Evaluation of Net-centric Command & Control (C · Manual Data Gathering Automated Data Gathering Integrated into Net-Centric Applications APL GIG Testbed Mini-GIG Distributed, Integrated

Evaluation of Net-centric Command & Control (C2)

Steven L. Forsythe, Ph.D.

Paul North

2

Purpose To describe APL’s approach for evaluating Command and Control (C2) in a hybrid Net-centric environment

Critical Challenges:

Evaluating C2

Evaluating the impact of net-centricity on force effectiveness

3

Specific Objectives

1. Evaluate the extent to which:Net-centricity improves Command and Control (C2) and related applicationsThe GIG infrastructure and Core Services will effectively and efficiently support C2 and related applications

2. In order to achieve objective #1, we need to:Develop a theoretical framework for C2Methodology for net-centric experimentationInfrastructure for net-centric experimentationImproved tools for automated C2 data gathering and analysis

4

Methodology for Net-centric Experimentation• Multi-Resolution Methodology For Net-Centric

Experimentation• Combine models with different levels of resolution to achieve the

needed insights• Constructive, Virtual & Live environments enable trade-offs between

cost, repeatability, and fidelity• Appropriate C2 measures:

• Measures of Performance (MOP)• Measures of Effectiveness (MOE)• Measures of Force Effectiveness (MOFE)

Experiment___________________________________________________

Conjecture____________________________________________________

Design

Analysis

Design Design

Analysis

• Supports the iterative nature of experimentation

5

Multi-resolution Modeling Evaluation Framework (MRMEF)

C2 ServiceServicesC2 ServiceServicesC2 ServiceServices

C2 Gaps and Requirements

MRM Evaluation Framework

GIG Components

C2 Evaluation Results“As Is” C2 Evaluation

Sim

ulat

ion/

Exe

rcis

e En

viro

nmen

t

Net-Centric C2 Evaluation

Operational Environment (OE)

Scenario within OE

Operational Mission

Operational Environment (OE)

Scenario within OE

Operational Mission

Analysis• Compare Net-Centric to “As-Is”• Analyze technical & cost data• Generate recommendations

Services& APPS

“As Is” (Baseline)Net-Centric: Portfolio 1

MOPs:Measures of Performancee.g. Service Latency

Effectiveness Values

MOEs: Measures of Effectivenesse.g. Planning time, quality

MOFEs:Measures of Force Effectivenesse.g. # Terrorist sites destroyed

Net-Centric: Portfolio n

“As Is” (Baseline)Net-Centric: Portfolio 1Net-Centric: Portfolio 1











ScenarioMission Thread

C2 Processes

EffectivenessAttributes

(MOPs, MOEs, MOFEs)

Physical Layer

Data Link Layer

Network Layer

Transport Layer

Core ServicesC

2 Sy

stem

s

C2

Serv

ices

C2

Serv

ices

C2

Serv

ices

Orc

hest

ratio

n

Dat

a M

odel

User Interface

Physical LayerData Layer

Network LayerTransport Layer

Gateway - Data & Services

Ded

icat

ed S

yste

m

Ded

icat

ed S

yste

m

Ded

icat

ed S

yste

m

Physical LayerData Layer

Network LayerTransport Layer

Gateway - Data & Services

Ded

icat

ed S

yste

m

Ded

icat

ed S

yste

m

Ded

icat

ed S

yste

m

GIG

NGONGOAgenciesAgencies CoalitionCoalition MilitaryMilitary

• Virtual Simulation (Simulations with a Test Bed involving Constructive Simulations with People & HW/SW In-The-Loop)

• Live Simulation (Simulation with real components in an exercise environment)

6

APL C2 Evaluation ObjectivesC2

TheoryNet-Centric C2Methodology

Net-Centric C2Infrastructure

2006

2005

ObjectiveAccepted

TheoreticalFoundation

for C2

Develop Aggregate C2 Model

C2 Review MRMEF:Constructive

MRMEF:Constructive,

& Virtual Simulation

MRMEF:Constructive,

Virtual,Live

Data Gatheringand Analysis

Manual DataGathering

Automated Data

Gathering

Integrated intoNet-Centric Applications

APL GIG Testbed

Mini-GIG

Distributed, Integrated

Red/Black GIG Testbed

7

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10

Experiment Run Number

Exec

utio

n Ti

me

(Sec

onds

))

Find PatternCreate Workspace

FY05: Performed Initial Measurements of Web Service & Human-in-the-loop (HITL) Execution Time

Process Decomposition via Scenario Modeling

1

4

Buy WME Move Launcher

Move WME

Prep Launch Site

Assemble Launch

Detect Activity Increase Monitoring

Threat Assessment & COA Development via COIs

Deter Sale

Destroy Launcher

Deter SiteDestroy Missile

Destroy WME

Terrorist Arrange

WME Purchase

Terrorist ActivitiesDeterrent Activities

Decomposed Scenario-based Activities

S t a r t

B u y W M D

M o v e W M E

L a u n c h M is s ileA s s e m b le a n d

T r u e

F a ls e

f a ile d

M is s ile la u n c h e d b u t

D a t a C o lle c t io nN u m b e r o f S t r ik e s

S t r ik e

M is s ile a n d W M E

A s s e m b le M is s ile

M o v e M is s ile

A c t iv it yD e t e c t B u y

A c t iv it ie s b e g inO r ig in a l

D u p lic a t e

A c t io n T e a m sC r e a t e C r is is

C A T f o r m e d

I n t e r c e p t

p la n D e t u r e a c t io n sO r ig in a l

D u p lic a t e

S a le A c t io nC o m p le t e D e t u r e

T r u e

F a ls e

D e t u r e S a le

S a le D e t u r e d

E n d S a le

S a le c o m p le t e d

N e u t r a liz e W M E

T r u e

F a ls e

P r o b a b ilit y o f s u c c e s sN e u t r iliz e W M E

W M E N e u t r iliz e d

E n d W M E

W M E a r r iv e s

A c t io n sP la n W M E

O r ig in a l

D u p lic a t e O r ig in a l

D u p lic a t e

A c t io nP la n M is s ile

in T r a n s itN e u t r a liz e M is s ile

O r ig in a l

D u p lic a t e

P la n S it e A c t io n

N eu t r aliz e S it e

P la n I M D

D is p o s e 8

T r u e

F a ls e

P r o b a b lit y o f S u c c e s sn e u t r a liz e d M is s ile

M is s ile n e u t r a liz e d

e n d M is s ile

M is s ile a r r iv e s

T r u e

F a ls e

P r o b a b lilt yN e u t r a liz e S it e

S it e N e u t r a liz e d

E n d s it e

S it e N o t N e u t r a liz e dp ic t u r e a d ju s t m e n t

A s s ig n 3

L o a d o n t o b o a t 1

lo a d o n t o b o a t 2

M is s ileC h a n g e p ic t u r e t o

o n e

v a r ia b le t o m in u ss e t N O S a le

V a r ia b le t o o n eA d ju s t N o S a le

T r u e

F a ls e

a r r iv e sc o m p le t e b e f o r e W M E

Y e s m in u s 1

S e t N o W M E t o

T r u e

F a ls e

D e c id e 8

T r u e

F a ls e

B e f o r e A r r iv a l t o Y e s ie m in u s 1

A d ju s t N o M is s ile

T r u e

F a ls e

A s s e m b ly ?N e u t r a liz e S it e P r io r t o

T r u e

F a ls e

S t o p p in g M is s ileI s I M D C a p a b le o f

T r u e

F a ls e

M is s ile R e lia b ilit y

T r u e

F a ls e

n e u t r a liz a t io nC h e c k o n W M E

N o ie o n e

A d ju s t N o W M E t o

T r u e

F a ls e

N e u t r a liz a t io nC h e c k o n M is s ile

t o o n eA d ju s t N o M is s ile

T r u e

F a ls e

n e u t r a liz a t io nC h e c k f o r S it e

o n eA d ju s t N o S it e t o

D is p o s e 1 4

T r u e

F a ls e

v a r ia b leC h e c k o n N o S a le

m in u s o n e

A d ju s t N o S it e t o

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

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0

0

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0

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Constructive Simulation

Red Force Processes

Blue Force Processes

2 3Created two web servicesMeasured service and HITL execution time

TimingResults

Application Execution Time

8

Theoretical Framework for C2

• Synthesize and aggregate current C2 models• OODA• MAAPPER• Enterprise Theory of C2 (EC2) developed by Jay Bayne,

Echelon 4 integrates:• Systems Engineering (Cybernetics)• Organizational Theory• Cognitive Science

• Key concepts:• The same C2 structure and processes occur at all levels of an

organization• Consistent relationships among C2 actors• A standard approach to C2 allows

• Efficiencies of C2 tool development & training• Better interoperability • Enhanced operations

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Developed Aggregate C2 Process Model

Combined process elements from existing C2 modelsSituational awareness, planning, and execution apply recursively to all levels of command

InformationSharing (IS)InformationSharing (IS)

CL-2, PT-1




CL-2, PT-2

CL-2, PT-n

IntentGuidance

PolicySA

E P

SASA

EE PP

IPo

G

SA

E P

IPo

G

SA

E P

SASA

EE PP

IPo

G

SA

E P

SASA

EE PP

IPo

G

SA: Monitor, Analyze, Assess, Predict

E:Approve, Exe

cute,

R

epor

t

P:D

evelop, Evaluate, Decide,

Disseminate

SA = Situational AssessmentKey

P = PlanningE = ExecutionI = IntentG = GuidancePo = PolicyCL = Command LevelPT = Participant

SA = Situational AssessmentKey

P = PlanningE = ExecutionI = IntentG = GuidancePo = PolicyCL = Command LevelPT = Participant

Define,

Plan,

CL-1, PT-1

Asse

ss,

10

FY06: Infrastructure for Experimentation

Agent-based simulation used as controllable scenario-generator

Joint Semi-Automated Forces simulation (JSAF)Supports agent-based free play Provides data to data fusion and visualization applications

Ground truthEntity perception

Interacts with other simulations and SOA-based applications via:Web-service/HLA translation interfaceHLA (High Level Architecture)DIS (Distributed Interactive Simulation)

Experiment architecture and infrastructure supports automated data collection based on metrics related to:

Systems/Technology Operational C2 processes

New Tools Enhance APL’s Experimental Capabilities

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Functional C2 Experimentation Architecture

Infrastructure

Experiment Control and Analysis

C2 Operations

DataCollection

• Network state• Stimulus state• Service

Performance• Application

metrics

• HSI / SME Observations

• Info Flow Observations

• Control Actions

• Network Infrastructure• Services & Applications• Experiment stimulus• Infrastructure Metrics• Simulation

-Juniper M10i-Juniper M10i

-Juniper M10i-Juniper M10i

-Juniper M10i-Juniper M10i-Cisco 7606-Cisco 7606

-Cisco 7606-Cisco 7606

-Cisco 7606-Cisco 7606

Cisco 3825 Cisco 3825

Classified

Unclassified

HAIPE

HAIPEHAIPE HAIPE


PublicInternet

FY06 InfrastructureGIG Test Bed


Firewall

End user application




Monitoring (AmberPoint) and

Management

Collaboration and messaging(.NET, J2EE,

LCS, IWS, VoIP, Jabber, MeetingPlace)

ServiceMediation (BizTalk)

Discovery (UDDI)



Security (NCES Security)

Monitoring (AmberPoint) and

Management

Collaboration and messaging(.NET, J2EE,

LCS, IWS, VoIP, Jabber, MeetingPlace)

ServiceMediation (BizTalk) Security

(NCES Security) Discovery (UDDI)

Cisco 3560G

Cisco 3560G

Cisco 3560G

Cisco 3560G

Ixia Traffic

Generator PS 1800e

PS1800e

PS 1800e

PS 1800e

PS Hurricane

PS Hurricane

1GbE IPv4 Backbone

Observe Control Observe

• C2/Decision Events• Collaboration Activities• Cognitive Actions

Scenario/Stimulus Stimulus Control

Stimulus Control Decision Activities

Stimulus Management

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Experiment ImplementationVignette 1 Example

Cntl

C2 Cell - PETCMonitor perceived

C2/tracks

Direct ISR,

WPN

Coord MSEL Inject

Observations

Cntl

Wpn Shooter Cell - TomahawkMSEL Injet

Observations

Cntl

MSEL Inject

Observations

Cntl

MSEL Inject

Observations

CAOC/TACCCntl

ISR/Fusion Cell -MSEL Inject

Observations

Monitor and control weapon

Ship Fire unit

Sample Ground Truth and drive SA via perceived track data.

UAV Gnd Station

“Edge User” - SOFAssess Situation

Provide ISR, CDE, PID

Direct Aimpoints

SOF

Stratcom – Strategic Lab Monitor C2/SA and provide National assets ISR

Cntl

Scenario Stimulus - JSAFProvide Ground Truth –OPFOR, SOF, other platforms

Strat ParticipantsCntl

MSEL Inject

Observations

Sub /TomahawkComm w/SOF

WPN shooter and control

Sub Fire unitCntl

Maintain Info Flow and collect metrics

IWS, JABBER, DCAT, WEEMC, Collabspace

NCES

CPAS, AmberpointServers + M&M

Cntl

MSEL Inject

Observations

GIG Testbed

+ CNTL net

CNTL VLAN

GIG”network”

13

Scenario OverviewBased on the MRM Evaluation Framework develop two scenario vignettes for current CEIVignette 1 – Global Strike

Information was received regarding the planned meeting of a high value target (HVT) in a mountainous village of Middle East countryA COA was developed and will be executed to insert a SOF team to either a) capture the target or b) eliminate the target via a Tomahawk strike

Vignette 4 – Emergency Disaster ResponseAn accident at the Calvert Cliffs Nuclear Power Plant resulted in the release of a radioactive plumeA COA was developed and will be executed to evacuate the surrounding community as quickly as possible in a manner that minimizes the evacuee’s exposure to the plume during the evacuation process

14

Operational Context Vignette 1

Participants:

Friendly: C2 node, ISR cell, Weapon Shooter, SOF team

OPFOR: Terrorist Cell meeting, Terrorist forces in area

Non-Combatants: local population

Goal:

Strike Terrorist Cell meeting.

Manage C2/ISR and strike assets. Minimize casualties to friendly forces and non-combatants.

Execute C2 processes and procedures stimulated by:

1. OPFOR actions

2. non-combatant actions.

15

Sample C2 Experiments:Vignette 1, Experiment 1

Evaluate if there is there a significant operational escape and avoid advantage to providing SOF teams with red force position information via fused ground track data vs. local sensing of red force positions (e.g. visual, motion sensors, etc.)Technology Focus: Data Fusion vs. local sensingOperational Focus: Effect on probability of enemy avoidanceMeasurements

Measures of Effectiveness (MOEs)# of red force (RF) detection events# of SOF team compromise events# of successful Tomahawk engagement events# of successful target destruction eventsProbabilities of each of the above

Measures of Performance (MOPs)Ground track update rateAccuracy of fused vs. simulation ground truth RF position data

16

Operational Context Vignette 4Participants:

Maryland EOC, Arlington EOC, USS WASP, Local Chiefs of Police, local population

Goal:

Evacuate the area surrounding the Calvert Cliffs Nuclear Power plant following a disaster

Manage evacuation assets from both Federal and State agencies. Minimize civilian casualties.

Execute C2 processes and procedures stimulated by:

1. Nuclear Plume movement

2. Evacuee actions

3. Traffic accidents

TBDCool Graphics

Calvert Cliff’sNuclear Power Plant

USS Wasp600 bed hospital

Helicopter refueling

Maryland EOC

Arlington EOC

EvacuationRoutes

17

Evaluate whether the availability of radioactive plume tracking data to the MD EOC allows that team to make better evacuation decisions compared with in-the-field reports of radioactive measurementsTechnology Focus: Data Fusion vs. local sensingOperational Focus: Effect on evacuation decision-making success

Proposed Measurements:Measures of Effectiveness (MOEs)

% of evacuees exposed to the plumeOf those exposed, degree of exposure to the radioactive plumeLevel of SA in the EOC regarding the plume location at defined periods of timeLevel of SA in the field regarding the plume location at defined periods of time

Measures of Performance (MOPs)Time to alter evacuation flow after a shift in plume directionResponse time of the weather web service to requests for weather/plume updates by the simulation tool# of communication events needed to establish effective SA regarding the plume location at defined periods of time

Sample C2 Experiments:Vignette 4, Experiment 1

18

Why Conduct Evaluations?

Supports value-based selection of net-centric services

Guides architecture decisions regarding core service selection, GIG capabilities & performance requirements, etc.

Helps define/refine net-centric implementation standards (NCIDS)

Documents

Evaluation of Net-centric Command & Control (C · Manual Data Gathering Automated Data Gathering Integrated into Net-Centric Applications APL GIG Testbed Mini-GIG Distributed, Integrated