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Large Scale Emulation Mobility in ProActive. OASIS Team, INRIA Sophia-Antipolis/I3S CNRS, Univ. Nice Christian Delbé Data Grid Explorer 15/09/03. Oasis Team. O bjets A ctifs, S émantique, I nternet et S écurité Common Project : INRIA, CNRS-I3S, UNSA Created in June 1999 - PowerPoint PPT Presentation
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OASIS Team, INRIA Sophia-Antipolis/I3S CNRS, Univ. Nice
Christian Delbé
Data Grid Explorer15/09/03
Large Scale EmulationMobility in ProActive
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Oasis Team
Objets Actifs, Sémantique, Internet et Sécurité
Common Project : INRIA, CNRS-I3S, UNSA
Created in June 1999
Directed by Isabelle Attali (isabelle.attali@sophia.inria.fr)
Methods and tools for analysis, construction, validation and maintenance of distributed applications
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Java API+Tools for Parallel, Distributed ComputingMain features :
Remotely accessible Objects (RMI, JINI, UDDI)Asynchronous Communications with synchronization
(automatic futures) Group Communications, Migration (mobile computations)XML Deployment DescriptorsInterfaced with various protocols (rsh,ssh,LSF,Globus,
….SOAP)Visualization and monitoring: IC2D
Requirements : JDK (>= 1.3)
ProActive
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Suited for the Grid (large and heterogeneous systems, high latency,…)
On going large scale SPMD applications environment :SPMD API based on group communicationsLoad balancing based on migrationFault toleranceDeployment with XML descriptors
ProActive and the Grid
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Recent experiment : Jem3D In cooperation with CAIMAN project (INRIA Sophia)Solve 3D Maxwell’s equations in electromagnetism
2 main tests :
On a 64 processors cluster
On desktop machines LAN: 252 processors
No more available resources...
0
100
200
300
400
500
600
700
800
900
0 10 20 30 40 50 60 70
# of processors
Du
rati
on
(sec)
21*21*21
31*31*31
43*43*43
55*55*55
81*81*81
97*97*97
113*113*113
121*121*121
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Objectives with Data Grid Explorer
More resources to confirm scalability
Develop and test new features new protocols integrationsecurity testingfault tolerance ...
Need to validate many models load balancingmigration discussed later ...
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Migration of Active Objects
Generic mechanism : any active object can migrate
No modification of source code nor bytecode
Weak migration : migration is initiated by the object itself
Automatic and transparent forwarding of: requests (remote references remain valid) replies (its previous queries will be fulfilled)
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Localization of Active Objects
Two approaches
distributed (forwarders)
When it migrates, an object leaves a forwarder which leads to its new location
centralized (location server)
When it migrates, an object informs a location server of its new location
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S
Host A
A
Host B Host C Host D
S : SourceA : AgentF : Forwarder
reference
Localization using forwarders
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S
Host A
Host B
A
Host C Host D
Request
forwarding forwardingF AF
Migration Migration
S : SourceA : AgentF : Forwarder
reference
Localization using forwarders
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Host B
F
Host C
A
Host D
Update location
F
S
Host A S : SourceA : AgentF : Forwarder
reference
Localization using forwarders
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Host B
F
Host C
A
Host D
F
S
Host A
Next communications with the new reference
S : SourceA : AgentF : Forwarder
reference
Localization using forwarders
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Localization of Active Objects
Two approaches
distributed (forwarders)
When it migrates, an object leaves a forwarder which leads to its new location
centralized (location server)
When it migrates, an object informs a location server of its new location
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S
Host A
A
Host B Host C Host D
S : SourceA : Agent
referenceServer
Localization using server
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S
Host A
Host B
A
Host C Host D
S : SourceA : Agent
reference
Migration
Server
Update
Localization using server
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S
Host A
Host B Host C Host D
S : SourceA : Agent
reference
MigrationA
Server
Update
Localization using server
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S
Host A
Host B Host C Host D
S : SourceA : Agent
reference
Message
A
Server
Failed
Localization using server
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S
Host A
Host B Host C Host D
S : SourceA : Agent
reference
A
ServerAsk for new
location
Answer
Message
Localization using server
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Provide an hybrid protocol : – use forwarders for limited period – if chain is broken, use localization server – a
Parameterized by two values : – TTL (Time To Live) : after TTL, forwarder is garbage collected – TTU (Time To Update) : a mobile object update his location
every TTU
Hybrid protocol : TTL-TTU
Forwarders are better on a MAN …
but resources consuming !
Server is better on a LAN …
but time consuming !
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First Step : validating models
Modeling using Markov chains for predicting response time (Fabrice Huet - 2003)– validate model with simulations and experiments
But hypothesis cannot be fulfilled !– Infinite number of hosts, homogeneous latency,…
Determine impact of hypothesis variation
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Second Step : Determining TTL and TTU
No model of the hybrid protocol (but some insights from previous models)
Determine impact of TTL-TTU values in given conditions
Choose best values for a minimal response time– before deployment– during execution
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Conclusion
Our objectives are : – Confirm scalability– Test new features– Validate models, localization TTL-TTU
Our requirements are :– a Java runtime (>=1.3)– ProActive packages
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