MONASH University 1/29 Computer Science & Software Engineering http://www.csse.monash.edu.au/ Boyd, Metcalfe and Amdahl - Modelling Networked Warfighting Systems � Carlo Kopp, BE(Hons), MSc, PhD � MIEEE, MAIAA, PEng � � Monash University, Clayton, Australia email: carlo@mail.csse.monash.edu.au � � � 2004, Monash University, Australia c � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 2/29 Defining the Problem � � � � � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 3/29 How to Quantify NCW Capability Gains? • Networked system ‘capability gain’ remains a contentious issue. • NCW advocates invoke Metcalfe’s Law and point to square law gains. • NCW critics argue that the number of engagements effected is the measure of system capability. • NCW trials and experiments do indicate measurable capability gains. � • How do these capability gains arise? � • How do we quantify these capability gains? � • How do we maximise these capability gains? � � • How do we minimise an opponent’s capability gains? � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 4/29 NCW - Counter-Air Environment Tanker Broadcasts Fuel State and Location Tanker Relays Link 16 Over the Radio Horizon Link 16 Combat Air Patrol Link 16 RAAF Defensive Counter Air NCW Example Link 16 Tanker � Link 16 Relay Platform � Link 16 Wedgetail AEW&C � Combat Air Patrol Wedgetail Transmits � Target Status and Commands to Combat Air Patrols � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 5/29 NCW - Strike Environment Tanker Broadcasts Fuel State and Location Tanker Relays Link 16 Over the Radio Horizon Link 16 Combat Air Patrol Link 16 RAAF Strike / Offensive Counter Air NCW Example Link 16 Tanker Strike Package Uses � Link 16 Relay Platform Wedgetail Threat Tracks To Evade Fighters and Bypass SAM Sites � Wedgetail AEW&C Link 16 � Wedgetail Transmits Target Status and Commands � to Combat Air Patrols Strike Package � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 6/29 NCW - Strike Environment SV PERSISTENT DATALINK/VOX SURVEILLANCE OK 00130 U.S. AIR FORCE 130 PERSISTENT BOMBARDMENT/ LOITERING BOMBER KILLBOX INTERDICTION OVERCAST PERSISTENT AUTONOMOUS SURVEILLANCE MUNITIONS � � � � � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 7/29 Quantifying Capability Gains � � � � � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 8/29 NCW vs Boyd’s OODA Loop • Boyd’s Observation-Orientation-Decision-Action loop presents an ab- straction to represent the event loop in an engagement. • Vast empirical evidence to support Boyd model - also applicable to biological ‘predator-prey’ interactions. • Players in the event loop Observe environment, Orient themselves to the situation by forming a model, Decide upon a course of action, and execute that Action . � • Intelligence Surveillance Reconnaissance (ISR) sensors and systems � collect information and a network distributes that information. � � • Networking accelerates OODA loops by accelerating the Observation- Orientation phases and improving situational awareness. � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 9/29 NCW - A Networked Fabric HOSTILE AIRSPACE FEBA FEBA CONTESTED AIRSPACE A NETWORKED ‘FABRIC’ � � TANKER TANKER � SURVEILLANCE PLATFORM � FRIENDLY AIRSPACE � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 10/29 The Incompleteness Problem • Representing capability gains using OO phases of OODA loop puts focus on information domain gains. • Real world systems combine information domain and kinetic domain elements. • Using only information domain elements neglects constraining sys- tem behaviours imposed by kinetic domain elements. • The result can be highly optimistic and unrealistic conclusions about � achievable capability gains. � � • Representative modelling of complete system capability gains re- � quires a complete model which can encompass both the OO and DA phases of the Boyd OODA loop. � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 11/29 Metcalfe’s Law • Metcalfe’s Law asserts that the usefulness or utility of a network increases with the square of the number of nodes in the network. • Empirically demonstrated on the WWW by correlating gains in sales revenue against number of nodes connected to the network. • Metcalfe’s Law is not a predictor of achieved utility, but rather an indicator of achievable utility . • ‘Utility’ is seen in terms of connectivity. � � • Widely cited as a measure of capability gain in networked warfighting � systems. � • Metcalfe’s Law contains no implicit mechanism to quantify time � domain behaviour in the system. � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 12/29 Metcalfe’s Law Metcalfe’s Law 1e+06 Metcalfe’s Law 900000 Number of Possible Connections [−] 800000 700000 600000 500000 400000 300000 � 200000 � 100000 � 0 100 200 300 400 500 600 700 800 900 1000 � Number of Network Nodes [−] � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 13/29 Metcalfe’s Law - Time Domain ISR FUNCTIONAL ISR USER INTERPRET/ NETWORK ISR MODEL DB SNS/PROC NK DELAY COLLATE TEMPORAL SNS/PROC NK � SNS/PROC NK DELAY VALIDATE SNS/PROC NK � MODEL SNS/PROC NK DELAY � OBSERVATION PHASE ORIENTATION PHASE � � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 14/29 Metcalfe’s Law Limitations • Implicit assumption that gains in connectivity produce gains in time domain performance. • Complex time domain dependencies in ISR system and network be- haviour not accounted for. • Network saturation and load effects not accounted for. • Effects of hostile jamming not accounted for. � • Metcalfe’s Law at best a useful predictor of bounds on capability � gain. � � � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 15/29 Kinetic Domain - Decision-Action • Completeness in modelling capability gains requires a kinetic do- main model which can encompass the Decision-Action phases of the OODA loop. • Establish what bounds exist on the number of engagements the sys- tem can produce within a defined time, with some bounded number of elements. • Decision processes involve delays since decision-makers often depen- � dent on inputs from superiors and subordinates, introducing queue- � ing behaviours into the system. � • Executing Actions involves sequences of events such as positioning � a platform for an engagement, also introducing queueing behaviours � into the system. � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 16/29 Kinetic Domain Constraint Example Queue for Transit to Queue for Transit to Runway, Takeoff Target Area Aerial Refuelling Station Orbit Station Await Targeting Directives Queue for Transit from Queue for Transit from Approach, Land Target Area Aerial Refuelling Station Strike Targets � � � SERIAL SERIAL SERIAL PARALLEL PARALLEL � WORKLOAD WORKLOAD WORKLOAD WORKLOAD WORKLOAD COMPONENT COMPONENT COMPONENT COMPONENT COMPONENT � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
MONASH University 17/29 Kinetic Domain - Decision-Action • In practical terms the system at the Decision-Action level involves complex mixes of sequential / serial / queueing behaviours, and some parallel behaviours. • How do we best model a complex mix of serial and parallel func- tions? � • Answer: exploit Amdahl’s Law used in supercomput- � ing. � � � � � Computer Science & Software Engineering Computer Science & Software Engineering Computer Science & Software Engineering
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