A Framework for Collaborative Distributed Simulation over the Grid

1
A Framework for Collaborative Distributed
Simulation over the Grid

• Stephen John Turner
• Parallel Distributed Computing Centre
• Nanyang Technological University
• Singapore

2
Outline

• Background
• Distributed Simulation
• Grid Computing
• Motivation
• Research Challenges
• HLA-based Distributed Simulation
• Grid Services and Service Discovery
• Load Management System
• Grid Enabled HLA/RTI
• Conclusions

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Distributed Simulation

• Provides a way of linking simulation components
  (federates) of various types at possibly
  different locations to create a common virtual
  environment (federation)

4
Example Application Areas

• Battlefield Simulation
• Linking different types of forces at multiple
  physical locations to create a realistic and
  complex virtual world
• Supply Chain Simulation
• Managing material and information flow, from
  manufacturers through distributors to customers
• Air Traffic Control
• Simulating airports and airspace sectors to
  provide faster than real-time simulation for
  what-if analysis
• Multi-player Internet Games
• Involving massive multi-player (10,000) virtual
  world

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High Level Architecture
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High Level Architecture

• Features of High Level Architecture
• Each federate has a simulation object model (SOM)
  defining the data to be shared with other
  federates allowing reuse in different federations
• The federation (set of federates) has a common
  federation object model (FOM)
• HLA supports distributed simulations linking the
  federates of a federation over a LAN or the
  Internet
• Time Management can be used to ensure the correct
  ordering of events
• HLA is an IEEE (1516) and OMG standard

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Grid Computing

• Grid technology is the next step in the evolution
  of computing, enabling new forms of collaboration
  through the seamless sharing of distributed
  computing and data resources

Communities can share geographically distributed
resources for their common purpose
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Grid Computing
Web Services Grid Services OGSA OGSI Globus
Toolkit
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Motivation

• Collaborative Simulation Development
• The development of complex simulations usually
  requires collaborative effort from analysts with
  different domain knowledge and expertise,
  possibly at different locations
• Sharing of Computing Resources
• Simulation systems often require huge computing
  resources and the participants in the simulation
  and/or data sets required may also be
  geographically distributed

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Motivation

• HLA-based Distributed Simulation on the Grid
• HLA defines a standard for reuse and
  interoperability
• Grid technologies enable collaboration and the
  use of distributed computing resources

• Collaborative
• Distributed
• Complex Multi-dimensional

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Simulation Life Cycle
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Research Challenges

• Service/Model Discovery
• Based on requirements, suitable component
  models are selected to form an overall simulation
• Research Issues
• How are simulation models registered as grid
  services
• How are simulation models discovered?
• How are the interfaces defined?
• Are the simulation models HLA compliant?
• Do they conform to any standard reference models
  (e.g. HLA-CSPIF)?

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Research Challenges

• Service/Model Composition
• Checking semantic interoperability between
  individual component simulation models from
  different sources
• Research Issues
• Can the output of one simulation model feed into
  the input of another?
• How is the work flow of the configuration
  described?
• What are the mechanisms for verifying the
  correctness of the simulation?

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Research Challenges

• Security
• Simulation partners should be allowed to specify
  selective access to their simulation models
• Research Issues
• Does a user have access to a particular
  simulation model or data?
• Can a user selectively share sensitive data with
  different partners?
• Does the simulation model originate from a
  trusted partner?
• Must the model be executed on a particular
  resource?

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Research Challenges

• Execution
• Simulation partners may obtain computing
  resources from the Grid to supplement their needs
• Research Issues
• How can the different simulation runs be
  partitioned onto the available computing
  resources?
• What mechanisms should be used for scheduling and
  load management of simulations on the Grid?
• What kind of fault tolerance mechanisms are
  required?

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Simulation Life Cycle
Semantic Interfaces
Resource Managemt
Workflow
Policies
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HLA-based Distributed Simulation

• Discovery and Composition of Models

• Discovery of Resources

• Management of Simulation Execution

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Grid Services and Service Discovery

• Query Index Service for RTI Service handle for
  federation
• Create RtiExec if necessary and get endpoint used
  by RtiExec
• Query Index Service for Federate Factory Service
  handle
• Create Federate Service and Federate Process
• Federate Processes join federation

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Grid Services and Service Discovery

• Query Index Service for Federate Factory Service
  handle
• Create Federate Service and Federate Process
• 4a.Federate Service can query Index Service for
  RtiExec endpoint
• 5. Federate Processes join federation

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Load Management System

• Use Grid software for
• Authentication,
• Resource Discovery, Allocation Monitoring, and
• Facilitating Federate Migration

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Load Management System
Resource Discovery Allocation Monitoring
Globus
Run Time Infrastructure
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SimKernel

• Simulation code extended with two interfaces
• One for communicating with Runtime
  Infrastructure (RTI)
• One for communicating with Load Management
  System (LMS)

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SimKernel
Design
Implementation
Execution
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Federate

• Each federate contains two threads (SimKernel)
  and load management thread (LMClient)
• SimKernel processes simulation events as defined
  by the user and communicates with RTI
• LMClient works with Load Manager (LM) to perform
  federate migration
• receive instruction from LM
• stop SimKernel
• get SimKernel execution state
• transfer SimKernel configuration and execution
  state

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Load Manager

• Load Manager
• Constantly monitors and collects load information
  of each individual participating computing node
• Runs load balancing algorithm to determine which
  federate should migrate from which host to which
  destination
• Communicates with the LMClients at both the
  source and destination hosts until migration
  succeeds

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Migration Approaches

• Federation wide synchronization

federate
federate
federate
Federation-Wide Save
Federate Migration
Federation-Wide Restore
Costly Operation!
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Migration Approaches

• Communication among federates
• Messages may be lost in transit during migration

publish
subscribe
msg
network
resign
join
subscribe
subscribe
unsubscribe
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Our Approach

• We developed an algorithm aiming to
• Provide transparent migration, and
• Minimize the migration overhead
• Run two instances of the migrating federate until
  event integrity is ensured
• No synchronization or FTP communication is
  required
• Implementation is specific to federates based on
  SimKernel

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Federate Migration
migrating federate
resignFederationExec
sendOutgoingEvents
returnStatus
suspend
missingMsg
receivedInteraction
flushQueueRequest
receivedInteraction
collect
returnStatus
LMClient _at_source
Req_migrate
migrationSucceeded
notifyMissingMsg
returnInformation
returnInformation
requestInformation
RTI
Load Manager
pub/sub Interaction
flushQueueRequest
receivedInteraction
joinFederation
Req_migrate
getMsgCount
recvMsgCount
LMClient _at_destination
resume
restore
new
restarting federate
Latency period
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Experimental Results
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Grid Enabled HLA/RTI
Client 1
Client 1
Grid Network


Client n
Client n
Federation 1
Federation m
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Design
Grid Services indexing, discovery, resource
management, monitoring services
Grid Services
Globus
Proxy
Simulation Code
Proxies Federates
Grid-enabled API
HLA API
Grid-enabled HLA API
HLA API
Globus
RTI on LAN
Globus
Grid Network
Client
Resource
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Discussion

• Advantages
• Avoids some firewall issues as client
  communicates with proxy via grid services
• Client application code can run on heterogenous
  platforms
• Provides easy migration of client code, proxy
  does not need to be migrated
• Disadvantages
• Overhead of communication as all simulation
  events use grid services

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Conclusions

• Work Done
• Developed a simple prototype using Globus for
  resource discovery, allocation and federate
  deployment (DS-RT 02)
• Developed SimKernel framework to allow modeler to
  concentrate on the simulation, rather than
  implementation (DS-RT 03)
• Developed a federate migration protocol without
  using federation synchronization (ICCS 04)
• Developed Grid Service and Service Discovery
  Framework (submitted to DS-RT 04)

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Conclusions

• Future Work
• Service/model discovery
• Service/model composition
• Grid workflow languages
• Grid enabled HLA/RTI
• Performance measurement
• Alternative communication mechanisms
• Migration and fault tolerance
• Integration of sub-projects
• Convert to GT4 (WS-RF)

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Thank you for your attention!
While the HLA defines a standard for the
construction of large-scale distributed
simulations, Grid technologies enable
collaboration and the use of distributed
computing resources, while also facilitating
access to geographically distributed data sets

• Questions Answers