface
Specifications
Applications of the framework(Compute, network,
storage provisioning,job reservation
submission, data management,application service
QoS, )
WS-Agreement(Agreement negotiation)
WS Distributed Management(Lifecycle, monitoring,
)
WS-Resource Framework WS-Notification(Resource
identity, lifetime, inspection, subscription, )
Web services(WSDL, SOAP, WS-Security,
WS-ReliableMessaging, )
WS-Transfer, WS-Enumeration, WS-Eventing,
WS-Management define similar functions
Foster, Czajkowski, Frey, et al., From OGSI to
WSRF, Proc. IEEE, 93(3). 604-612. 2005
17
Identifying Primitives(3) Open Source
Implementation
www.globus.org
Data Replication
Replica Location
Grid Telecontrol Protocol
CredentialMgmt
Data Access Integration
Community Scheduling Framework
Delegation
Python Runtime
WebMDS
Reliable File Transfer
CommunityAuthorization
Trigger
C Runtime
Workspace Management
GridFTP
Authentication Authorization
Grid Resource Allocation Management
Index
Java Runtime
Data Mgmt
Security
CommonRuntime
Execution Mgmt
Info Services
I. Foster, Globus Toolkit Version 4 Software
for Service-Oriented Systems, LNCS 3779, 2-13,
2005
18
  • Open Science Grid
  • 50 sites (15,000 CPUs) growing
  • 400 to gt1000 concurrent jobs
  • Many applications CS experiments includes
    long-running production operations
  • Up since October 2003 few FTEs central ops

Jobs (2004)
www.opensciencegrid.org
19
Virtual OSG Clusters
OSG
20
Dynamic Service Deployment
Community A
Community Z
  • Requirements
  • Community control
  • Persistence
  • Resource guarantees
  • Non- interference
  • Community scheduling logic
  • Data distribution
  • Community management
  • Science services
  • ...

21
Summary
  • How do we scale the number of scientists
    benefiting from computational techniques?
  • ? Construct powerful science services
  • ? Simplify construction by decomposing roles
    content, function, resource
  • What should be the role of infrastructure
    providers in enabling this scaling?
  • ? Service providers for communities wanting to
    deliver content
  • ? Resource providers for service providers
    wanting to deliver services

22
Service-Oriented ScienceScaling by Separating
Concerns
Simulation code
Expt design
Content
Simulation code
Expt output
Certificate authority
Electronic notebook
Telepresence monitor
Simulation server
Function
Portal server
Data archive
Metadata catalog
Resources
Servers, storage, networks
Experimental apparatus
I. Foster, Service-Oriented Science,
Science, 308, May 6, 2005
23
Acknowledgments
  • NSF, DOE, NASA, IBM for financial support
  • Numerous fine colleagues at Argonne, U.Chicago,
    USC/ISI, and elsewhere
  • In particular

SteveTuecke
KateKeahey
Carl Kesselman
Bill Allcock, Ann Chervenak, Ewa Deelman,
Jennifer Schopf, Mike Wilde
24
For More Information
  • Globus Alliance www.globus.org
  • Papers www.mcs.anl.gov/foster

For those at IGrid Carl Kesselmans Master
Class (Thursday)
For those at APAC Globus Toolkit Tutorial
(Thursday, Friday)
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