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

…

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

* 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

9

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

10

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!

11

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

12

A Bird Eye View of World-Wide Grid Environment

Grid Resource Broker

Resource Broker

Application

Grid Information Service


databaseR2R3

RN

R1

R4

R5

R6


13

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

14

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

15

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

16

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

18

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

19

Grids have Emerged as Cyberinfrastructure that scales from

from enterprise to global


Resource Broker

Application



databaseR2R3

RN

R1

R4

R5

R6


20

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

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


1.3 billion (Rs)

27 million

2? billion


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.

• 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

28







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 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

39

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

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On Demand Assembly of Services and Utility/ Market-based Grid Computing

Data Source



Grid Info 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


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



data1

36

45

Res

ults

9 7

Results+

Cost Info

10

11

Bill

12Data Catalogue

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Data Source



Grid Info Service



GridbusGridBank

Data

GSP(e.g., UofM)

PEGSP

(e.g., VPAC)

PE

GSP(e.g., IBM)

CPUorPE


Alchemi

GS

GTS

Cluster Scheduler


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



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


Data Source



Grid Info Service



GridbusGridBank

Data

GSP(e.g., UofM)

PEGSP

(e.g., VPAC)

PE

GSP(e.g., IBM)

CPUorPE


Alchemi

GS

GTS

Cluster Scheduler


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



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







4938


Data Source



Grid Info Service



GridbusGridBank

Data

GSP(e.g., UofM)

PEGSP

(e.g., VPAC)

PE

GSP(e.g., IBM)

CPUorPE


Alchemi

GS

GTS

Cluster Scheduler


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



data1

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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”


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)


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


Data Source



Grid Info Service



GridbusGridBank

Data

GSP(e.g., UofM)

PEGSP

(e.g., VPAC)

PE

GSP(e.g., IBM)

CPUorPE


Alchemi

GS

GTS

Cluster Scheduler


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



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


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


…………

Subject:

“/O=Grid/O=Globus/OU=cs.uwa.edu.au/CN=Alexander Barmouta”

…………


…………

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


Data Source



Grid Info Service



GridbusGridBank

Data

GSP(e.g., UofM)

PEGSP

(e.g., VPAC)

PE

GSP(e.g., IBM)

CPUorPE


Alchemi

GS

GTS

Cluster Scheduler


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



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


Data Source



Grid Info Service



GridbusGridBank

Data

GSP(e.g., UofM)

PEGSP

(e.g., VPAC)

PE

GSP(e.g., IBM)

CPUorPE


Alchemi

GS

GTS

Cluster Scheduler


(e.g., CERN)

PECluster Scheduler

J ob

8

GridResource Broker

2



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


NWSSensor

GridFTPGRIS

GlobusGatekeeper


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


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


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


-- --

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


-- --

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







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

Dr. Rajkumar Buyya

Documents

Dr. Rajkumar Buyya