nco role in battlefield management

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c r a f t i n g i n n o v a t i o n t o g e t h e r

Navneet Bhushan

([email protected])

Crafitti Consulting (www.crafitti.com)

CAIR, DRDO, August 10, 2010

A visualization of the network structure of the Internet at the level of “autonomous systems”—local groups

of computers each representing hundreds or thousands of machines. Picture by Hal Burch and Bill Cheswick, courtesy of Lumeta

Corporation. INTERNET

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August 16, 2010 2© Crafitti Consulting Private Ltd.

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The Singaporean designer Fung Kwok Pan has managed to capture

the flow of water in solid form, and the results are stunning.

http://www.fastcodesign.com/1662020/eye-candy-solid-

vase-is-a-3-d-pic-of-splashing-milk

http://www.fastcodesign.com/1662020/eye-candy-solid-vase-is-a-3-d-pic-of-splashing-milk























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Globe has been Re-engineered!

Flattening World

… And we don’t even realize it …

While the defining measurement of (old world)

was weight – … – the defining measurement of

the globalization system is speed – speed of

commerce, travel, communication and

innovation

Thomas L. Friedman, “The Lexus and Olive Tree”

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Power SystemViolence

Wealth

Knowledge

Knowledge based Violence &

Wealth

Violence & Wealth based

knowledge

Structure of

Future

World

Technological SystemsInformation Technology

Industrial Automation

Genomics

Bio-Technology

Smart Materials

Nanotechnology

Propulsion Technology

Geo Political SystemBipolarity/ Multi-polarity

Multinational Companies

controlling the world

Reducing Value of Nation State

Social SystemRise of the Individual/Ethnic/Religious

groupings

Nuclear/Single parent family system

Rise of dissatisfaction

Economic SystemSmall more Networked

Organizations

Rapid Changes in the way wealth

is generated

Low tariff barriers

Common Currencies and

compatible economic systems

Low entry barriers

Organization FormsHierarchies shifting to

Networked form of

Organization

Hierarchical Networks

Networked Hierarchies

SOURCE: Bhushan N. and Rai K., Strategic Decision Making, Springer Verlag, Jan 2004

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The Globalized World

• Global Real-time Awareness

• Large monolithic structures to small, distributed well-connected organizations –Collabtetion –Collaboration+Competition

• Hierarchies – Hierarchical Networks – Networked Hierarchies – Networks

• Power shifts to Knowledge Based Real-time Actors

• Time, Trade, Space, Geography, Cultural, Language, Social Shackles Demolished

• Survival of the Agile – Decision Making and Action at Electronic Speed

• Everyone has the wherewithal to continuously Re-invent oneself

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As economic fortunes rise, so does nationalism

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Complexity in a FlatteningWorld

Number of alternatives

Time pressure

Need for analysis

Information de-coherence

Connections

Networks

Human Processing Limits

(The Magic Number 7 ± 2)

Framing Limits

Confidence

Rapid Explosion

of Complexity

Connections create Value and Dependencies

create complexity

Future is approaching us Faster than History is

leaving us!

Increasing distance between user requirements

of what they really need versus what they want.

With every choice we make today we Kill

many possible futures

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Decision Making in a Flattening World

Number of alternatives

Time pressure

Need for analysis

Information de-coherence

Connections

Networks

Human Processing Limits

(The Magic Number 7 ± 2)

Framing Limits

Confidence

Rapid Explosion

of Complexity

Each Decision (a Choice) affects future

Choices (decisions)

Each Decision is impacted by past Decisions

(Choices) made by someone somewhere

With every choice we make today we Kill

many possible futures

With every choice we make today we Select

only a small subset of possible futures

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The Magical Number Seven, Plus or Minus Two:

Some Limits on our Capacity for Processing Information

George A. Miller (1956)

Harvard University

First published in Psychological Review, 63, 81-97.

[1] This paper was first read as an Invited Address before the Eastern Psychological Association in Philadelphia on April 15, 1955.

The point seems to be that, as we add

more variables to the display, we

increase the total capacity, but we

decrease the accuracy for any

particular variable. In other words,

we can make relatively crude

judgments of several things

simultaneously.

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The first decade of 20th Century…

• In 1890, Average company in US had - FOUR employees (4)

• By 1901, US Steel became world’s first 1 Billion $ company

• Ford Motor Company, founded in 1903, was producing half a million cars a by 1913


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The first decade of 21st Century…


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More is Different – Scale is the New Frontier


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SEI ULS Study – 2006!


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Why we don’t know how to Design ULSS?


System Design - Present ApproachesAll conflicts must be resolved centrally and uniformly

Requirements can be known in advance and change slowly.

Tradeoff decisions will be stable.

Discrete Time System improvements

Effect of a change can be predicted sufficiently well.

Configuration information

Components and users are fairly homogeneous.

People are just users of the system.

Collective behavior of people is not of interest.

Social interactions are not relevant.

Failures will occur infrequently. Defects can be removed.

A prime contractor is responsible for system development,

operation, and evolution.

ULS CharacteristicsDecentralized Control

Inherently conflicting, unknowable,

and diverse requirements

Continuous evolution and

deployment

Heterogeneous, inconsistent, and

changing elements

Erosion of the people/system

boundary

Normal Failures

New paradigms for acquisition and

policy

?

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20© Crafitti Consulting Private Ltd.

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ULSS Research Areas


ULS Systems

Research Area

Specific Sub-Areas

Human Interaction

• Context-Aware Assistive computing

• Understanding Users and Their Contexts

• Modeling Users and User Communities

• Fostering Non-Competitive Social

Collaboration

• Longevity

Computational

Emergence

• Algorithmic Mechanism Design

• Metaheuristics in Software Engineering

• Digital Evolution

Design

• Design of All Levels

• Design Spaces and Design rules

• Harnessing Economics to Promote Good

Design

• Design Representation and Analysis

• Assimilation

• Determining and Managing

Requirements

Computational

Engineering

• Expressive Representation Languages

• Scaled-Up Specification, Verification, and

Certification

• Computational Engineering for Analysis

and Design

Adaptive

System

Infrastructure

• Decentralized Production Management

• View-Based Evolution

• Evolutionary Configuration and

Deployment

• In Situ Control and Adaptation

Adaptable and

Predictable

System Quality

• Robustness, Adaptation, and Quality

Attributes

• Scale and Composition of Quality

Attributes

• Understanding People-Centric Quality

Attributes

• Enforcing Quality Requirements

• Security, Trust, and Resiliency

• Engineering Management at Ultra-

Large Scales

Policy,

Acquisition,

and

Management

• Policy Definition for ULS Systems

• Fast Acquisition for ULS Systems

• Management of ULS Systems

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Competitive Advantage- Over Ages

Time

Ex

tent of

Connec

tednes

s

How much of

Agricultural land

and Natural

Resources

How much can

be produced

How much and

Quickly can be

Informed

How much

Actionable

Knowledge

How Fast

Innovate

How Fast

Co-Create

In the Connected Age –

Co-Creators will thrive

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c r a f t i n g i n n o v a t i o n t o g e t h e rNature is

Fractal!

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Black Swan – The impact of the highly improbable

• “I cannot accept a pretense of science. I much prefer a sophisticated craft, focused on tricks, to a failed science looking for certainties” Nassim Nicholas Taleb

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© CRAFITTI CONSULTING

A Weakening of Hierarchies

• Information abundance permits INDIVIDUALS to by-pass hierarchies that have – deliberately or inadvertently – controlled or limited information

• Alternative human organization forms – based mainly on the Network have proved more effective and efficient for transacting information than hierarchies.

• In Information intensive enterprises, hierarchical organizations may not be competitive with networks.

IN ATHENA’s CAMP – Preparing for conflict in the Information Age, (Ed)

Arquilla J. and Ronfeldt D, RAND, 1997

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© CRAFI

ONLY Networks

CAN FIGHT Networks

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Combat

Fight/Duel/Conflict/Battle/War/World

War/Armageddon

Modelling

Representing a system and its internal and/or external

dynamics in such a form (may be mathematical) that

information about its behaviour can be extracted or

studied

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Parameters and Processes of Combat

• Two Sides

• Search

• Detection

• Identification

• Acquisition

• Tracking

• Weapon Target Assignment

• Weapon Aiming and Firing

• Attrition

• Command and

Control

• Damage

Assessment

• Strategic and

Tactical

Movement

• Influence of

Technology

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Nature of Combat and Combat Models

Past : Numerical Strength is Combat Power/ Attrition

Based

Modelling: Lanchester Equations Based and Fire Power

Scores in QJMA

Present: Technology Based Platform-Centric Revolution

in Military Affairs

Modelling: Weapon Power Scores in Extended Adaptive

Dynamic Model

Future: Network Centric Warfare

Modelling: Exploring New Models

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Approaches to Combat Modelling

Analytical Methods

• Lanchester Equations

• Adaptive Dynamic

Model

Firepower Scores

• QJMA

• WEI

• Weapon Power Scores

Simulation

• Combat

Simulations

• Wargames

New Approaches

• Cellular Automata

• Petri Nets

• Artificial Life

• Particle Swarm

Optimization

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Rand Report MG 268 (http://www.rand.org)


More than 12000 Sorties flown in mid 1990s to compare JTIDS datalink 16 system with conventional voice only communications

250% IMPROVEMENT

IN Kill Ratio

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Performance Evaluation of an Air Defence System (Networked) Modelled as a Petri Net (1998)


Delay

Arrival

Penetration

No response

Fighter

SAM

Gun

AD1

AD2

AD3

CAOC

CAOC

ACC

ACC

ACC

CAOC

TL3

TR2

TR1

TL3

BOR DERBOR DERBOR DER

Enemy AircraftAirborne radar

Mobile radar

Radar

Sensor Fusion Post (SFP)

ACC1

ACC2

SFP2

SFP3Central Air Operation

Centre (CAOC)

AIR CONTROL

CENTRE

(ACC)

SAM

OP

Centrel

SHORAD

OPERATION

CENTRE

FIGHTER

SQUADRON

OP CENTRE

SAM

Site

Air Defence

Guns

Fighter

Squadron

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Delay Delay StartStop Arrival

Limit

300 .Arrivals

Arrival

Threats

DetectedUndetected

Back Sensor

Undetected

PenetrationsPenetration

TX1

SFP

TL

Gone1

Gone2CAOC

ACC

NS

Plane

No response

ACCL

TR

ACCRSAM

Gun

Sqdn

SAMOC

Fighter Plane

SAM

Gun

Pres

Sres

Gres

SHORADOC

NG

NP

ACC

TX2

Transition with exponential firing

Transition with determinstic firing

Fig. 3 : TTPN Model of an AD System

Time Transition Petri Net Model of an AD System

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Penetration Probability Vs Arrival Rate


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Application- Simulation of Terrorist Networks and Evaluation of Strategies

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Destabilization Strategies

Each strategy identifies actor criticality in a different way. All strategies rely on data in one or more cells in the meta-matrix. The identified strategies are:

• Highest degree centrality: Isolate one agent from the covert network that has the highest degree centrality [20].

• Highest betweenness centrality: Isolate one agent from the covert network that has the highest betweenness centrality [20].

• Highest cognitive load: Isolate one agent from the covert network that has the highest cognitive load [6], where cognitive load is computed as a linear combination of:

– Number of people person i interacts with / total number of people in the group;

– Number of subtasks person i is assigned to / total number of subtasks;

– Sum of number of people who do the same tasks person i does / (total number of tasks * total number of people);

– Sum of negotiation needs person i needs to do for each task / total possible negotiations, where a negotiation corresponds to the amount of information or resources that an agent needs to complete a subtask that it is assigned to, but doesn't have (and thus has to obtain from another agent by negotiation).

• Highest task accuracy: Isolate the best performing agent in the organization. This corresponds to standard police practice of arresting agents implicated in commission of a terrorist act.

• Amount of unique knowledge: Isolate the agent that has the highest expertise.

© Crafitt

39

http://www.cmu.edu/joss/content/articles/volume6/TsvetovatCarley/index.html



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NetWatch: A Multi-Agent Network Model of Covert Network Surveillance and Destabilization

© Crafitt

40

• Random case consisted of random removal strategy combined with one of the three wiretapping strategies. The baseline increases with accuracy of network discovery because of the fact that learning more of the network gives the random strategy better access to targets (including these of high importance). In the absence of false positives, the baseline strategies perform better then many complex heuristics.

• Degree Centrality-based removal of agents performs well only with targeted wiretapping. This is because targeted wiretapping allows the Blue Team to completely discover a cell and all of its neighborhood, and thus be very confident in removal of a most central person. However, the network does recover reasonably quickly from the hit, thus decreasing the effectiveness of this strategy.

• Betweenness Centrality-based removal performs well with roving wiretaps - because of the fact that they allow quick location of key gatekeepers in the network.

• Cognitive Load-based removal requires significant knowledge of the network, and thus only performs well under targeted and roving wiretap strategies.

• Quite surprisingly, removal of Well-Performing individuals did not result in significant damage to the terrorist network. Most likely this is caused by the structure of the tasks that the agents perform and equivalence of individuals in equivalent network positions.

• Knowledge-based removal proved to be the most effective strategy of the lot, and the only one to outperform the baseline strategies. The key to knowledge-based removal, though, is that its effectiveness hinges on speed of response more than the accuracy of structural knowledge. The experiments show that the highest efficiency of this strategy is achieved if Red Team experts are found and removed before they transmit much of their knowledge to the rest of the group, thus favoring quick decisive action to lengthy deliberation and heuristic learning that are characteristic of roving wiretaps.

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The Past

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Combat

• Duels

• LOS Fire

• Attrition Based Warfare

• Numerical Strength

Important (the 3:1 Rule)

To make a Brigade of 4000 troops ineffective, one

needs to destroy atleast 33% to 50% of its troops

using a Division of about 12000 troops

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Combat Models: Past

• Coupled Differential Equations

incorporating the rate at which both sides

destroy each other’s numerical strengths

• Quantified Judgement Method of Analysis

based on Empirical Formulae developed

using Historical Combat Data of Past

Wars (T.N. Dupuy)

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The Present

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Influence of Technology on War/Combat

Information Technology

C4ISR IW/EW/SEW

PGMs ILSS

Knowledge Processing

Intelligence Analysis

Tactical and Strategic

Planning

Automated/Rapid Military

Decision Making

Telecom & Networking

Communications

NetWar/CyberWar

Mobile Comm

Lethality

Mass Destruction to

Selective/Precise &

Effective Destruction

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COLLECT &

PROCESS

BATTLEFIELD

INFORMATION WITH

SPEED AND

ACCURACY

CAPABILITY TO

PICK OUT

TARGETS IN A

DYNAMIC BATTLE

SCENARIO

ABILITY TO DESTROY

TARGETS WITH

PRECISION FROM

GREATER RANGES

HEART OF REVOLUTION IN MILITARY AFFAIRS

(RMA)

INTERACTION

ABILITY TO SEE / CHOOSE TARGETS BETTER

INCREASES THE EFFECTIVENESS OF

PRECISION GUIDED MUNITIONS

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The Future

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Network Centric Warfare

Network is the Computer

Fundamental Shift from Platform Centric

warfare to Network Centric Warfare

Characterized by:

Very High Level of Shared Battlespace

Awareness

Shared Knowledge of Commanders Intent

Self-Sync, Speed of Command, and rapid lock-

out

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Network Centric Warfare:

Sources of Increased Combat Power

Shared Battlespace Awareness

Increased Battlespace Awareness

Battlespace Expansion: Employment of

Weapons at Max Range

Increased Survivability

Self-Synchronization of Forces

Reduced Collateral Damage

Virtual Collaboration: Moving Information not

people

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Modelling and Analysis of

Advanced Technologies and

Combat Support Systems in

Combat between RMA Forces

The Present

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Evaluation of Weapon

Power Scores of Army,

Navy and Air Force

Weapons

Combat

Support System

(CSS)

Capability

Assessment

Combat

Outcomes

CSS Weights

based on AHP

Force Multiplier

related to CSSEstimation of

Quantity of

Weapons

Force Strength

Evaluation

Generation of

Combat Scenarios

Adaptive

Dynamic

Model

Estimation of

Model

Parameters

M E T H O D O L O G Y

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Weapon Power Score

Self

Protection

Index

Integration

IndexLethality Operability

Index

On-Board

Weapons

Capability

On- Board Self

Defence

Capability

Night / All

Weather

Capability

Ability to get

connected to

C3I System

Each Node in the Network

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= Operational Lethality Index (OLI) x (1+ Self-Protection Index (SPI)) x

(1 + Operability Index (OI)) x (1 + Integration Index (II))

Weapon Power Score (WPS)

Force Strength (FS)

= Summation of product of WPS and Quantity of weapons in a force

Force Potential (FP)

= Force Strength x (1 + Combat Support System Effectiveness Factor)

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Factors considered for OLI Computations

Weapons Factors

Infantry Small Arms

and Non Mobile

Weapons

Rate of Fire, Range, Accuracy, Reliability,

and Potential Targets per Strike, Dispersion

Factor

Arty Towed/AD Guns All of the above and certain Artillery

related factors

Arty Self-Propelled All of the above and Mobility factors.

Armour, Ships,

Submarines

OLI of on-board Guns and Missiles,

Mobility factor Punishment factor,

Ammunition factor, Amphibious

capability factor etc.,

Attack Helicopter,

AircraftOLI of on-board Guns, Missiles, Ceiling

factor Mobility factor,

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Factors Affecting SPI, OI and II of Army Platforms

Weapon System Factors Affecting

SPI IIOI

Infantry Survivability Night Vision,

Transportability

Communication Links

with Brigade. HQ. and

RPV/UAV

Armor

Built-in-Armor,

Reactive Armor, Top

Attack Protection NBC

Protection, Fire &

Explosion Suppression,

Silhouette, Agility

Night Vision, All

Weather Operations,

fording,

Amphibious

Capability, Air

droppable

Communication Links

with RPV/UAV and other

Armor Vehicles.

Artillery GunsShoot & Scoot

Capability, Stand Off

Range, Armored

Protection

All weather

Operability, NBC

Operability.

Integration with AOP

AD Arty/ SAMShoot & Scoot

Capability, Stand Off

Range

Radar Control, NBC

Environment

Integration with C2

system

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c r a f t i n g i n n o v a t i o n t o g e t h e rFactors Affecting SPI, OI and II of Air force Weapons


SPI OI II

Close Air

Support /

Attack Helo

Deep Strike

Air Defense

Chaff, ECM,

ESM, Multi Mode

Radar, Precision

Guided Munitions

All of the above

and Inertial

Navigation

System

All of the above

and Look

Down/Look Up

Radar

Night Flight,

Night Time

Delivery, All

Weather

Operation

Inter Aircraft

& Ground

Station

Communicati

on

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c r a f t i n g i n n o v a t i o n t o g e t h e rFactors Affecting SPI, OI and II of Naval Platforms


SPI IIOI

Battle Ships Intensity of

Threats faced,

Ability to detect

threatening

Platform,

Protection to

Evade hit,

Protection to

Evade Kill given

hit, Ability to

Jam/Confuse

Enemy Platform

Shallow

Water/ High

Seas

Operability

Communication

Links with Shore,

with Maritime

Aircraft, with Sub

Marine force, with

other Ships.

Submarine

Communication Links

with Shore, Maritime

Aircraft, Own

Submarine force.

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Combat Support Systems (CSS)

Intelligence Surveillance

& Reconnaissance(ISR)C4 Information

Warfare

Logistics

Support

System

Space based

Airborne

Sea Based

• Ground Based

Command and

Control

Communications

Computers

System Integration

EW

Opsec

Psyops

Deception

Lethal IW

Non lethal IW

Encryption

SW Engg

Networking

Computer

Security

Info Security

Infrastructure

Resources

Material

Management

National

Resources

Inter-service

Integration

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IW

ILSS

Space

Air

Sea

Gnd

Cmd & Control

Communications

Computers

System Integration

ISRC4

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I1 I2 I3 I4 C1 C2 C3 C4 W L

Space based ISR (I1) 1 1 1 1 1 0 0 0 1 1

Airborne ISR (I2) 0 1 1 1 1 0 0 0 1 1

ISR Sea based ISR (I3) 0 0 1 0 1 0 0 0 1 1

Gnd based ISR (I4) 0 1 1 1 1 0 0 0 1 1

Cmd and Control (C1) 0 0 0 0 1 0 0 0 1 0

C4 Communications (C2) 1 1 1 1 1 1 1 1 1 1

Computers (C3) 1 1 1 1 1 1 1 1 1 1

System Integration (C4) 1 1 1 1 1 1 1 1 1 1

IW (W) 1 1 1 1 1 1 1 1 1 1

ILSS (L) 0 0 0 0 1 0 0 1 0 1

I1 I2 I3 I4 C1 C2 C3 C4 W L

Space based ISR (I1) 1 0 0 0 0 1 1 1 1 0

Air ISR (I2) 1 1 0 1 0 1 1 1 1 0

ISR Sea based ISR (I3) 1 1 1 1 0 1 1 1 1 0

Gnd based ISR (I4) 1 1 0 1 0 1 1 1 1 0

Cmd and Control (C1) 1 1 1 1 1 1 1 1 1 1

C4 Communications (C2) 0 0 0 0 0 1 1 1 1 0

Computers (C3) 0 0 0 0 0 1 1 1 1 0

System Integration (C4) 0 0 0 0 0 1 1 1 1 1

IW (W) 1 1 1 1 1 1 1 1 1 0

ILSS (L) 1 1 1 1 0 1 1 1 1 1

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Combat

Support

Systems

Combat

Support

System

Dependency

Indices (Di)

Combat

Synergy

Indices

(Si)

Sub System

Activity Index

Ai =(Di) X (Si)

CSS Normalised

Weights

(Wi)

Order of

Ranking

Space based ISR 0.064 0.083 0.00531 0.0598 VIII

Air based ISR 0.096 0.070 0.672 0.0757 IV

Sea based ISR 0.115 0.047 0.00541 0.0609 VI Gnd based ISR 0.096 0.070 0.00672 0.0757 IV

Cmd and Control 0.165 0.033 0.00545 0.0614 V

Communications 0.054 0.165 0.00891 0.1004 III Computers 0.054 0.165 0.00891 0.1004 III

System

Integration 0.076 0.165 0.01254 0.1413 II

IW 0.142 0.165 0.2343 0.2639 I

ILSS 0.138 0.039 0.00538 0.0606 VII

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ISR C4

Space Based

Air Based

Sea Based

Ground Based

Command and Control

Communications

Computers

System Integration

IW ILSS

Country A Country B Country C

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CSS Factors

ISR

Space based ISR Communications Satellites, Navigation Satellites,

Meterological Satellites, Imaging Reconnaissance Satellites,

Relay Satellites

Air baser ISR AWACS/AEW, Air based Ground Tactical Reconnaissance,

Maritime Reconnaissance, Airborne Ground Strategic

Reconnaissance, Airborne Battlefield Surveillance Capability

(UAV/RPV capability)

Sea based ISR Surface Tactical Recce, Sub-surface Tactical Recce, Strategic

Recce, Coast based Strategic Recce

Ground based

ISR

Tactical Recce, Air Space Recce, Strategic Recce

C4

Command and

Control

Strategic C2, Tactical C2, Politics Military C2, Inter Services

Integration

Communications Utilization of EM Spectrum, Communication System,

Communication Security, Merger with National Telecom

System

Computers Computing Power, Software capability, Knowledge

processing and Automated Decision Making Capability

System

Integration

Data Fusion, National Level Interoperability, Inter Services

Operability, Integration of ISR, C2, ILSS with Lethal

System, Fault Tolerant Communication / Computing,

Interoperability Standards

Information Warfare (IW) Operations Security, Psychological Operations, EW,

Deception Lethal IW, Non Lethal IW, Cryptology, Computer

Security, Info Security, Intelligence

ILSS Armed Forces Resources, Logistics Infrastructure, Material

Management, National Resources, Inter Service Integration

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Adaptive Dynamic Model (ADM)

• Off shoot of Lanchester Models

• J.M. Epstein

• Use of Exchange Ratio and

Prosecution Rate

• Parameters reflecting ability to

concentrate fire in engagements

• Uses Force strength instead of

Numerical Strength

• Withdrawal and reinforcements

• Close Air Support to Ground Forces

Extensions

• Air to Air Combat

• Naval Combat

including sub surface

• use of Weapon Power

Scores instead of

WEI for Force

Strength

• Estimation of

parameters based on

realistic data

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• Initial Force Strengths

of the Forces

• Force Strength

Reinforcement on each

day

• Force Strength Attrition

Rate

• Exchange Ratio

• Threshold Attrition

Rates

• Number of Close Air

Support (CAS) Aircraft

• CAS daily Sortie rate

per Aircraft

• CAS aircraft Attrition

rate per sortie

• Battle termination

Conditions

Force

Strength loss

and Aircraft

Attrition per

day

OUTPUT

INPUT

Adaptive

Dynamic

Model

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Equations of the Model :

,)1(111 tg

RAtDCASttg

Atg

A

,)1(11

11 t

gRDtACASt

gA

t

tt

gDt

gD

,

maxW

W(t)1 )( )(

t

gt

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)1( if )1( 1

)1(W )1(

)1( if 0

)(max

dT

dTddTd

dT

d

tttW

tW

t

tW

.)(

)1()1()(

)(t

gD

tg

RDtg

Dtg

D

td

We set W(1) = 0, on the attacker’s side

aT

ta

aT

tgTa

tg

tg

)1(

)1(

)1()(

,

)(

)1()1()1(

)(t

gA

tg

RAtg

Atg

A

ta

.

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We set g(1) equal to some initial value [g(1)

aT].

The ground-induced exchange ratio is givenby

,

)(g

A

)(

0 = )(

at

dtg

D

t

(8)

where 0 is a constant.

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Equations for Close Air Support (CAS)aircraft:

),( 1 )1(a

D = )( ta

RDdS

datt

aD

).(1 )1( = )( ta

RAaS

aat

aAt

aA

),( = )( ta

DatDCAS

, 1

1da

-1-1

=

da

dS

V

dKL

a

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),(A b = )( ta

tACAS

. 1

1

aa-1-1

=b

aa

aS

Va

KL

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SIDE A SIDE B

Ground Forces Ground Forces

CAS Forces CAS Forces

AD FightersAD Fighters

AD EscortsAD Escorts

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Test Scenario – Country A Strike

Corps attacking Country B holding forces

Force with

Country A

Force with

Country B

1 Armoured

Division

2 Infantry Division

1 Independent

Armoured Brigade

3 Independent

Armoured Brigades

3 Infantry

Divisions

1 Armoured

Regiment

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Total FS available (x1000)

Country A

1 Armoured Division + 3 Infantry Division + 1Independent Armed Bde = 910.6 + 3 x 184.5 + 359.9 = 1824

Country B

2 Infantry Division + 3 Independent Armed Bde + 2Armoured Regiments = 2 x 152.3 + 3 x 266.2 + 88.7 = 1191.9

Force Strength Ratio (FSR (A/B)) = 1.53

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Mobilizations Schedule

Ith

Day Country A (Attacker) Country B (Defender)Force FS

(x1000)Force FS

(x1000)1 2 Infantry Division

= 2 x 184.5369 2 Infantry Bde + 1

Integral ArmedRegt = 2 x 1/3 x152.3 + 1/3 x266.2

190.3

2 2 Armed Bdes =2 x 359.9

719.8 2 Armed Bde + 1Inf. Bde = 2 x266.2 + 1/3 x152.3 = 532.4 +50.8

583.2

3 Armoureddivision -Armoured Bde =910.6 - 359.9

550.7 1 Armed Bde =266.2

266.2

4 Infantry Division 184.4 1 Infantry Division 152.3

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Results of Test Scenario

o=2.0 a = d = 0.035

Day FSattacker

(remaining)

FSdefen

der(remaining)

Threshold

attacker

Threshold

defender

FSR

1 369.00 193.10 184.50 127.50 1.93902 1041.16 583.56 520.58 390.99 1.78423 1527.58 675.61 763.79 452.66 2.26104 1613.37 656.90 806.69 440.12 2.45615 1501.68 496.89 806.69 440.12 3.02216 1395.64 354.74 806.69 440.12 3.9343

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Performance IndexATK (A) DEF (B)

TFS (a) 1823.9 1192RFS (b) 1395.64 354.74FSL(a-b) 428.26 837.26

FSL/TFS (X) 0.235 0.70PI = X(B)/X(A) 0.70/0.235 = 2.99

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The Future

An Information Theoretic

Approach to Estimate Threat

Intensity Distribution in

Network Centric Combat Force

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INFORMATION

GATHERING NODES

•SATELLITE

SURVEILLANCE

•AD RADAR

•AIRBORNE EARLY

WARNING

•UAV, etc

NETWORK CENTRIC COMBAT FORCE

DATA FUSION NODECOMMAND AND

CONTROL NODE

AIRBORNE EARLY WARNING

SATELLITE

SURVEILLANCE

LOGISTICS NODE

COMBAT NODES

BATTLE DAMAGE

ASSESSMENT NODE

UAV

AD

RADAR

SENSOR INFO.

COMM. LINK.

ENEMY FORCES

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THREAT INTENSITY (T) VS COMBAT SUPPORT SYSTEM EFFECTIVENESS

RATIO (k)

T = exp(- k x FSR )

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

00.

20.

40.

60.

8 11.

21.

41.

61.

8 22.

22.

42.

62.

8 3

Combat Support System Effectiveness (f/e) (k)

Th

reat

Inte

nsi

ty

(T)

Force Strength Ratio = 0.5 Force Strength Ratio = 1.0 Force Strength Ratio = 1.5

Force Strength Ratio = 2.0 Force Strength Ratio =2.5 Force Strength Ratio = 3.0

THREAT INTENSITY (T)

T = f (FS, CSS) for friendly and Enemy force

= e-k * FSRk = Ratio of CSS

FSR = Ratio of FS

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New Modelling Approaches for Combat

Petri Nets

Cellular Automata

Artificial Life

Chaos/Catastrophe Theory

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© Crafitt

81

Some terms

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© Crafitt

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Real World Networks

• Social Networks: Set of people or groups of people with some pattern of contacts or interactions between them

• Information/Knowledge Networks: How information units are linked – e.g. Citation Network of academic papers OR World Wide Web

• Technological Networks: Man-made networks designed for distribution of some commodity or information. Electric Power Grid, Railways

• Biological Networks: Food web, Blood Vessels

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Network Centric Operations

NCO is a theory which proposes that the application of information age concepts to speed communications and increase situational awareness through networking improves both the efficiency and effectiveness of military operations.


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© CRAFI

Social Computing and Social Network Analysis

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© CRAFI

Social Computing (Wikipedia)• Social computing is a general term for an area of computer science that is concerned with the

intersection of social behavior and computational systems.

• In the weaker sense of the term, social computing has to do with supporting any sort of social behavior in or through computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking and other instances of what is often called social software illustrate ideas from social computing, but also auction software and other kinds of electronic market or electronic negotiation platforms where people interact socially.

• In the stronger sense of the term, social computing has to do with supporting “computations” that are carried out by groups of people, an idea that has been popularized in James Surowiecki's book, The Wisdom of Crowds. Examples of social computing in this sense include collaborative filtering, online auctions, prediction markets, reputation systems, computational social choice, tagging, and verification games.

• Social computing has become more widely known because of its relationship to a number of recent trends. These include the growing popularity of social software and Web 2.0, increased academic interest in social network analysis, the rise of open source as a viable method of production, and a growing conviction that all of this can have a profound impact on daily life

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© CRAFI

Social Networks• Graphs representing social relationships between

people or organizations

• Each Node is a person or actor

• An edge connecting two nodes is also called a tie and represent a social relationship

How can we Draw this Network for 1 Million people?

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© CRAFI

Building a Social Network• How to gather data for building a social network?

• Two Main Approaches

• Elicitation – Questionnaire/Survey

• Registration – Registered information – emails, membership lists

• Elicitation – old method is inaccurate and costly

• Registration is more useful and scalable

• Especially with online networks

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Random Graph

© Crafitt

90

• Mathematicians have studied these extensively

• Undirected edges are placed at random between a fixed n vertices

• Maximum edges possible = (n/2) (n-1)

• In a random graph each edge is independently present with a probability p

• Degree of the vertex is distributed according to a binomial or Poisson distribution

Real life Networks appear to be Non-random – leading to explanations about network formation and emerging structures

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Milgram’s Experiment – Six Degrees of Freedom

• In mid-sixties Stanley Milgram, a social psychologist teaching at Harvard, with a reputation of doing original experiments, conducted an innocuous experiment which by his standards was rather boring to say the least. He asked 160 volunteers to send a letter to his stockbroker friend in Boston. The only condition was to send the letters not directly to the stockbroker but to their own friends, whom the volunteers think are most likely to know the stockbroker. Each of the friends was asked to send this further in the same manner.

• Surprisingly, the letters arrived to the stock broker in an average six-hops or six-degrees. This led to the notion of six-degrees and of small world – that all of us are connected to each other by six intermediate connections. We all are connected to a small subset of people, which is true. It is also a fact that each of our connections is not mutually exclusive. They connect with each other as well. In effect, our connections are clustered. This leads to a problem, world can’t be both – a small world and a clustered one.

© Crafitt

91

HOW CLOSE YOU ARE TO BARACK OBAMA?

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Small-World Effects

© Crafitt

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• Most pair of vertices in most networks seem to be connected by a short path through the network

l << n

How fast rumors spread in a network?

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Transitivity or Clustering

© Crafitt

93

• A friend of your friend is most likely to be your friend as well!

• How many triangles does the Network has

Clustering Coefficient

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Minimally Connected Networks- Properties

© Crafitt

95

N=16; Arcs = 15 => Arcs/N = 0.94

Minimally Connected Network – Nodes are all connected with the minimum number of links possible

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© Crafitt

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Maximally Connected Network – Every Node is directly connected to every other node

Maximally Connected Networks - Properties

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© Crafitt

97

Random Network– Unpredictability in the network

Random Network- Properties

Links are distributed randomly

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© Crafitt

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Regular Network– Uniform clustering

Regular/Lattice Network- Properties

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© Crafitt

99

Small World Network– A Minor rewiring of Regular Network

Small World Network- Properties

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© Crafitt

100

Random Network with Growth – A Minor rewiring of Regular Network

Random Network with Growth- Properties

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© Crafitt

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Scale Free Network with preferential attachment – A very adaptive network

Scale Free Network with preferential attachment - Properties

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© Crafitt

102

Network Comparison

15

120

32

15

15

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Social Scientists Classification of Social Networks

© Crafitt

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Ego-Centric Networks Socio-Centric Networks Open-System Networks

Networks that are

connected with a single

node or individual

Boundaries of the

network are clear;

Networks in a Box

Boundaries are not

necessarily clear

Example, My good

friends, All companies

doing business with ABC

Example, students in a

class, employees of an

organization

Example, network of

elite class, connections

between corporations

Lists alone are

insufficient – info about

connections also is

required

Most studied in terms of

fine points of network

structure

Most interesting and

most difficult to study

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Social Network Archetypes

Type Customized Response Modular Response Routine Response

Problems and

Solutions

Ambiguous Known components –

but combination or

sequence not known

Well-defined and

predictable

Value Quickly framing and solving

a problem in an innovative

way

Delivering a unique

response depending

upon the constellation

of expertise required

by the problem

Efficient and consistent

response to a set of

established problems

Types New product dev,

investment banks, Strategy

consulting

Surgical teams, Law

firms, B2B sales

Call centers, insurance

claims processes

© Crafitt

105

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Taxonomy of Network Centric Warfare Architectures

© Crafitt

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Architecture Characteristics

A. Centralized One central high value Hub – other low value nodes networked

and controlled by Hub

B. Hub-Request “Type E” Request based plus one or more central high value hubs

C. Hub-Swarm “Type G” Swarming plus one of more central high value hubs

D. Joint Mixture of other six types (Type A, Type B, Type C, Type E, Type F

and Type G)

E. Request-Based Nodes of same value, but with different specialized capabilities.

Request for service between nodes of different kinds

F. Mixed Mixture of “Request-Based” and “Swarming”

F1: Limited Types Small number of node types (includes the case of separate sensor,

engagement, and C2 grids”

F2: Commonality Nodes are different, but have significant commonality

G. Swarming Nodes identical or nearly so

G1: Emergent Swarming Nodes follow simple rules, like insects

G2: Situationally Aware

Swarming

Nodes share information to build up Situational Awareness

picture

G2(a): Orchestrated One node is a temporary “leader”

G2(b): Hierarchical Nodes are arranged in a Hierarchy

G2(c): Distributed No Leader or Hierarchy

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Combining these three classifications – we propose following 5 type of social networks

• Customized Response Open Swarms (CROSs) Networks

• Modular Response Socio-Centric Request-Based (MRSR) Networks

• Routine Response Ego-Centric Centralized (RECC) Networks

• Customized Response Socio-Centric Hub-Swarm (CuSHuS) Networks

• Customized Response Open Request-Based (CROR) Networks

© Crafitt

107

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OPEN QUESTION?????

Network Centric Warfare –

A Revolution in Search of Doctrine


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NCW Military Doctrine

Military Doctrine is defined as a comprehensive system of views and procedures for conduct of future wars including various military operations, established by military experts, technologists and armed forces, in the likely threat environment, and within the purview of present force structures.

The doctrine is subject to periodic reviews and analysis and is evolved taking into account the dynamic geo-political, economic and technological trends in the world scenarios. Also such a doctrine should be freely available as a comprehensive document, so as to give a common basis for decision making at all level of military and defense hierarchy of the nation.


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National Security Doctrines


Doctrines

Domain Aim(s)

1. POLITICAL DOCTRINE

International Relations

Foreign Policy

Diplomacy

Politics

How to Avoid war

If imposed, how to support war

2. MILITARY DOCTRINE

Army

Navy

Air Force

Space Force

Joint Operations

How to wage war

3. ECONOMIC DOCTRINE

Economic Policy

Industrial Policy

How to support and sustain war

4. INTELLIGENCE DOCTRINE

Intelligence Agencies

Analysis Agencies

How to collect, process and disseminate information for timely decision making

5. WMD DOCTRINE NBC Policy

Peaceful Nuclear Uses

How to deal with enemy’s WMDs and deploy own WMD

6. SPACE DOCTRINE

Space Plans

Communication, Reconnaissance & Spy Satellites

Launch Vehicles

How to support (1) - (5) by providing near real time information to analysts

7. CYBERPACE/ INFORMATION

WARFARE DOCTRINE

Cyber Space

Audio Visual & print Media

Propaganda

Propaganda in cyberspace

Counter enemy propaganda

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The Changing Battlefield – from Linear Battlefield ….


Logistic Supply

Centre

Strategic Reserve

C2Centre

FWD Deployed Force

Mobile

Attack with

Armour

Enemy FWD

Deployed

Force

Border

Enemy

Mobile

Reserve

Fig. 1. Traditional Linear Battlefield

( Sequentially dealing with each of enemy’s force component)

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Strategic Reserve

C2Centre

FWD Deployed Force

Traditional

Armour

Advance

FWD

Deployed

Force

Border

Mobile

Reserve

Fig.2. Air Land Battle Doctrine

( Increased Non-Linearity)

Air Attack

on Follow

on Force,

Strategic

Reserves

and C2

Centre

The Changing Battlefield – to Air Land Battle Doctrine ….

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Anti ISR Attack

Anti C4 Attack

Anti EW Attack

Anti ILS Attack

Strategic Attack

Attack against enemy

Mobile Unit

Attack Levels

Border

FWD Deployed

Highly Mobile

smaller Units

(screen force)

Airborne Surveillance

Systems

Automated

PG Long Range

Missile

Mobile C4 ISR

Centre

Enemy

Fig. 3. Future Doctrine (Highly Non-Linear)

Mobile Armoured Units

The Changing Battlefield – to Non-Linear Network Centric Battlefield ….

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Key Features of the NMD

Catering for Unanticipated Threats

Knowledge Based

Flexible

Timely

Highly Trained Manpower

Accurate BDA

The Changing Battlefield – to NCW Doctrine Features ….

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Key Features of NMD

• NMD should cater for ‘unanticipated threats’. Gone are the days when it was possible to clearly point out one’s friendly and enemy nations. In the new world order, no country has permanent friends or foes. It is only the interests of the country that have permanent nature. Therefore, a nation should be prepared to deal with ‘unanticipated threats’ from unknown quarters.

• Intelligence/Information and knowledge should be the basic building block of the NMD. Troops, units and military organisations should be trained and structured to treat information and knowledge as the basic tool of fighting wars. These should be armed with processes and equipment for speedy collection, processing and dissemination of information/intelligence and knowledge.

• NMD should be flexible enough to take care of multitude of varied threats with different levels of sophistication e.g. the high mobility armoured units based doctrine may not work against Guerrilla’s or terrorists in an LIC (Low Intensity Conflict), but will have excellent performance against conventional multi-layered defence layout.


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Key Features of NMD

• Forces, logistics and communications should have ‘Just in Time’ capability. Bringing out forces needed to destroy an enemy as soon as the need arises is the crux of the problem. If the enemy is made to believe that the friendly forces are omnipresent, it will be extremely difficult for the enemy to attack, however strong the enemy may be.


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Key Features of NMD

• Despite all the technologies, it is the man beside the machine who counts. The NMD should start with a well balanced training of troops and commanders. The future battlefields will require agile leaders. These commanders must be capable of rapidly formulating concepts, planning operations, making decisions and pressing the fight. Agile leaders who quickly and accurately apply the conditions of their environment much faster than the enemy will produce decisive victories. Therefore, proper, continuous training programs based on automated battlefield systems for military commanders are needed. Quality of leadership in terms of training, motivation and innovativeness will decide the wars of future. The burden on the military soldier who will actually pull the triggers will increase manifolds. These soldiers should be trained to handle multiple weapons in various terrains, environment conditions and jointly with other forces. Manpower development is the basis of the NMD.


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Key Features of NMD

• NMD should be based on accurate and timely Battle Damage Assessment (BDA) on the enemy. If a first strike is successful against an enemy, there is no point in going for second and third strikes. The resources can be better utilised by going to the next task. In earlier warfare, BDA was a luxury but in future wars it will be a necessary activity as it gives the option of using one’s forces in a much more flexible way. BDA helps the commanders to allocate means, commit collection assets and execute collection plans. Timely, accurate and continuous BDA is the key feature of the NMD.


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S.No. Threat Countered By

1 Low Intensity Conflict/Guerrilla

Warfare/Insurgency

Intelligence/Propaganda/

counterinsurgency Doctrine

2. Traditional Face to Face Attrition warfare based

military deployment (Ex. Soviet Union multi-

layered defence layout)

Highly Mobile Tanks/Armour Penetration Units

based doctrine

3. Mobile armour/tank penetration doctrine Airland Battle Doctrine/Follow on Forces Attack/

Strike Deep Strike Hard

4. Air Land Doctrined Forces SEW, PGMs integrated in C4ISR system backed by

RMA technologies

5. RMA backed Joint force doctrined forces Combination of SEW and PGMs at Strategic level

backed up by very small units capable of disrupting

enemy’s lines of Communications, C2 system and

capable of

disinformation/camouflaging/Information Warfare

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A New Integrated Armed Structure called SLAP

SLAP (Sea Land Air and sPace) force

The small, independent, information warfare capable units should be linked together through a series of multi-purpose, redundant, reliable, fault tolerant

and intelligent communications links, C2 nodes, logistics support links and SEW links.


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Platoon Information Combat and Kill


ORGANISATION OF PICK

Arms Section Information Warfare Section C4ISR Section

A1. Anti Air Weapons

Portable SAMs

Portable Anti Missiles Missiles

B1. UAV unit

Short and Medium range

information collection

Short range strike capability

C1. Liaison Unit

Computerised Connections with

other PICKs

A2. Anti Armour Weapons

Anti Tank Missiles

Anti Tank Guns

B2. EW unit

Electronic Jammers

ECCM Systems

ESM systems

C2. Signals Unit

Mobile computing based, multi

media based system

Uses GPS

A3. Anti Personnel Weapons

Light Weight Mortars of high

calibres capable of firing smart

munitions

Dual use rapid fire guns for long

range (sniper fire) and short

range fights.

C3. Analysis Unit

PICK HQ

C2 centre

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NCW Doctrine has to be based on Swarming and Spiral Swarming

Swarming is achieved when the dispersed nodes of a network of small (and alsoperhaps some large) forces can converge on an enemy from multiple directions,through either fire or maneuver. The overall aim should be sustained pulsing -Swarm networks must be able to coalesce rapidly and stealthily on a target, thendisserver and redisperse, immediately ready to recombine for a new pulse.


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Doctrine of Spiral Swarms

• To defeat an already networked force – which acts through swarming – we need to develop very complex Spiral Swarms – Swarming the Swarms Doctrine


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Crafitti Consulting

Crafting innovation together . . .

www.crafitti.com

Navneet Bhushan ([email protected])

124

http://www.crafitti.com/

nco role in battlefield management

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