the grid introduction

7/27/2019 The Grid Introduction

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GRID COMPUTING

Sandeep Kumar PooniaHead Of Dept. CS/IT

B.E., M.Tech., UGC-NETLM-IAENG, LM-I ACSIT,LM-CSTA, LM- AIRCC, LM-SCIEI, AM -UACEE

O UTLINEWhy we are trying to develop acomplex system?Common TermsIntroduction to Grid ComputingMethods of Grid computingGrid MiddlewareGrid Architecture

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W HY WE ARE TRYING TODEVELOP A COMPLEX SYSTEM ?

We can justify the importance of parallel computing fortwo reasons.

Very large application domains, andPhysical limitations of VLSI circuits

Though computers are getting faster and faster, userdemands for solving very large problems is growing ata still faster rate.

Some examples include weather forecasting, simulationof protein folding, computational physics etc. Sandee

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P HYSICAL LIMITATIONS OF VLSICIRCUITS

The Pentium III processor uses 180 nano meter(nm) technology, i.e., a circuit element like atransistor can be etched within 180 x 10 -9 m .

Pentium IV processor uses 160nm technology.

Intel has recently trialed processors made by using65nm technology.

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H OW MANY TRANSISTORS CAN WEPACK ?

Pentium III has about 42 mill ion transistors and

Pentium IV about 55 million transistors.

The number of transistors on a chip isapproximately doubling every 18 months (Moore sLaw).

There are now 100 transistors for every ant onEarth

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P HYSICAL LIMITATIONS OF VLSICIRCUITS

All semiconductor devices are Si based. It is fairly

safe to assume that a circuit element will take atleast a single Si atom. The covalent bonding in Si has a bond length

approximately 20nm . Hence, we will reach the limit of miniaturization

very soon. The upper bound on the speed of electronic

signals is 3 x 10 8m/sec , the speed of light. Hence, communication between two adjacent

transistors will take approximately 10 -18 sec .


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C LUSTER A RCHITECTURE

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P EER -TO -P EER COMPUTING

Connect to other computersCan access files from any computer on the

network Allows data sharing without going throughcentral serverDecentralized approach also useful for Grid

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P EER TO P EER ARCHITECTURE

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W HY G RID C OMPUTING ?

40% Mainframes are idle90% Unix servers are idle95% PC servers are idle0-15% Mainframes are idle in peak-hour70% PC servers are idle in peak-hour

Source: Grid Computing Dr Daron G Green

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E LECTRICAL P OWER GRID A NALOGY

Electrical power

gridusers (or electricalappli an ces) get access toelectrici ty th rough wa llsockets with no care orconsideration for where orhow the electricity isactually generated.

The power grid linkstog ether power pl ants of many different kinds

The Grid

users (or cl ien t applications)gain access to computingresources (processors, storage,data, applications, and so on) asneeded with little or noknowledge of where thoseresources are located or whatthe underlying technologies,hardware, operating system,and soon are"the Grid" l ink s tog ethercomputing resources (PCs,workstations, servers, storageelements) and provides themechanism needed to accessthem. Sandeep Kumar Poonia

W HY NEED G RID C OMPUTING ?

Core networking technology now accelerates at amuch faster rate than advances in microprocessorspeedsExploiting under utilized resourcesParallel CPU capacity

Virtual resources and virtual organizations forcollaboration

Access to additional resources


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W HO NEEDS G RID C OMPUTING ?

Not just computer scientistsscientists hit the wall when faced with situations:

The amount of data they need is huge and the data is stored indifferent institutions.The amount of similar calculations the scientist has to do ishuge.

Other areas:GovernmentBusinessEducationIndustrial design

H OW G RID C OMPUTING W ORKS

Super computer,Big mainframe

Idol timeIdol CPU

Idol CPU Idol timeSource: The Evolving Computing Model: Grid Computing Michael Teyssedre

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Virtual machine Virtual CPU

Idol timeIdol CPU

Idol CPU Idol timeSource: The Evolving Computing Model: Grid Computing Michael Teyssedre

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GridComputing

0% idol0% idol

0% idol 0% idolSource: The Evolving Computing Model: Grid Computing Michael Teyssedre

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G RID A RCHITECTURE

Autonomous, globally distributed computers/clusters

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W HAT IS A G RID ?

Many definitions exist in the literatureEarly defs: Foster and Kesselman, 1998A computational grid is a hardware and software

infrastructure that provides dependable, consistent,pervasive, and inexpensive access to high-endcomputational facilities

Kleinrock 1969:We will probably see the spread of computer utilities,

which, like present electric and telephone utilities, willservice individual homes and offices across the country.

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3- POINT CHECKLIST (F OSTER 2002)

1. Coordinates resources not subject tocentralized control

2. Uses standard, open, general purpose protocolsand interfaces3. Deliver nontrivial qualities of service

e.g., response time, throughput, availability,security

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D EFINITION

Grid computing is A distributed computing system

Where a group of computers are connectedTo create and work as one large virtualcomputing power, storage, database, application,and service

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D EFINITIONGrid computing

Allows a group of computers to share the systemsecurely andOptimizes their collective resources to meetrequired workloadsBy using open standards

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GRID COMPUTINGGrid computing is a form of distributed computingwhereby a "super and virtual computer" is composed of acluster of networked, loosely coupled computers, acting inconcert to perform very large tasks.

Grid computing (Foster and Kesselman, 1999) is agrowing technology that faci litates the executions of large-scale resource intensive applications ongeographically distributed computing resources.

Faci li tates flexible, secure, coordinated large scaleresource sharing among dynamic collections of individuals, institutions, and resource

Enable communities (virtual organizations ) to sharegeographical ly distributed resources as they pursuecommon goals

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A C OMPARISON

SERIAL

Fetch/Store

Compute

PARALLEL

Fetch/Store

Compute/

communicateCooperative game

GRID

Fetch/Store

Discovery of Resources

Interaction with remoteapplication

Authentication / Authorization

Security

Compute/Communicate

Etc

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D ISTRIBUTED COMPUTING VS . GRID

Grid is an evolution of distributed computingDynamic

Geographically independentBuilt around standardsInternet backbone

Distributed computing is an older termTypically built around proprietarysoftware and networkTightly couples systems/organization

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G RID T OPOLOGIES

Intragrid Local grid within an organisation

Trust based on personal contracts Extragrid

Resources of a consortium of organisationsconnected through a (Virtual) Private

Network Trust based on Business to Business

contracts Intergrid

Global sharing of resources through theinternet

Trust based on certification

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C OMPUTATIONAL G RID

A computational grid is a hardware and softwareinfras tructure that provides dependable, consistent ,

pervasive, and inexpensive access to high-endcomputational capabilities.

Example : Science Grid (US Department of Energy)

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D ATA G RID A data grid is a grid computing system that deals withdata the controlled sharing and management of large amounts of distributed data .

Data Grid is the storage component of a gridenvironment. Scientific and engineering applicationsrequire access to large amounts of data, and often thisdata is widely distributed. A data grid providesseamless access to the local or remote data required tocomplete compute intensive calculations.

Example :

Biomedical informatics Research Network (BIRN),the Southern California earthquake Center (SCEC).

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M ETHODS OF G RIDC OMPUTING

Distributed SupercomputingHigh-Throughput ComputingOn-Demand ComputingData-Intensive ComputingCollaborative ComputingLogistical Networking

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D ISTRIBUTED S UPERCOMPUTING

Combining multiple high-capacity resources ona computational grid into a single, virtualdistributed supercomputer.

Tackle problems that cannot be solved on asingle system.Examples: climate modeling, computationalchemistryChallenges include:

Scheduling scarce and expensive resourcesScalability of protocols and algorithmsMaintaining high levels of performance acrossheterogeneous systems

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H IGH -T HROUGHPUT COMPUTING

Uses the grid to schedule large numbers of loosely coupled or independent tasks, with thegoal of putting unused processor cycles towork.Schedule large numbers of independent tasksGoal: exploit unused CPU cycles (e.g., fromidle workstations)Unlike distributed computing, tasks looselycoupledExamples: parameter studies, cryptographicproblems

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TECHNOLOGYTRENDS

Storage, Networks, and Computing power, doubles or,more or less equivalently, halves in price in around 12,9, and 18 months, respectively

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GRID ARCHITECTURE

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GRID ARCHITECTURE .

At the lowest level, the fabric , we have the physical

devices or resources that Grid users want to share

and access, including computers, storage systems,

catalogs, networks, and various forms of sensors.

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The resource layer contains protocols that exploit communication

and authentication protocols to enable the secure initiation,

monitoring, and control of resource-sharing operations.

Running the same program on different computer systems

depends on resource layer protocols.The Globus Toolkit is a commonly used source of connectivity

and resource protocols and APIs.

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The collective layer contains protocols, services, and APIs thatimplement interactions across collections of resources.

Because they combine and exploit components from therelatively narrower resource and connectivity layers, thecomponents of the collective layer can implement a wide varietyof tasks without requiring new resource-layer components.

Examples of collective services includedirectory and brokering services for resource discovery and

allocation;monitoring and diagnostic services;data replication services; andmembership and policy services for keeping track of who in

a community is allowed to access resources.

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At the top of any Grid system are the user applications, which are

constructed in terms of, and call on, the components in any otherlayer.For example, a high-energy physics analysis application that needs

to execute several thousands of independent tasks, each taking asinput some set of files containing events, might proceed by

obtaining necessary authentication credentials ;querying an information system and replica catalog to determine

availability of services;submitting requests to appropriate computers, storage systems, and

networks to initiate computations, move data, and so forth (resourceprotocols); and

monitoring the progress of the various computations and datatransfers, notifying the user when all are completed, and detecting andresponding to failure conditions (resource protocols).


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AUTHENTICATION, AUTHORIZATION AND POLICY

In Grid environments, the situation is more complex. The distinction

between client and server tends to disappear, because an individual

resource can act as a server one moment (as it receives a request)

and as a client at another (as it issues requests to other resources).

Managing that kind of transaction turns out to have a number of interesting

requirements, such as:

Single sign-on

Mapping to local security mechanisms

Delegation

Community authorization and policy

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Single sign-on: A single computation may entail access to many resources, but

requiring a user to re-authenticate on each occasion (by, e.g., typing

in a password) is impractical and generally unacceptable.

Instead, a user should be able to authenticate once and then

assign to the computation the right to operate on his or her behalf,

typically for a specified period.

This capability is achieved through the creation of a proxy

credential.

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In Figure, the program run by the user (the user proxy)

uses a proxy credential to authenticate at two different

sites.

These services handle requests to create new processes.

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Mapping to local security mechanisms:Different sites may use different local security solutions, such as

Kerberos and Unix. A Grid security infrastructure needs to map to these local solutions at

each site, so that local operations can proceed with appropriateprivileges.

In Figure, processes execute under a local ID and, at site A, are assigned a

Kerberos ticket, a credential used by the Kerberos authentication system to

keep track of requests.

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Delegation:

The creation of a proxy credential is a form of delegation, anoperation of fundamental importance in Grid environments.

A computation that spans many resources creates sub-computations(subsidiary computations) that may themselves generate requests toother resources and services, perhaps creating additional sub-computations, and so on.


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In Figure, the two sub-computations created at sites A and B bothcommunicate with each other and access files at site C. Authentication operations and hence further delegated credentials

are involved at each stage, as resources determine whether to grantrequests and computations determine whether resources aretrustworthy.

The further these delegated credentials are disseminated, thegreater the risk that they will be acquired and misused by anadversary. These delegation operations and the credentials that enablethem must be carefully managed.

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Community authorization and policy: In a large community, the policies that govern who can use which

resources for what purpose cannot be based directly on individual

identity.

It is infeasible for each resource to keep track of community

membership and privileges.

Instead, resources (and users) need to be able to express policies in

terms of other criteria, such as group membership, which can be

identified with a cryptographic credential issued by a trusted third

party.


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In the scenario depicted in Figure, the file server at site C must know

explicitly whether the user is allowed to access a particular file. A

community authorization system allows this policy decision to be

delegated to a community representative.

G RID M IDDLEWAREGrids are typically managed by grid ware -

a special type of middleware that enable sharing andmanage grid components based on user requirementsand resource attributes (e.g., capacity, performance)Software that connects other software components orapplications to provide the following functions:

Run applications on suitable available resources Brokering, SchedulingProvide uniform, high-level access to resources Semantic interfaces Web Services, Service Oriented Architectures

Address inter-domain issues of security, policy, etc.

Federated IdentitiesProvide application-level statusmonitoring and control

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M IDDLEWARES

Globus chicago UnivCondor Wisconsin Univ High throughputcomputingLegion Virginia Univ virtual workspaces-collaborative computingIBP Internet back pane Tennesse Univ logistical networkingNetSolve solving scientific problems inheterogeneous env high throughput & dataintensive

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G RID U SERSMany levels of users

Grid developersTool developers

Application developersEnd usersSystem administrators

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S OME G RID CHALLENGESData movementData replication

Resource managementJob submission

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SOME OF THE M AJOR GRID P ROJECTS

Name URL/Sponsor Focus

EuroGrid, GridInteroperability(GRIP)

eurogrid.orgEuropean Union

Create tech for remote access to super comp resources & simulation codes; inGRIP, integrate with Globus Toolkit

Fusion Collaboratory fusiongrid.orgDOE Off. Science

Create a national computationalcollaboratory for fusion research

Globus Project globus.orgDARPA, DOE,NSF, NASA, Msoft

Research on Grid technologies;development and support of GlobusToolkit; application and deployment

GridLab gridlab.orgEuropean Union

Grid technologies and applications

GridPP gridpp.ac.ukU.K. eScience

Create & apply an operational grid within theU.K. for particle physics research

Grid ResearchIntegration Dev. &Support Center

grids-center.orgNSF

Integration, deployment, support of the NSFMiddleware Infrastructure for research &education

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Grid in India- GARUDA

GARUDA is India's Grid Computinginitiative connecting 17 cities across thecountry.The 45 participating institutes in thisnationwide project include all the IITs andC-DAC centers and other major institutesin India.

S IMULATION TOOLS

GridSim job schedulingSimGrid single client multiserverschedulingBricks schedulingGangSim- Ganglia VOOptoSim Data Grid SimulationsG3S Grid Security services Simulator security services

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GT-OGSA Grid Service Infrastructure

OGSI Spec Implementation Security Infrastructure

System-Level Services

Base Services

User-Defined Services

Grid Service Container

Hosting Environment

Web Service Engine

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THE SPECIFICATION DEFINES HOW E NTITIES CAN C REATE , D ISCOVER AND INTERACT WITH A GRID SERVICE

Servicedata

element

Servicedata

element

Servicedata

element

Service Implementation

GridService(required) other interfaces (optional) Optional:

- Service creation- Notification- Registration- Service Groups

+ application-specific interfaces

Required:- Introspection

(service data)- Explicit destruction- Soft-state lifetime

GT3 Core: OGSI Specification

Includes 0 or more Grid Service Handles (GSHs)Includes 0 or more Grid Service References (GSRs)

Service locator

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Client

A S ERVICE CREATION SCENARIO *

Registry

* The scenarios in this presentation are offered as examples and are not prescriptive

1. From a knownregistry, the clientdiscovers a factory

by querying theService data of theregistry

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Client

Registry

2. The client calls thecreateServiceoperation on thefactory

Factory



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Client

Registry




Factory

Service

3. The factorycreates aservice

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Client

Registry


Factory

Service


4. The factoryreturns a locator



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Client

Registry


Factory

Service



5. The client and service interact



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NotificationSink

A N OTIFICATION SCENARIO

1. NotificationSink calls thesubscribe operation on

NotificationSource

NotificationSource 7

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Base Services



Hosting Environment

Web Service Engine

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GT3 C ORE : S YSTEM LEVEL SERVICES

General-purpose services that facilitate the use of GridServices in production environmentsThe 3.0 distribution includes the following System-Levelservices:

An Administration Service A Logging Service A Management Service

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Base Services



Hosting Environment

Web Service Engine87

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GT3 C ORE : G RID S ERVICE C ONTAINER

Interface Layer

Transport Layer

Implementation Layer

Layers in the Web Services Model

OGSI Spec is here

Transport/BindingLayer (GT3 supportsSOAP over HTTP)

Container is here

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Base Services



Hosting Environment

Web Service Engine

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GT3 C ORE : H OSTING E NVIRONMENT

GT3 currently offers support for four JavaHosting Environments:

EmbeddedStandaloneServletEJB

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GT3 C ORE : V IRTUAL H OSTING E NVIRONMENTF RAMEWORK

Virtual Hosting allows grid services to bedistributed across several remote containers

Useful in implementing solutions for problemscommon to distributed computing

Load balancingUser account sandboxing

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A S ERVICE CREATION S CENARIOILLUSTRATING REDIRECTION IN V IRTUAL H OSTING

Client

Registry

Router

HE Starter

1. Froma knownregistry,the clientretrievesa factorylocator

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A S ERVICE CREATION SCENARIOILLUSTRATING R EDIRECTION IN V IRTUAL H OSTING

Client

Registry

Router 1. Froma knownregistry,the clientretrievesa factorylocator

HE Starter 2. The routerintercepts thecreateServicecall on thefactory

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Client

Registry

Router 1. Froma knownregistry,the clientretrievesa factorylocator

2. The routerintercepts thecreateServicecall on thefactory

HE Starter

3. The router passes the createServicerequest to the Host Env Starter

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A S ERVICE CREATION SCENARIOILLUSTRATING R EDIRECTION IN V IRTUAL H OSTING

Client

Registry

Router

Service



HE Starter


4.The HEStartercreatesa newHost Envas wellas theservice

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Client

Registry

Router

Service



HE Starter


4.The HEStartercreatesa newHost Envas wellas theservice

5. The router returnsa service locator

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Client

GRAM J OB SUBMISSION SCENARIO

IndexService

1. From an indexservice, the clientchooses anMMJFS

2. The client calls thecreateServiceoperation on thefactory,supplyingRSL

MMJFS

MJS

3. The factorycreates aManaged JobService

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Client


IndexService



MMJFS

MJS



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Client


IndexService



MMJFS

MJS



5. The client subscribes tothe MJS status SDE andretrieves output

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GT3 B ASE : I NFORMATION SERVICES

Index Service as Caching AggregatorCaches service data from other grid services

Index Service as Provider FrameworkServes as a host for service data providers that liveoutside of a grid service to publish data

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GT3 B ASE : RELIABLE F ILE TRANSFER

Reliably performs a third party transfer between two GridFTPserversOGSI-compliant service exposing GridFTP control channelfunctionalityRecoverable Grid Service

Automatically restarts interrupted transfers from the last checkpoint

Progress and Restart Monitoring

GridFTPServer 1

GridFTPServer 2

RFT

JDBC

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Base Services



Hosting Environment

Web Service Engine

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GT3 U SER -D EFINED S ERVICES

GT3 can be viewed as a Grid Service DevelopmentKit that includes:

Primitives designed to ease the task of building OGSI-Compliant ServicesPrimitives for provisioning securityBase services that provide an infrastructure with whichto build higher-level services

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GT3 U SER -D EFINED S ERVICES (CONT .)

ANT

User source files

GT3 Build Files

User Build File

GridServiceexecutablefiles

(Diagram inspired byBorja Sotomayorsexcellent tutorial on GT3)

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F UTURE D IRECTIONS OF GT

Standardization of container modelDevelopment of lightweight container/api

Adding rich support for queriesFurther refinements of Base Service designsPushing on standardizing at a higher level than OGSI

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the grid introduction

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