1. 19ISMOR C2IS – A Novel Method for Assessing the Value of Information Systems 27 – 30 August 2002 Kym Rawlings PGM Modelling & Studies Technical Consulting Group EDS Defence 27 – 30 August 2002 Kym Rawlings PGM Modelling & Studies Technical Consulting Group EDS Defence

2. 2 Overview Introduction The challenge The C2IS modelling approach –Component parts –Sum of the parts –Benefits (& pitfalls) of the approach Recent application areas The future Summary Q&A

3. 3 The challenge “For many years, the study of military command and control (including all the associated processes such as intelligence gathering and situation assessment) was placed in the ‘too difficult box’. …. Command and control is now seen as central to the enterprise of conflict. In dynamical terms, it could be argued that we have moved from the linear regime to the region of complexity – and we need to manage such complexity.” Moffat In other words, we need to move from the ‘too difficult’ box to the ‘we can do this’ comfort zone.

4. 4 The challenge Analysis of C2 systems is difficult: –C2 systems typically reside in formation HQs. It is not normally possible to observe such organisations operating in the combat environments for which they have been developed –Data collection has to be carried out in limited, partial and artificial situations, such as HQ exercises and equipment trials –The process is complicated by the limited number of formation HQs available for observation, and by the variability of their organisations and modes of operation

5. 5 The challenge Corps Division Brigade Battlegroup Increasing volume of interest Increasing information resolution Analysis of C2 systems is really difficult: –Different HQs operate at different levels –HQ areas of interests may overlap (and at different levels of interest)

6. 6 The challenge Any C2 analysis process must: –Facilitate the verification and validation of behaviours (such as system loading, task durations, resource conflict resolution) that are represented –Provide the means of determining such behaviours in complex, spatially distributed scenarios –Support the analysis of the impact of issues on overall operational performance and withstand formal scrutiny

7. 7 The EDS approach EDS have been involved in C2 system research for the past 20 years Research has proved that a C2 process model approach based on control theory provides effective insights into factors governing the operation of such systems Research has covered how process models can address geographic constraints at multiple levels and link to battle outcome to support equipment investment decisions A close working relationship with Dstl Land Systems

8. 8 C2IS – the basic components I C2 process model C2 system model Battle model CLASSPetri Nets

9. 9 What is a Petri Net? A Petri Net is: –“A collection of directed arcs connecting places and transitions” –“A condition/event graph, where places are conditions and transitions are events”. Petri nets contain four basic components: –Transitions (vertical rectangles) –Places (circles) –Directed arcs connecting Places to Transitions and vice versa –Tokens (small circles) which define the state (marking) of the net

10. 10 A simple Petri net Engine startedAt car Select gear In neutralEnter carIn car Ready to go Select neutralStart engine Restart engine Legend: Place Directed arc Transition Token

11. 11 A more complicated Petri Net – Brigade Targetting nonHPTs(2) tgtinfoshortfall(HPT) tgtinfo tgtinfo wpn&tgtcomb`ns(2) tgtingdataHPTs(1) wpn&tgtcomb`ns engagementfailed tgtinfo tgtinfoshortfall(urgent) othertargets(2) wpn&tgtcomb`ns(3) tgtinfoshortfall(nonHPT) wpn&tgtcomb`ns(1) non-HPTs(1) HPTs othertargets(1) starttargeting TestagainstTSS ChecktgtinfoFilterforHPTsTestagainstTSS Checktgtinfo Identothertgts(2) Retrievetgtinfo Identothertgts(1) TestagainstTSS Checktgtinfo

12. 12 A more complicated Petri Net – Brigade Targetting Resources

13. 13 A more complicated Petri Net – Brigade Targetting Routine Hasty Routine Hasty Urgent Alternative Routes Resources

14. 14 STARDIS - Simulation Tool for Analysing the Responses of Distributed Information Systems An event based dynamic system modelling toolset to model distributed information systems A strategic tool for: –Assessing how an organisation currently uses it’s information –Optimising an organisation’s information handling procedures and infrastructure (computers, communications and staff) Node based, allowing ready examination of factors such as: –Interaction between separate elements –System loading –Geographic constraints http://www.stardis.com

15. 15 STARDIS concepts Each IS consists of a set of distributed entities, which: –Have a local data base of its own information –Can gather local data from its environment –Can exchange information using messages –Can process information to generate more information –Can use information to take action e.g. move, or to order action e.g. instruct another entity to move Message passing is subject to communications network restrictions, e.g. capacity, availability Information processing, action and message generation is rule based and resource limited

16. 16 The STARDIS rule syntax No limit on number of rules for an entity Rule Triggers Conditions Reactions Resources Events, Time Pass, On Initialise Message Receipt, Data Changes e.g Tests on Stored Data e.g. Send Message, Move, Process Data

17. 17 Run time display of STARDIS model Message traffic loading Staff officer loading Physical connectivity Logical connectivity

18. 18 CLASS - Corps Level All-Arms Systems Simulation A multi sided model of the land battle, representing systems and operational concepts Systems represented through input data changes, rather than substantial code changes The basis of the model is the acquisition and treatment of targets for Blue indirect fire systems Following primary elements represented: –STA –Indirect fire C3I systems –Delivery systems –Rocket launchers –Guns –Ammunition –Casualties –Terrain –Met –Mines, barriers & obstacles –Routing –Movement

19. 19 CLASS - Corps Level All-Arms Systems Simulation Detailed representations: –Blue artillery munitions and delivery systems –Indirect fire command, control and communication (C3) –Intelligence –Target acquisition systems Less detailed: –Movement of both Red and Blue ground forces –Interactions in direct fire battles –Modelled in sufficient detail to provide a valid target stream

20. 20 CLASS model spine Delay in seconds between 290 - 410 BDE MAIN FDCBDE INT RECCE GUNS COY/SQN HQ FOO TANK Sqn/Inf Coy BG Main HQ FPCBG INT Delay in seconds between 390 - 510 Delay in seconds between 106 - 206 100 second delay DIV MAIN ARTY OPS DIV INT WLR RPV SR Delay in seconds between 164 - 284 Delay in seconds between 190 - 286 Delay in seconds between 206 - 326 ARRC MAIN ARTY OPS ARRC INT SOR SBOP Delay in seconds between 490 - 620 Delay in seconds between 334 - 454 DFDC MLRS 100 second delay Divisional Intelligence Picture (Picture reviewed every 2400 seconds) Report Received Call for fire report Arty Int. req. for fire Location reports Suppression reports Arty suppression reports Damage reports Acquisition reports Sightings reports Prob. Inclusion In Current Picture 0.91 0.96 0.84 0.90 0.96 0.70 0.90 Time Delay (secs) 920 900 840 900 920 Key Explicit communications Implicit communications Node - explicitly represented Node - implicitly represented DFDC ATACMS 100 second delay GUNS

21. 21 I C2IS – the sum of the parts C2 process model C2 system model Battle model Initial assessment of C2 process timings CLASSPetri Nets C2 process activity log Revised assessment of C2 process timings

22. 22 CLASS Compare to CLASS Use MOEs & MOPs for study Inconsistent Consistent C2IS delays C2IS MOPs CLASS event stream MOEs The C2IS Model - Petri Nets, STARDIS & CLASS working together Petri Net/STARDIS

23. 23 Benefits of the C2IS approach It permits analysis and validation of individual C2 system tasks with respect to staff and system resource utilisation, and the durations and products of individual activities It provides a means of aggregating task representations to allow analysis of C2 system loadings and task durations in complex, spatially distributed, scenarios It permits analysis of the influence of task duration on operational effectiveness and battle outcomes

24. 24 Pitfalls Data collection: –Process requires extensive combination of: Observation of HQ trials and exercises Interviews with domain experts Examination of other studies of military C2 system operation Analysis: –Analysis of this C2 system data and the development of the formation HQ process models requires the application of: A theoretical model of generic C2 operation A general understanding of the operational environment within which the formation HQs operate

25. 25 Current application areas FALCON –Next generation tactical area communications system –Dstl Land Systems are responsible for the COEIA, C2IS has been selected as one of the analytical approaches Organisational behaviour in military HQs: –Dstl Information Management are conducting research into features or attributes a HQ model would need to contain in order to adequately represent organisational behaviour –EDS are assisting with C2IS

26. 26 The future Representation of decision quality Real-time link C2 system Model Battle Model t 1 Decision Type d 1 Required at HQ h 1 t 2 Decision Type d 1 Required at HQ h 2 t 4 Decision Type d 2 Required at HQ h 1 t 3 Decision Type d 1 Available at HQ h 1 t 5 Decision Type d 2 Available at HQ h 1

27. 27 Summary C2IS combines the strengths of three sophisticated modelling approaches: –Petri nets provide the means of defining and checking C2 processes by: Statically validating process models Dynamically verifying the process models –STARDIS represents the C2 features of the system under evaluation: Checks that the operation of the battle model is valid Keeps the battle model fast running –CLASS: Provides the means of testing the C2 system in user-defined scenarios C2IS provides a truly novel method for assessing the value of Information Systems Have we reached the ‘we can do this’ comfort zone? … not yet...

28. Questions

29. eds.com Contacts: EDS:Kym Rawlings, kym.rawlings@eds.com kym.rawlings@eds.com Steve Brooker,steve.brooker@edl.uk.eds.com Dstl:Tony Usher,apusher@dstl.gov.uk dstl.gov.uk Copyright © 2002 Electronic Data Systems Corporation. All rights reserved.