Download - Dr. Rajkumar Buyya
Grid Computing and The Gridbus Toolkit:
Creating and Managing Utility Grids for eScience and eBusiness Applications
Dr. Rajkumar Buyya Fellow of Grid Computing
Grid Computing and Distributed Systems (GRIDS) Lab. Dept. of Computer Science and Software EngineeringThe University of Melbourne, Australia
gridbus.org/~raj/tut/gridbus.zip
WW Grid
2
4 Essential Utilities (in Home)
(1) Water
(2) Electricity
(3) Gas
(4) Telephone
3
(5) IT services as the fifth utility (water, electricity, gas, telephone, IT)
eScienceeBusiness
eGovernmenteHealth
MultilingualeEducation
…
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GRIDS Lab @ Melbourne
The youngest and one of the largest research labs in the CSSE Dept:
2 PostDocs 2 Research Programmers 7 RHD (6 PhD) students ~5 honours/masters projects
Funding National and International organizations Australian Research Council Many industries (Sun, StorageTek,
Microsoft, IBM) University-wide collaboration:
Faculties of Science, Engineering, and Medicine
Many national and international collaborations.
Academics Industries
Software: Our Grid middleware technologies are
widely in academic and industrial users. Publication:
My research team produces 20% of our Dept’s research output.
EducationR & D
+ Community Services
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Books at Glance: Co-authored/edited
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Presentation Outline
Part 1: Introduction to Grid Computing and Applications Technology Evolution and Application Drivers Grid Challenges, Approaches, and Architecture
Part 2: Grid Economy and Service Oriented Computing Challenges Service-Oriented Grid Architecture (SOGA) Realisation of SOGA
Part 3: Global Grids and Gridbus Technologies Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor
Part 4: Performance Evaluation on the World-Wide Grid Compute Grid Application eScience Application – Belle Analysis Data Grid
Part 5: Closing Remarks Open Challenges in Grid Economy Analogy to Electric Power Grid Summary and Conclusion
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Evolution: Humans eHumans (eHugging, eSmell, eFood!), Science eScience, Business
eBusiness
8
Computing and Communication Technologies Evolution
* Sputnik
1960 1970 1975 1980 1985 1990 1995 2000
* ARPANET
* Email* Ethernet
* TCP/IP* IETF
* Internet Era * WWW Era
* Mosaic
* XML
* PC Clusters* Crays * MPPs
* Mainframes
* HTML
* W3C
* P2P
* Grids
* XEROX PARC wormCO
MP
UTIN
GC
om
mu
nic
ati
on
* Web Services
* Minicomputers
* PCs
* WS Clusters
* PDAs* Workstations
* HTC
2010
* eScience
* Computing Utility
* eBusiness
* SocialNet
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2100
2100 2100 2100 2100
2100 2100 2100 2100
Personal Device SMPs or SuperComputers
LocalCluster
GlobalGrid
SERV ICES
+
PERFORMANCE
Inter PlanetGrid
•Individual•Group•Department•Campus•State•National•Globe•Inter Planet•Universe
Administrative Barriers
EnterpriseCluster/Grid
Computing Evolving towards: Global/Grid Computing
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Leading to Grid (computing) Paradigm:
Cyberinfrastructure for sharing resources
•Inspired by Power Grid!
•* A service-oriented/utility computing paradigm that enables seamless
sharing of geographically distributed, autonomous resources.
•* This was the original aim of building Internet although it ended up in
giving birth to email!
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What is Grid ?(there are several definitions)
A type of parallel and distributed system that enables the sharing, selection, & aggregationof geographically distributed “autonomous” resources:
Computers – PCs, workstations, clusters, supercomputers, laptops, notebooks, mobile devices, PDA, etc;
Software – e.g., ASPs renting expensive special purpose applications on demand;
Catalogued data and databases – e.g. transparent access to human genome database;
Special devices/instruments – e.g., radio telescope – SETI@Home searching for life in galaxy.
People/collaborators.
depending on their availability, capability, cost, and user QoS requirements.
Widearea
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A Bird Eye View of World-Wide Grid Environment
Grid Resource Broker
Resource Broker
Application
Grid Information Service
Grid Resource Broker
databaseR2R3
RN
R1
R4
R5
R6
Grid Information Service
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Type of Services Modern Grids Offer
Computational Services – CPU cycles NASA IPG, WWG, TeraGrid, SETI@Home
Data Services Data replication, management, secure
access--LHC Grid/Napster Application Services
Access to remote software/libraries and license management—NetSolve
Information Services Extraction and presentation of data with
meaning Knowledge Services
The way knowledge is acquired and managed using meta data & semantics.
Utility Computing Services
Computional Grid
Data Grid
ASP Grid
Information Grid
Knowledge Grid
Utility Grid
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Prominent Grid Drivers: Emerging e-Science and e-Business
Apps Next generation experiments, simulations, sensors, satellites, even people
and businesses are creating a flood of data. e-Science refers to the large scale science that will increasingly be carried
out through distributed global collaborations enabled by the Internet.
Life Sciences Digital Biology
Finance: Portfolio analysis
~PBytes/sec
Newswire & data mining:Natural language engineering
Astronomy
Internet & Ecommerce
High Energy Physics Brain Activity Analysis
Quantum Chemistry
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1. Online Medical Instrumentation and Neuroscience
Osaka Univ. Hospital
Osaka Univ. DV transfer
Life-electronics laboratory,AIST
Data Analysis
•Provision of MEG•Provision of expertise in the analysis of brain function
Cybermedia Center
Data Generation
Analysis Results
Analysis Results
Virtual Laboratoryfor medicine and brain science
•Knowledge sharing•MEG sharing?•Data Sharing
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3. Enterprise Computing Applications
Traditional Model Grid Based Model
Email server
Webserver
Databaseserver
Appsserver
Upgrade to a new serverto handle
more users
Horizontal integration of Email, Web, Data, and Apps servers
Service Virtualization Layer & Load Balancing
Global Grids and Challenges
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E-Science / E-Business App Elements
Distributed instruments
Distributed computation
Distributed data
Peers sharing ideas and collaborative interpretation of data/resultsE-Scientist
2100 2100 2100 2100
2100 2100 2100 2100
Remote Visualization
Data & Compute Service
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Grids have Emerged as Cyberinfrastructure that scales from
from enterprise to global
Grid Resource Broker
Resource Broker
Application
Grid Information Service
Grid Resource Broker
databaseR2R3
RN
R1
R4
R5
R6
Grid Information Service
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2100
2100 2100 2100 2100
2100 2100 2100 2100
Personal Device SMPs or SuperComputers
LocalCluster
GlobalGrid
SERV ICES
+
PERFORMANCE
Inter PlanetGrid
•Individual•Group•Department•Campus•State•National•Globe•Inter Planet•Universe
Administrative Barriers
EnterpriseCluster/Grid
Grid-based Utility Computing model need to scale from desktops to Global level
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Grids need to offer a wide variety of services
Computational Services – CPU cycles SETI@Home, NASA IPG, TeraGrid, I-Grid,…
Data Services Data replication, management, secure
access--LHC Grid/Napster Application Services
Access to remote software/libraries and license management—NetSolve
Information Services Extraction and presentation of data with
meaning Knowledge Services
The way knowledge is acquired and managed—data mining.
Utility Computing Services Towards a market-based Grid computing:
Leasing and delivering Grid services as ICT utilities.
Computional Grid
Data Grid
ASP Grid
Information Grid
Knowledge Grid
Utility Grid
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Grid Challenges
Security
Resource Allocation & Scheduling
Data locality
Network Management
System Management
Resource Discovery
Uniform Access
Computational Economy
Application Construction
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Grid Operations Management Challenges – dynamic resources, policies, and
self interested entities
Grid Economy Technologies
GOC
GSP1
GSPGSP
GSP2
Grid Exchange
GSP3
GSP4
GSP5
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Some Grid Initiatives Worldwide
Australia Nimrod-G Gridbus DISCWorld GrangeNet. APACGrid ARC eResearch
Brazil OurGrid, EasyGrid LNCC-Grid + many others
China ChinaGrid – Education CNGrid - application
Europe UK eScience EU Grids.. and many more...
India I-Grid
Japan NAGERI
Korea...N*Grid
SingaporeNGP
USA Globus GridSec AccessGrid TeraGrid Cyberinfrasture and many more...
Industry Initiatives IBM On Demand Computing HP Adaptive Computing Sun N1 Microsoft - .NET Oracle 10g Infosys – Enterprise Grid Satyam – Enterprise Grid StorageTek –Grid.. and many more
Public Forums Global Grid Forum Australian Grid Forum Conferences:
CCGrid Grid HPDC E-Science
http://www.gridcomputing.com
1.3 billion – 3 yrs
1 billion – 5 yrs
450million – 5 yrs
486million – 5 yrs
1.3 billion (Rs)
27 million
2? billion
120million – 5 yrs
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mix-and-match (service)
Object-oriented
Internet/partial-P2P
Network enabled Solvers
Economic-based Utility / Service-Oriented
ComputingNimrod-G
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The Gridbus Project @ Melbourne:Enable Leasing of ICT Services on
Demand
WWG
World Wide Grid!On Demand Utility
Computing
Gridbus
Distributed Data
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The Gridbus Project @ GRIDS Lab, The University of Melbourne: Toolkit for Creating and Deploying e-Research Applications on Utility Grids
The Gridbus Project @ GRIDS Lab, The University of Melbourne: The Gridbus Project @ GRIDS Lab, The University of Melbourne: Toolkit for Creating and Deploying eToolkit for Creating and Deploying e--Research Applications on Utility GridsResearch Applications on Utility Grids
Gridbus
Distributed Data
http://www.gridbus.org
• Gridbus is a “open source” Grid R&D project with focus on Grid Economy, Utility Grids and Service Oriented Computing.
• Gridbus Middleware components include:– Alchemi: .NET-based Enterprise Grid
– Grid Market Directory and Web Services
– Grid Bank: Accounting and Transaction Management
– Visual Tools for Creation of Distributed Applications
– Grid Service Broker and Scheduling
– Workflow Management Engine
– GridSim Toolkit
– Libra: SLA-based Resource Allocation
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Presentation Outline
Part 1: Introduction to Grid Computing and Applications Technology Evolution and Application Drivers Grid Challenges, Approaches, and Architecture
Part 2: Grid Economy and Service Oriented Computing Challenges Service-Oriented Grid Architecture (SOGA) Realisation of SOGA
Part 3: Global Grids and Gridbus Technologies Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor
Part 4: Performance Evaluation on the World-Wide Grid Compute Grid Application eScience Application – Belle Analysis Data Grid
Part 5: Closing Remarks Open Challenges in Grid Economy Analogy to Electric Power Grid Summary and Conclusion
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Gridbus considers: “Incentive” as a Design Parameter for Grid
Computing Grids aim at exploiting synergies that result
from cooperation of autonomous distributed entities. Synergies include:
Creation of Virtual Organisations/Enterprises Resource sharing Aggregation of resources on demand.
For this cooperation to be sustainable, participants needs to have (economic) incentive.
Therefore, “incentive” mechanisms should be considered as one of key design parameters of Grid computing.
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Grid Economy: Methodology for Sustained Resourced Sharing and Managing Supply-and-Demand for Resources
31
Benefits of Computational Economy
It provides an effective paradigm for managing self interested and self-regulating entities (resource owners and consumers)
Helps in regulating supply-and-demand of resources. Services can be priced in such a way that equilibrium is maintained.
User-centric / Utility driven Scalable:
No need of central coordinator (during negotiation) Resources(sellers) and also Users(buyers) can make their own decisions and
try to maximize utility and profit. Adaptable, It allows to offer different QoS (quality of services) to different applications
depending the value users place on them. It offers incentive for resource owners for being part of the grid! It offers incentive for resource consumers for being good citizens. It improves the utilisation of resources.
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It helps Users to Achieve their Goals
Grid Consumers Execute jobs for solving varying problem size and
complexity Benefit by selecting and aggregating resources wisely Tradeoff timeframe and cost
Strategy: minimise expenses Grid Providers
Contribute (“idle”) resource for executing consumer jobs Benefit by maximizing resource utilisation Tradeoff local requirements & market opportunity
Strategy: maximise return on investment
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New challenges of Grid Economy
Grid Service Providers (GSPs) How do I decide service pricing models ? How do I specify them ? How do I translate them into resource allocations ? How do I enforce them ? How do I advertise & attract consumers ? How do I do accounting and handle payments? …..
Grid Service Consumers (GSCs) How do I decide expenses ? How do I express QoS requirements ? How do I trade between timeframe & cost ? How do I map jobs to resources to meet my QoS needs? …..
They need mechanisms and technologies for value expression, value translation, and value enforcement.
GRACE: A Reference Grid Economy Services Architecture
GRid Architecture for Computational Economy (GRACE)
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Market-based Computing Systems Requirements
To enable users (GSPs and GSCs) to realise economic value, market-based systems need to provide mechanisms for:
Value Expression a means to express their requirements, valuations, and
objectives Value Translation
scheduling policies to translate them to resource allocations
Value Enforcement mechanisms to enforce the selection and allocation of
differential services, and dynamic adaptation to changes in their availability at runtime
Market mechanisms, accounting and payment, Reservation of resources.
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Grid Node N
GRACE: A ReferenceService-Oriented Grid Architecture for Computational
Economies
Grid Consumer
Pro
gra
mm
ing
En
viro
nm
ents
Grid Resource Broker
Grid Service Providers
Grid Explorer
Schedule Advisor
Trade Manager
Job ControlAgent
Deployment Agent
Trade Server
Resource Allocation
ResourceReservation
R1
Misc. services
Information Service
R2 Rm…
Pricing Algorithms
Accounting
Grid Node1
…
Grid Middleware Services
…
…
HealthMonitor
Grid Market Services
JobExec
Info ?
Secure
Trading
QoS
Storage
Sign-on
Grid Bank
Ap
pli
cati
on
s
Data Catalogue
37
Realising Market-based Grid: Minimal New Components
Grid Market Directory Services Grid Trading Services –
for different economic models Grid Metering Services Grid Accounting and Payment Services Grid Service Broker
38
Gridbus and Complementary Grid Technologies – realizing
GRACE
AIXSolarisWindows Linux
.NET GridFabricSoftware
GridApplications
Core GridMiddleware
User-LevelMiddleware(Grid Tools)
GridBank
Grid Exchange & Federation
JVM
Grid Brokers:
X-Parameter Sweep Lang.
Gridbus Data Broker
MPI
Condor SGE TomcatPBS
Alchemi
Workflow
IRIX OSF1 Mac
Libra
Globus Unicore ……Grid
MarketDirectory
PDB
CDB
Worldwide Grid
GridFabricHardware
……
PortalsScience Commerce Engineering ……Collaboratories
……
Workflow Engine
Grid Storage Economy
Gri
d E
con
om
y NorduGrid XGrid
ExcellGrid
Nimrod-G
GRIDSIM
Gridscape
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On Demand Assembly of Services: Interaction Between Grid Components
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)
(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
Job
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Resu
lts9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
4038
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
4138
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
42
Alchemi: .NET-based Enterprise Grid Platform & Web Services
InternetInternet
InternetInternet
Alchemi Worker Agents
Alchemi Manager
Alchemi Users
Web Services
Web Services
•SETI@Home like Model•General Purpose•Dedicated/Non-dedicate workers•Role-based Security•.NET and Web Services•C# Implementation•GridThread and Job Model Programming•Easy to setup and use• Widely in use!
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Some Users of Alchemi
Tier Technologies, USALarge scale document processing using Alchemi framework
CSIRO, AustraliaNatural Resource Modeling
The Friedrich Miescher Institute (FMI) for Biomedical Research, SwitzerlandPatterns of transcription factors in mammalian genes
Satyam Computers Applied Research Laboratory, IndiaMicro-array data processing using Alchemi framework
The University of Sao Paulo, BrazilThe Alchemi Executor as a Windows Service
stochastix GmbH, GermanyAsynchronous Excel Tasks using ManagedXLL and Alchemi .Net Grid Computing framework.
Many users in Universities: See next for an example.
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Students' project gives old computers new life - 1/25/2005
4538
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
d
46
Globus Technologies Usage
Security (GSI - Globus Security Infrastructure) - single sign-on and authentication based on RSA public key cryptography technology.
You need have Grid ID, public key, and private key (assigned by trusted CA) Authorization to use: You need have your Grid ID mapped to a physical (login)
account on every Grid nodes that you want to use. Authentication: User proxy (trigger by grid-proxy-init) and Grid node
gatekeeper authenticate each other by exchanging messages. (If you can decrypt the message that I sent by encrypting using your public key, then you are who you are claiming to be.)
Information (MDS - Metacomputing Directory Service) – LDAP-server based uniform access to resource structure/state information.
GIIS – Grid Index Information Service (one for your Grid!/organisation) GRIS – Grid Resource Information Service (one for each node).
Communications (grid-ftp) - multi-method communication and QoS management.
Process/Job Management (GRAM - Globus Resource Allocation Manager) - Low-level (uniform) API for various local schedulers.
Remote file access (GASS - Global Access to Secondary Storage). Reservation of Resources in Advance (GARA).
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Globus Components (in One Slide)
Globus SecurityInfrastructure
Job Manager
GRAM client API calls to request resource allocation
and process creation.
MDS client API callsto locate resources
Query current statusof resource
Create
RSL Library
Parse
RequestAllocate &
create processes
Process
Process
Process
Monitor &control
Site boundary
Client-side APIs MDS: Grid Index Info Server
Gatekeeper
MDS: Grid Resource Info Server
Local Resource Manager
MDS client API callsto get resource info
GRAM client API statechange callbacks
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Presentation Outline
Part 1: Introduction to Grid Computing and Applications Technology Evolution and Application Drivers Grid Challenges, Approaches, and Architecture
Part 2: Grid Economy and Service Oriented Computing Challenges Service-Oriented Grid Architecture (SOGA) Realisation of SOGA
Part 3: Global Grids and Gridbus Technologies Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor
Part 4: Performance Evaluation on the World-Wide Grid Compute Grid Application eScience Application – Belle Analysis Data Grid
Part 5: Closing Remarks Open Challenges in Grid Economy Analogy to Electric Power Grid Summary and Conclusion
4938
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
The Grid Market Directory
Grid Vision: To enable the creation of Virtual Enterprise
(VE), Virtual Oranisation (VO), or Grid MarketPlace (GMP).
51
A Market-Oriented Grid Environment
“Solve this in5hrs for $20”
Grid Market Directory (GMD)
ResourceBroker
Grid Info. Service
GTS
GTS
(Grid Service Provider)
GTS
GTS GTS
“register me as GSP”
“Give me list of GSPs & price?”
“service available?”
(GTS - Grid Trade Server)
(GSP)
“service available?”“service available?”
(RB selects GSPs)
“Solve this in5hrs for $20”
Grid Market Directory (GMD)
ResourceBroker
Grid Info. Service
GTSGTS
GTSGTS
(Grid Service Provider)
GTSGTS
GTSGTS GTSGTS
“register me as GSP”
“Give me list of GSPs & price?”
“service available?”
(GTS - Grid Trade Server)
(GSP)
“service available?”“service available?”
(RB selects GSPs)
52
Grid Market Infrastructure
Grids need to provide an infrastructure that supports: (a) the creation of one or more GMP registries; (b) the contributors to register themselves as
GSPs along with their resources/application services that they wish to provide;
(c) GSPs to publish themselves in one or more GMPs along with service prices; and
(d) Grid resource brokers to discover resources/services and their attributes (e.g., access price and usage constraints) that meet user QoS requirements.
53
GMD Architecture
Grid Service Info (RDBMS)
Web Server (Tomcat)
GMD QueryWebservice
Consumer (Web Client)
Grid Market Directory (GMD)
GMD PortalManager
Provider (Web Client)
Publish/Manage Query(SOAP+XML)
Grid Node
Browse
Consumer (Grid Resource Broker)
Grid NodeGrid Node
Jobsubmission
54
Globus MDS Vs Gridbus GMD
GSP2
GSP1
GIIS
R1
R2
R3
R4
GIIS
VO1
VO2
register
register
R5
GSP2
GSP1
GIIS
R1
R2
R3
R4
GIIS
VO1
VO2
register
register
R5
GSP2
GSP1
GMD
R1
R2
R3
R4
GMD
GMP1
GMP2
GSP2 register
GSP2 register
GSP1 register
GSP1 regist
er
R5
GSP2
GSP1
GMD
R1
R2
R3
R4
GMD
GMP1
GMP2
GSP2 register
GSP2 register
GSP1 register
GSP1 regist
er
R5
Globus MDS Gridbus GMD
55
GSP Registration
56
GSP Service Publication
57
GSP Service Browsing
58
GMD Query Message
Query Message
SOAP Message Repository Handler
Query Processing
GMD Repository
GMD Query Webservice
Repository Handler
Query Processing
HTTPServer
SOAP Engine
GMD Repository
GMD Query Webservice
Query Message
GMD Webservice client
XML
59
GMD Use Case: SC’02 HPC Challenge Demonstration
60
How can I Access GMD Software ?
Download, Deploy, and Use it: “Open Source” Reference Implementation
(Java-based) is available: http://www.gridbus.org/gmd/
Or Make use of Global GMD registry hosted by the Gridbus Project.
For more info, Read Technical Report: A Market-Oriented Grid Directory Service
for Publication and Discovery of Grid Service Providers and their Services
6138
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
Grid Bank
A Grid Accounting Services Architecture
63
The Grid Bank Operations
Grid Resource
Broker (GRB)
GridBank Payment Module
Grid Trade Server
GridBank Charging Module
GridBank Server
Establish Service Costs
A p p l i c a t i o n s
Grid Agent Grid Resource
Meter
GridCheque
Deploy Agent and Submt Jobs
Usage Agreement
Resource Usage
GridCheque
Grid Service Provider (GSP)
GridCheque + Resource Usage (GSC Account Charge
Grid Service Consumer (GSC)
R1 R2 R3 R4
User
User
64
GridBank Architecture
Security Layer Payment Protocol Layer Accounting Layer
Globus I/O API
GSS API
(SSL sockets)
GB Security Protocol
Admin Protocol
GridCheque Protocol
GridHash Protocol
Other Payment Protocols
GB Administration
GB Accounts
GB Database
e.g. SQL
Globus I/O API
GSS API
(SSL sockets)
GB Security Protocol
Admin Protocol
GridCheque Protocol
GridHash Protocol
GridBank API
GridBank Client ArchitectureInsecure network
•Open account•Request account details•Request account statement•Funds transfer•Availability check•Lock funds•Transfer from locked funds
•Deposit•Change credit limit•Cancel transfer•Close account•Withdrawal
GridBankPayment Module
GridBankChargingModule
65
Grid Bank Components
Grid Bank Server Regular account management features (open,
close, delete, update, browse) are supported. GridBank Database GridBank Client Access Interface
Payment Module Charging Module Protocols in XML format
Resource Usage Record (confirm to GGF RUR format).
66
App
lica
tion
s
Grid Resource Broker (GRB)
Grid
Service P
rovider (G
SP
)
Grid Trade Server
Grid Resource Meter
GridBank Charging Module
R1 R
2R
3R
4
Execute job
Resource Usage Record
GridBankPaymentModule
GridBank Server
Establish Service Rates
GridCheque
User
Chargeable Item 1 – RateChargeable Item 2 – Rate
.
.
.
RATESItem 1 – RateItem 2 – Rate
.
.
.
XXXXX
Usage – Item 1Usage – Item 2
.
.
.
=====
RURCharge for Item 1Charge for Item 2
.
.
.
Service Cost Total
GridCheque +
Charge
Filter relevantresource usage
information
Convert to standardResource Usage
Record
GridBank systemcomponent names are in italics
Grid Components Interaction and Utilization of Grid Bank
67
Grid Bank Usage Scenario
GSPs and GSCs open account with GridBank When GSC wants to consume GSP service, it informs
the GSP about the account to which access cost can be charged.
GSPs can confirm with GridBank whether GSC has sufficient credit or even request to put the amount on hold.
GSP measures the amount of resource consumed and charges the GSC account in Grid Bank.
Grid Bank transfers to tokens/credits/money from GSC to GSP account; and maintains transaction details (Resource Usage Record).
Grid Bank also be used for developing Scalable Authentication Infrastructure.
68
X509v3 Digital Certificate
…………
Subject:
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Chris McDonald”
…………
Clients
ResourcesResource access authorization file (grid-mapfile)
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Alexander Barmouta” alex
“/O=Grid/O=Globus/OU=cs.mu.oz.au/CN=Rajkumar Buyya” rajkumar
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Chris McDonald” chris
X509v3 Digital Certificate
…………
Subject:
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Alexander Barmouta”
…………
X509v3 Digital Certificate
…………
Subject:
“/O=Grid/O=Globus/OU=cs.mu.oz.au/CN=Rajkumar Buyya”
…………
Access Scalability Problem
69
Resource access authorization file (grid-mapfile)
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=GridBank” gridbank
GridBank
Template (local) accounts
gbaccount1
gbaccount2
gbaccount3
Resource access authorization file (grid-mapfile)
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=GridBank” gridbank
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Alexander Barmouta” gbaccount1
Template (local) accounts
gbaccount2
gbaccount3
Request to access resource
Passing client’s Certificate Subject
Execute job
GridBank Accounts“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Alexander Barmouta”
“/O=Grid/O=Globus/OU=cs.mu.oz.au/CN=Rajkumar Buyya”
“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Chris McDonald”
GridBank’s Solution to Access Scalability Problem
70
How can I Access GridBank Software ?
Download, Deploy, and Use it: “Open Source” Reference Implementation
is available: http://www.gridbus.org/
For more info, Read Technical Report: GridBank: A Grid Accounting Services
Architecture (GASA) for Distributed Systems Sharing and Integration
7138
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
The Gridbus Grid Service Broker for Data Grid
Applications
Builds on the Nimrod-G Computational Grid Broker and
Computational Economy [Buyya, Abramson, Giddy, Monash
University, 1999-2001]And
Extends its notion for Data and Service Grids
73
A resource broker for scheduling task farming data Grid applications with static or dynamic parameter sweeps on global Grids.
It uses computational economy paradigm for optimal selection of computational and data services depending on their quality, cost, and availability, and users’ QoS requirements (deadline, budget, & T/C optimisation)
Key Features A single window to manage & control experiment Programmable Task Farming Engine Resource Discovery and Resource Trading Optimal Data Source Discovery Scheduling & Predications Generic Dispatcher & Grid Agents Transportation of data & sharing of results Accounting
Grid Service Broker (GSB)
74
Gridbus Broker Architecture
Grid Middleware
Gridbus Client Gridbus ClientGribus Client
Grid Info Server
Schedule Advisor
Trading Manager
Gridbus Farming Engine
RecordKeeper
Grid Explorer
GE GIS, NWSTM TS
RM & TS
Grid Dispatcher
RM: Local Resource Manager, TS: Trade Server
G
G
CU
Globus enabled node.A
L
Alchemi enabled node.
(Data Grid Scheduler)
DataCatalog
DataNode
Unicore enabled node.
$
$
$
App, T, $, Opt
(Bag of Tasks Applications)
75
Gridbus Broker and Remote Service Access Enablers
Alchemi
Gateway
UnicoreData Store
Access Technology
Grid FTPSRB
-PBS-Condor-SGE
Globus
Job manager
fork() batch()
Gridbusagent
Data Catalog
-PBS-Condor-SGE-XGrid
SSH
fork()
batch()
Gridbusagent
Credential RepositoryMyProxy
Home Node/Portal
GridbusBroker
fork()
batch() -PBS-Condor-SGE-Alchemi-XGrid
Por
tlets
76
Gridbus Services for eScience applications
Application Development Environment: XML-based language for composition of task farming
(legacy) applications as parameter sweep applications. Task Farming APIs for new applications. Web APIs (e.g., Portlets) for Grid portal development. Threads-based Programming Interface Workflow interface and Gridbus-enabled workflow
engine. Resource Allocation and Scheduling
Dynamic discovery of optional computational and data nodes that meet user QoS requirements.
Hide Low-Level Grid Middleware interfaces Globus (v2, v4), SRB, Alchemi, Unicore, and ssh-based
access to local/remote resources managed by XGrid, Condor, SGE.
77
Figure 3 : Logging into the portal.
Drug DesignMade Easy!
Click Here for Demo
78
Excel Plugin to Access Gridbus Services
Excel
ExcelGrid Add-In
ExcelGrid Runner
ExcelGridJob
ExcelGrid Middleware
Gridbus Broker
Enterprise Grid
2100
2100
2100
2100
2100
2100
2100
2100
79
Discover Discover ResourcesResources
Distribute JobsDistribute Jobs
Establish Establish RatesRates
Meet requirements ? Remaining Meet requirements ? Remaining Jobs, Deadline, & Budget ?Jobs, Deadline, & Budget ?
Evaluate & Evaluate & RescheduleReschedule
Discover Discover More More
ResourcesResources
Compose & Compose & ScheduleSchedule
Adaptive Scheduling Steps
80
Deadline (D) and Budget (B) Constrained Scheduling Algorithms
Algorithm
Execution Time (D)
Execution Cost (B)
Compute Grid
Data Grid
Cost Opt Limited by D
Minimize Yes Yes
Cost-Time Opt
Minimize if possible
Minimize Yes
Time Opt Minimize Limited by B
Yes Yes
Conservative-Time Opt
Minimize Limited by B, jobs have guaranteed minimum budget
Yes
81
Gridbus Project: Some Applications and Users
Gridbus Project: Gridbus Project: Some Applications and UsersSome Applications and Users
http://www.gridbus.org
BioGrid: Molecular docking for Drug-discovery
BioGrid: Molecular docking for Drug-discovery
High Energy Physics: Particle Discovery
High Energy Physics: Particle Discovery
Melbourne University
NeuroScience: Brain Activity Analysis
NeuroScience: Brain Activity Analysis
Natural Resource ModelingNatural Resource Modeling
CSIRO Land and Water, Austraila.
Large Scale document processing
Large Scale document processing
Tier Technologies, USA.
Detection of patterns of transcription factors in mammalian genes
Detection of patterns of transcription factors in mammalian genes
8238
On Demand Assembly of Services and Utility/ Market-based Grid Computing
Data Source
(Instruments/distributed sources)
Data Replicator(GDMP) ASP Catalogue
Grid Info Service
Grid Market Directory
GSP(Accounting Service)
GridbusGridBank
Data
GSP(e.g., UofM)
PEGSP
(e.g., VPAC)
PE
GSP(e.g., IBM)
CPUorPE
Grid Service (GS)(Globus)
Alchemi
GS
GTS
Cluster Scheduler
Grid Service Provider (GSP)
(e.g., CERN)
PECluster Scheduler
J ob
8
GridResource Broker
2
Visual Application Composer
Application CodeExplore
data1
36
45
Res
ults
9 7
Results+
Cost Info
10
11
Bill
12Data Catalogue
83
Case Study: High Energy Physics and Data Grid The Belle Experiment
KEK B-Factory, Japan Investigating fundamental
violation of symmetry in nature (Charge Parity) which may help explain the universal matter – antimatter imbalance.
Collaboration 400 people, 50 institutes
100’s TB data currently
84
Australian Belle Data Grid Platform
Grid Service Broker
Replica Catalog
AARNET
NWS NameServer
VirtualOrganization
Analysis Request
Analysis Results
CertificateAuthority
NWSSensor
GridFTPGRIS
GlobusGatekeeper
Dual Intel Xeon 2.8 Ghz, 2 GB RAM
NWSSensor
GridFTPGRIS
GlobusGatekeeper
Dual Intel Xeon 2.8 Ghz, 2 GB RAM
NWSSensor
GridFTPGRIS
GlobusGatekeeper
Dual Intel Xeon 2.8 Ghz, 2 GB RAM
GRIDS Lab, University of Melbourne
Dept. of Physics,University of Sydney
ANU, Canberra
Dept. of Computer Science, University of Adelaide
NWSSensor
GridFTPGRIS
GlobusGatekeeper
Intel Pentium 2.0 Ghz, 512 MB RAM
Dept. of Physics,University of Melbourne
NWSSensor
GridFTPGRIS
GlobusGatekeeper
Dual Intel Xeon 2.8 Ghz, 2 GB RAM
85
Case Study: Event Simulation and Analysis
B0->D*+D*-Ks
• Simulation and Analysis Package - Belle Analysis Software Framework (BASF)• Experiment in 2 parts – Generation of Simulated Data and Analysis of the distributed data
Analyzed 100 data files (30MB each) were distributed among the five nodes
86
Resources Used and their Service Price
Organization
Node details Role Cost (in G$/CPU-sec)
CS,UniMelb belle.cs.mu.oz.au4 CPU, 2GB RAM, 40 GB HD, Linux
Broker host, Data host, NWS server
N.A. (Not used as a compute resource)
Physics, UniMelb fleagle.ph.unimelb.edu.au1 CPU, 512 MB RAM, 40 GB HD, Linux
Replica Catalog host, Data host, Compute resource, NWS sensor
2
CS, University of Adelaide
belle.cs.adelaide.edu.au4 CPU (only 1 available) , 2GB RAM, 40 GB HD, Linux
Data host, NWS sensor
N.A. (Not used as a compute resource)
ANU, Canberra belle.anu.edu.au4 CPU, 2GB RAM, 40 GB HD, Linux
Data host, Compute resource, NWS sensor
4
Dept of Physics, USyd
belle.physics.usyd.edu.au4 CPU (only 1 available), 2GB RAM, 40 GB HD, Linux
Data host, Compute resource, NWS sensor
4
VPAC, Melbourne
brecca-2.vpac.org180 node cluster (only head node used), Linux
Compute resource,NWS sensor
6
87
Network Cost (in Grid $/Currency!)
NETWORK COSTS BETWEEN THE DATA HOSTS AND THE COMPUTE RESOURCES
(IN G$ PER MB) Data Node
Compute Node ANU UniMelb
Physics Sydney Physics
VPAC
ANU 0 34.0 31.0 38.0 Adelaide CS 34.0 36.0 31.0 33.0 UniMelb Physics 40.0 0 32.0 39.0 UniMelb CS 36.0 30.0 33.0 37.0 Sydney Physics 35.0 33.0 0 37.0
88
Deploying Application Scenario
A data grid scenario with 100 jobs and each accessing remote data of ~30MB
Deadline: 3hrs. Budget: G$ 60K Scheduling Optimisation Scenario:
Minimise Time Minimise Cost
Results:
SUMMARY OF EVALUATION RESULTS
Scheduling strategy Total Time Taken (mins.)
Compute Cost (G$)
Data Cost (G$)
Total Cost (G$)
Cost Minimization 71.07 26865 7560 34425 Time Minimization 48.5 50938 7452 58390
89
Time Minimization in Data Grids
0
10
20
30
40
50
60
70
80
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
Time (in mins.)
Nu
mb
er
of
job
s c
om
ple
ted
fleagle.ph.unimelb.edu.au belle.anu.edu.au belle.physics.usyd.edu.au brecca-2.vpac.org
90
Results : Cost Minimization in Data Grids
0
10
20
30
40
50
60
70
80
90
100
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63
Time(in mins.)
Nu
mb
er o
f jo
bs
com
ple
ted
fleagle.ph.unimelb.edu.au belle.anu.edu.au belle.physics.usyd.edu.au brecca-2.vpac.org
91
SUMMARY OF EVALUATION RESULTS
Scheduling strategy Total Time Taken (mins.)
Compute Cost (G$)
Data Cost (G$)
Total Cost (G$)
Cost Minimization 71.07 26865 7560 34425 Time Minimization 48.5 50938 7452 58390
Observation
Organization
Node details Cost (in G$/CPU-sec)
Total Jobs Executed
Time Cost
CS,UniMelb belle.cs.mu.oz.au4 CPU, 2GB RAM, 40 GB HD, Linux
N.A. (Not used as a compute resource)
-- --
Physics, UniMelb fleagle.ph.unimelb.edu.au1 CPU, 512 MB RAM, 40 GB HD, Linux
2 3 94
CS, University of Adelaide
belle.cs.adelaide.edu.au4 CPU (only 1 available) , 2GB RAM, 40 GB HD, Linux
N.A. (Not used as a compute resource)
-- --
ANU, Canberra belle.anu.edu.au4 CPU, 2GB RAM, 40 GB HD, Linux
4 2 2
Dept of Physics, USyd
belle.physics.usyd.edu.au4 CPU (only 1 available), 2GB RAM, 40 GB HD, Linux
4 72 2
VPAC, Melbourne
brecca-2.vpac.org180 node cluster (only head node used), Linux
6 23 2
92
The GridSim ToolkitA Java based tool for Grid Scheduling
Simulations
Basic Discrete Event Simulation Infrastructure
Virtual Machine (Java, cJVM, RMI)
PCs ClustersWorkstations
. . .
SMPs Distributed Resources
GridSim Toolkit
Application Modeling
InformationServices
Resource Allocation
Grid Resource Brokers or Schedulers’s Simulation
Statistics
Resource Modeling and Simulation (with Time and Space shared schedulers)
Job Management
ClustersSingle CPU ReservationSMPs Load Pattern
Application Configuration
Resource Configuration
Visual Modeler
Grid Scenario
Network
SimJava Distributed SimJava
Resource Entities
Output
Application, User, Grid Scenario’s Input and Results
Add your own policy for resource allocation
93
Selected GridSim Users - 2002
Workflow Scheduling
SKIP (if Time Problem)
95
Grids and Workflow
GETdataset
galfit
GETdataset
store store
sextr
preview
stack
store
storephot
Issues:
•Naming
•Security
•Authorization
•Service interface
•Data representation and interchange
•Programming models
•Work flow
•etc.
Astronomical Data Analysis
(Hugh Couchman, Computing in Canadian Astronomy)
96
Grid-based workflow
Grid workflow A collection of tasks that are processed on distributed
resources in well-defined order. Differences
Grid workflow could be long lasting Large data flow need to be supported (e.g. Sloan
Digital Sky Survey ~Petabytes) Resources used by Grid workflow are heterogeneous Resources are dispersed across multiple
administrative domains Resource availability and utilization varies
dynamically over time
97
Requirements and Challenges
Requirements Composition tools (e.g. expressing large-scale workflow) Harnessing distributed resources and services that meet
user requirements Large-scale data transfer
Challenges Dynamic execution environment of Grid workflow Unknown locations of intermediate data Acquisition of resource information
98
Workflow Management System
Developed a service-oriented workflow management system driven by IBM TSpaces
Provides XML based language for expressing workflow
Able to deploy workflow applications on global grids
Serve as an infrastructure for our future work on economy-based workflow scheduling.
99
Architecture
DatabaseDatabase
Workflow Submission Handler
Workflow Language Parser
Tasks Parameters Dependencies
Resource Discovery
Dispatcher Data Movement
GMD
ReplicaCatalog
Gridbus Broker Globus
Web services HTTP GridFTP
Data transfer
Workflow Planner Application Composition …… Scientific Portal
Workflow Enactment Engine
Workflow description & QoS
Info Service
MDS
Workflow Scheduler
100
Workflow Scheduling System
Workflow Coordinator (WCO) TM generation and activation Life-time of workflow execution
Task Managers (TMs) Task execution Resource discovery and selection Monitoring Failure management
Communication approach between WCO and TMs Communication Model
Complexity of task dependencies (e.g. multiple parents and multiple children) Many-to-many
Solutions Event-driven mechanism Subscription-notification Event exchange server using tuple spaces (IBM TSpaces)
Workflow Coordinator
Task Manager
ResourceGroup
TaskGroup
Monitor
Task ManagerFactory
EventService
Decentralized Scheduling Architecture
101
Event-driven Mechanism using Tuple Spaces
Event Service(IBM TSpaces)
Workflow Coordinator
Task Manager A Task Manager B Task Manager N. . . . . .
status
output
notify
notify
Grid resources
Monitornotify
102
A Sample WF model, Task and Datalink Definition
<datalink> <link> <from>C:port2</from> <to>F:port0</to> </link> <link> <from>D:port2</from> <to>F:port1</to> </link> ….. </datalink>
<task name="C"><executable> <name>ycalc</name> <host>belle.anu.edu.au</host> <accesspoint type="GT2Gram">/data/ycalc.sh</accesspoint> <input>
<port0 type="file">para</port0> <port1 type="msg">5</port1> </input> <output> <port2 type="file">output</port2>
</output></executable>
</task>
optional
A
B C D
E G F
H
Fa Fa Fa
FbFc
FbFd
Fc Fd
Fe Fg Ff
Directed Acyclic Graph
103
Performance Evaluation (Synthetic Application on Belle Data Grid)
Task ProgramInput 1 Input 2 Output
type type type
A xcalc parameter parameter file
B ycalc file parameter file
C ycalc file parameter file
D ycalc file parameter file
E addcalc file file file
F addcalc file file file
G addcalc file file file
H merge merge three input files into one file
Workflow Task Application
A
B C D
E G F
H
Fa Fa Fa
FbFc
Fb Fd Fc Fd
Fe Fg Ff
Experimental Workflow
104
Test-bed
Node Machine Detail Location
belle.cs.mu.oz.au 4 CPU, 2GB RAM, 70 GB HD, RH Linux 8.0 , Globus 2.4
Melbourne
belle.anu.edu.au 4 CPU, 2GB RAM, 70 GB HD, RH Linux 7.3, Globus 2.4
Canberra
belle.physics.usyd.edu.au 4 CPU, 2GB RAM, 70 GB HD, RH Linux 7.3 , Globus 2.4
Sydney
gilels.cs.mu.oz.au 1 CPU, 512MB RAM, 10 GB HD, RH Linux 8.0, CoG 1.1
Melbourne
105
Execution Progress
A
B C D
E G F
H
Fa Fa Fa
FbFc
Fb Fd Fc Fd
Fe Fg Ff
Task
Time (min.)
H
G
F
E
D
C
B
A
belle.cs.mu.oz.au
belle.anu.edu.au
belle.physics.usyd.edu.au
0 2.0 4.0 6.0 8.0 10 12 14
106
Comparison of Sequential and Distributed Execution
Task Time
A 3m59.849s
B 3m59.997s
C 4m59.997s
D 5m59.997s
E 4.996s
F 5.996s
G 5.996s
H 0.005s
Total 19m13s
Task NodeStart time
(min)End time
(min)Time
A belle.cs.mu.oz.au 0 4.137 4.137m
B belle.cs.mu.oz.au 4.169 8.822 4.652m
C belle.anu.edu.au 4.174 9.66 5.486m
D belle.physics.usyd.edu.au
4.281 10.684 6.403m
E belle.anu.edu.au 9.669 10.097 25.62s
F belle.physics.usyd.edu.au
10.708 11.145 26.16s
G belle.cs.mu.oz.au 10.688 11.152 27.78s
H belle.cs.mu.oz.au 11.172 11.394 13.32s
WFEE Execution Time 0 11.394 11.394m
Distributed Execution time on Grid Testbed
Sequential Execution Time
107
Presentation Outline
Part 1: Introduction to Grid Computing and Applications Technology Evolution and Application Drivers Grid Challenges, Approaches, and Architecture
Part 2: Grid Economy and Service Oriented Computing Challenges Service-Oriented Grid Architecture (SOGA) Realisation of SOGA
Part 3: Global Grids and Gridbus Technologies Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor
Part 4: Performance Evaluation on the World-Wide Grid Compute Grid Application eScience Application – Belle Analysis Data Grid
Part 5: Closing Remarks Open Challenges in Grid Economy Analogy to Electric Power Grid Summary and Conclusion
Alessandro Volta in Paris in 1801 inside French National Institute shows the battery
while in the presence of Napoleon I
Fresco by N. Cianfanelli (1841) (Zoological Section "La Specula" of National History Museum of Florence
University)
109
….and in the future, I imagine a WorldwidePower (Electrical) Grid …...
What ?!?!This is a mad man…
Oh, monDieu !
110
2005 - 1801 = 204 Years
111
(5) IT services as the fifth utility (water, electricity, gas, telephone, IT)
eScienceeBusiness
eGovernmenteHealth
MultilingualeEducation
…
112
Summary and Conclusion
Introduced requirements for an eScience application
Demonstrated suitability of Grid computing as Cyberinfrastructure for eScience and e-Business.
Grids exploit synergies that result from cooperation of autonomous entities:
Resource sharing, dynamic provisioning, and aggregation at global level.
Grids allow users to dynamically lease Grid services at runtime based on their quality, cost, availability, and users QoS requirements.
Delivering ICT services as computing utilities. Grids offer enormous opportunities for realizing
eScience and eBusiness at global level.
113
Any Questions ?
Web - http://www.gridbus.org
114
Thanks for your attention!
We Welcome Cooperation in Research and Commercialisation!
http:/www.gridbus.org | http://www.gridbus.com