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 Engineering The University of Melbourne, Australia gridbus.org/~raj/tut/gridbus. zip WW Grid
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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
…
4
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
5
Books at Glance: Co-authored/edited
6
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
7
Evolution: Humans eHumans (eHugging, eSmell, eFood!), Science eScience, Business
eBusiness
8
Computing and Communication Technologies Evolution
Grid-based Utility Computing model need to scale from desktops to Global level
21
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
22
Grid Challenges
Security
Resource Allocation & Scheduling
Data locality
Network Management
System Management
Resource Discovery
Uniform Access
Computational Economy
Application Construction
23
Grid Operations Management Challenges – dynamic resources, policies, and
self interested entities
Grid Economy Technologies
GOC
GSP1
GSPGSP
GSP2
Grid Exchange
GSP3
GSP4
GSP5
24
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
25
mix-and-match (service)
Object-oriented
Internet/partial-P2P
Network enabled Solvers
Economic-based Utility / Service-Oriented
ComputingNimrod-G
26
The Gridbus Project @ Melbourne:Enable Leasing of ICT Services on
Demand
WWG
World Wide Grid!On Demand Utility
Computing
Gridbus
Distributed Data
27
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.
– 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
28
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
29
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.
30
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.
32
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
33
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)
35
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.
36
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
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!
43
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.
44
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).
47
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
48
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
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.
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