Towards a Comprehensive Computational Experimentation ...dddas.org/iccs2005/talks/chaturvedi.pdfTEAM...

Towards a Comprehensive Computational Experimentation Environment: Dynamic Data

Driven Approach

Alok Chaturvedi, PIPurdue Homeland Security InstitutePurdue Homeland Security Institute

Purdue UniversityPurdue University

NSF ITR Grant # CNS-0325846, Indiana 21st Century R&T Fund, JPEOCBD, JFCOM J-9

Outline• Background• Building the Synthetic Environment

– Society of Simulations– Configuration– Integration

• Calibration• Validation• Experiment• Q&A

Support & Partnerships:

National Science FoundationIndiana State 21st Century Fund

Department of DefenseIndiana State Department of Health

Purdue University (PHSI, CRI, Discovery Park, Krannert School of

Management, School of Liberal Arts, College of Engineering, and Department of Computer Sciences)

Simulex Inc.

TEAM• PI: Alok Chaturvedi

• Co-PIs: Roko Aliprantis, Steve Beaudion, Jerry Busemeyer, Daniel Dolk, Jay Gore, Anant Grama, Chris Hoffman, Elias Houstis, Rich Linton, Shailendra Mehta, Suresh Mittal, Jenna Rickus, Vernon Rego, Ahmed Sameh, and Rusi Taleyarkhan.

• Collaborators: Eric Dietz, Jari Niemi, Chih-hui Hsieh, Teja Bhatt, Angela Mellema, Beth Naylor, Cliff Wojtalewicz, Rashmi Chaturvedi, Chee Foong, Midh Mulpuri, David Lengachar, Yeeling Tham, Steve Mallema, Johnson Char

• State of Indiana• Purdue University, West Lafayette, IN, USA • Naval Postgraduate School, Monterey, CA, USA• Indiana University, Bloomington, IN, USA• Simulex Inc.

Computational Experimentation Paradigm

WORLD

Observations

BehaviorEstimation

SyntheticEnvironment

Theory+DataValidation

Assumptions Model

Observations

Theories ofPhenomena

Validation

ConditionalPredictions

AssumptionsModel

SyntheticObservations

Theories ofPhenomena

Validation

ConditionalPredictions

Analytical &Observational

ComputationalExperimentationDomain Models

& Theories

Human

Issues in Computational Experimentation..

• High fidelity computational experimentation requires deep understanding of:

– The underlying Science -- physical, social, computational, life sciences, humanities

– The computational models • Mathematical equations• Equation free• Differential equations vs Difference equations• Baseball or basketball

– Representation paradigms -- Common (?) Uniform (?) Diverse (?)

– Presentations -- digital art (?) semantics (?) ontology (?) storytelling (?) entertaining (appeals to emotions)

– Platform HPC (?) Peer-2-Peer (Xbox, PS 2/3, PDA)– Business models (?)

Outline• Simulations Composed of Simulations• A Society of Simulations: the Concept

– Defining a Society of Simulations– The Components of a Society

• Fire Evacuation Society: a Case Study– The Goal– The Heterogeneous Members– Bridging the Members– Resulting Storylines

• Future Work– Further Development & Lessons Learned– Other Applications

Society of SimulationsA Definition

society:1. A group of human beings bound together by shared institutions and

culture.2. An association of people with mutual aims or interests.

• Each simulation is an autonomous member of the society.• Members operate independently on their own understanding of

reality.• Members share overlapping portions of their models of reality.• Members of a society cooperate to achieve their goals.• The fulfillment of the societal goals emerge from member actions.

Society of SimulationsExample: Fire Evacuation Society

• Goal:Model evacuation and health issues to address safety concerns regarding building fires.

• Members: Fire simulation & synthetic human simulations.

Fire Sim.

Human Sim.Human Sim.Human Sim.

building,smoke,temperature

A Society of SimulationsShared Reality

Portions of reality modeled by multiple members.• A shared and distributable data space.• Data is pulled by the members

on demand.• Decouples publishing & subscribing.

All interactions occur within the shared reality.• Time coordination by waiting for unavailable data.• Allows for multiple spatial & temporal granularities of access.

CD

BA

sharedreality

building,smoke,temperature

Fire Sim.

Human Sim.Human Sim.Human Sim.

A Society of SimulationsThe Bridging Component

Links between members and shared reality.• Grabs the data from shared reality that influences its member &

writes data the member produces.• Member-specific ontology translation.• Translates, scales, filters, & interpolates data.• Can trigger a series of actions in the member.• (optimistic) Initiates a roll back when significant data in the

member’s past is available.

Fire Sim.

Human Sim.Human Sim.Human Sim.building,

smoke,temperature

A Society of SimulationsThe Member Component

Autonomous & specialized models.• Developed independently.• Can be event-based or continuous-time,

optimistic or conservative.• Reusable in multiple societies.• Sense shared data (on-demand.)• Interpret data relative to member-specific semantics.• All interactions with members is through shared reality.

Fire Sim.

Human Sim.Human Sim.Human Sim.building,

smoke,temperature

Shared Reality Model

Shared Reality Engine

Fire Evacuation SocietyMembers in General

Fire Simulation:• FDS (Fire Dynamics Simulator,

from NIST.)• Optimistic

(checkpoint / restart.)• Continuous-time,

fluid dynamics.• Fine-grained in space

and time.• Time-consuming

(1 minute required to simulate each second.)

Human Simulation:• Includes physiology, mobility,

familial relationships, & some decision-making.

• Discrete-event.• Coarse-grained.• Real-time.• Conservative

(follows a leader.)

Fire Evacuation Society

• Children playing with matches.

• Kitchen fires.

Integrated Science Based Modeling

Bridged Science and Agent based models• Fire Model (NIST’s FDS)• Structure Model (LS Dyna)• Agent based Model (SEAS)• Physiology Model

• Safer building• Virtual Ground Zero• Prognosis for Real-time courses of

action planning

Large Evacuation Model

SEAS Parallel World Architecture

JINI Network Technology Services

RMID Services

Discovery Services

Transaction Services

Output Space

Output Space

Agent Space

Agent Space

Input Space

Input Space

Parallel World 3

Worker Agents

Proxy Service

Output Space

Output Space

Agent Space

Agent Space

Input Space

Input Space

Parallel World 2

Worker Agents

Proxy Service

Output Space

Output Space

Agent Space

Agent Space

Input Space

Input Space

Parallel World 1

Worker Agents

Proxy Service

Parallel World Coordination Space

Parallel World Coordination Space

Action Permutation

Algorithm

Exit Effect 1

• All 5 exits open: 4 deaths

Exit Effect 2• Top exit closed: 18 deaths

Exit Effect 3

• Bottom exit closed: 9 deaths

Exit Effect 4

• Side exits closed: 5 deaths

Exit Effect 5

• Top & bottom exits closed: 28 deaths

SEAS NRT

JSAF

SimBridge

RTI

STEALTH3D Visualization

SEAS VIS

SimBridge

Manf & Serv

Energy

Labor

Information

Finance

Infrastructure

Emergent Network Model

Consumer

EmID

S

S

S

S

S

S

E1

E4

E3

E2

E5

E6

ONA (Operational Net Assessment)

Effects

SPorts to receive messages Channels to send messages Sensors to sense messages

Modeling ExperimentationIntegration Validation VisualizationAnalysis

MRE ToolkitMRE ToolkitMRE Toolkit 6

Science BasedModels

Process/ResponseModels

Threat & RiskModels

Chemical & Bio.Models

Nuclear & Rad.Models

Cyber SecurityModels

Effects BasedModels

Nodal AnalysisModels

GISData

EconomicData

CapabilityData

LessonsLearned

ONAData

SurveillanceData

SensorData

IntelligenceData

4

High Performance ComputingDynamic Data Driven Applications

Storage, Networking, PlatformSecurity

2Cyber InfrastructureCyber InfrastructureCyber Infrastructure

OrganizationalInfrastructure

SocialEconomy

Process

Healthcare

Mixed Reality EnvironmentMixed Reality EnvironmentMixed Reality Environment

ComputationalExperimentation

Laboratory

LivingLaboratories

Mixed Reality Environment

Scaling

Validation

1

MuscatatuckE-Stadium

Borman HignwayDRCC

State of Indiana

Regenstrief Healthcare

Sensor/Instrument

Forensics

Enforcement

Intelligence

Prevention

NRP/NIMS

Technology

Processes

Training

Preparedness

HealthCare

Logistics

Organizations

Net Assessment

Response Network

5

3

Knowledge Portal-Net Assessment-Red View-Blue View-Political, Military, Social, Economic, Information, Infrastructure Summaries

Knowledge Base ONADatabase

-Effects-Nodes-Actions-Consequences-Links-Rationale

Concept

Development

Living Lab Experimentation

Computational Experimentation

Doctrine Development

Training & Education using Mixed Reality

Mixed Reality Experimentation

(Concept Scaling)

War Games (Concept

Assessment)

Concept ValidationValidated Concept

Concept Prototyping

NRP (Concept Institutionalization)

NRP (Concept Institutionalization)

Validated Scalable Concepts

Validated Scalable Concepts

Refine ConceptRefine

Concept

Refine ConceptRefine

Concept

SEAS WORLD

Bombing at the building level

SEAS CountryPopulation & Social Networks

Near Real Time Reactions and behaviors

SEAS City

SEAS City Block

SEAS BuildingSEAS BUILDING

SEAS CITYJSAF CITY

SimBridge

Agent Routing andAgent Sensing Algorithms

World Opinion

SEAS CITY BLOCK

Multi-layer, Multi-Granularity

Cities

Countries

Regions

World

Liberal View

Cultural ViewCross Cultural

View

Social Network

Realist ViewKeynsian View

X

X

X

X

X

X

X

X

X

X

X

Plurality of Thought

SEAS DDDAS Development Process

Universities

Synthetic Environment

DomainTheories

Experimental/Archived Data

Current/BestPractices Data

Lessons Learned

DoctrinalInformation

Peer-review(Validation,

Verification &Accreditation)

Expert &PractitionerValidation

VisualizationLocal CW

Province CW

National CWGlobal CW

ModelOutput

Inputs

Proprietary Data

OtherAgencies

Towards an Ecosystem

Models Bull pen

Compare theoretical behavior &

actual behavior

Accreditation for use

Open Source World

Model repository

Environment

TeamUmpire

Adversary

Behaviorally accurate, community developed, experimentally calibrated, scientifically validated, professionally verified

Tale of Two WorldsFirewall Hypothesis

Open Source World

Hidden World

Attrition World

Theories

Controls

FilterFilter

Simbridge

Synthetic Environment for Analysis and Simulation

SEAS

Crowd Formation

Coordinated Attack Simultaneous Attack

Crowd Formation

Demonstration - Counter DemonstrationDemonstration

Crowd Formation

Refugees -- Hotel Rwanda

Crowd Formation

Friday Prayer Opinion Formation

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Conclusions• Society of simulations is an effective method to link

heterogeneous simulations.– Consumers translate & interpret data specific to their needs.

• Capable of being distributed for scalable performance.– Scalable wrt. data size

pull-based, on-demand, sensing.– Scalable wrt. synchronization

asynchronous interactions, decoupling of consumer’s access patterns from producer’s.

Questions / Comments?

Shared Reality

World Region Country Province

SEAS - VIS

City Block

City

City Block Incident

City

JSAF

SEAS - NRT

GeographiesEntities