Didier Perdu, Alexander H. Levis. C3I Center, George Mason Universiry. Fairfax,
VA 22030. Abstract. The process of using Colored Peni Nets (CPNs) to model.
June 1993
GMU/C3r.136-P
METHODOLOGY OF EVALUATING NAVY'S COPERNICUS ARCHITECTURE USING COLORED PETRI NETS Yan-Shek Hoh - The MITRE Corporation Didier M. Perdu - George Mason University Alexander H. Levis - George Mason University
A METHODOLOGY OF EVALUATING NAVY'S COPERNICUS ARCHITECTUREUSING COLOREDPETRI NETS Yan-Shek Hoh TheMITRE Corporation McLean,VA 22102 Didier Perdu, Alexander H. Levis C3I Center,GeorgeMason Universiry Fairfax, VA 22030 Abstract The processof using ColoredPeni Nets (CPNs)to model andevaluatea largemilitary C3 architecturehasbeen investigatedby developinga methodologyandapplying it to a specificexample. The methodologyhasbeen illustratedusing a problemrelatedto "warrior pull" of information in the Navy's Copemicusarchitecture.The softwareusedto implementthe CPNswas Design/CPNru,u.riion 1.9. Themodelwasconstructed from existing infomution on battle group tactical infonnation flows, and functional decompositionof the Copernicusarchitecturecomponentsimplementedalloat andashore.The resultssuccessfullydemonsnatedthe effectof the "warrior pull" processwhenthedifference betweenthe tacticalpicturesashoreandafloatexceededa prescribedthresholdvalue.
1 Introduction
Commander(SEWC). The influenceof SEWis so wide sweepingthat ordinarymodelingmethodsmay not of its impactsin the contextof the supportthe assessment Navy'sCopemicusarchitecture.Navy plannersneednew analysistechniquesto investigatenew large C3I architectureandtheSEWrequirements. This paperpresentsa modeling techniquewhich has of large the potentialto provide a quantitativeiNsessment C3I systems.The smdydemonsraFsthatexecutable modelsof a largeC3I architecturesuchasCopernicuscan be constructedusing CPNs. The useof Petri Nets as a modelingtool to representselectedC3I functionsand their interactions wasrecentlydemonstrated [1]. This study involvesa broaderinvestigationusinga wide rangeof proc€sses includingdatafusionat theCCC andtheTCC, exchangeof tacticalpictureinformation,and the "waffior pull" of infonnation. The methodologyis illustrated usinga particularproblerr relatedto the tacticalpictures generatedat theTCC and the CCC, respectively. Emphasisis on the informationpulling process.
Architecture In August 1991, Copernicus theNavy's emergedto providearchirccnrral,technologicaland progranrmaticdirection for all Navy Command,Control, Communications,Computer,and Intelligence(C4I) programs.The Copernicusarchitectureis an interactive frameworkof four pillars: Global InformationExchange System(GLOBIXS), TacticalInfomtationExchange System(TADXS), Commander-in-Chief(CINC) CommandComplex(CCC), andTactical Command Center(TCC). Thesepillars supportthe flow of infonnation amongnaval forcesafloat andashore. The Copemicusarchitecturespecifically supportsthe SpaceandElecronic Warfare(SEUI)missionto conrol anduseresourcesneededto successfullyconduct informationwarfare. This architectureprovidesthe baule force commandersassetsto support"warrior pull" information flows. The asse8aremanagedby the SEW
An outline of the Petri Net theory is presentedin Section2. It providesthe technicalbackgroundneededfor discussingthe model in the latter part of the paper. Section3 givesa brief overviewof theCopernicus architecture.Section4 presentstheCPN modelof the Navy'sCopemicusarchitectureanddescribesa methodologyfor evaluatingit. Includedarethe model assunptions,test scenario,outline of the model,and two illustrative examplesof model execution. Section5 thestudyresults. sumnrarizes
2 Petri Net Theory and Application A Petri Net is a graphicalandmathematicaltool for modelingandanalyzingsystemsthatmay have andnon deterministic concurrent,asynchronous,
characteristics.Itprovides an intuitive and visual descriptionof the systemand its behavior. It also allows for the analyticevaluationof the behavioralandstructuml propertiesassociatedwith the system.This section outlinesthe Peri Net theoryand discussesthe featuresof CPN in the contextof the problem to be modeled.
presenceof conflict denotesthenon deterministic characteristicof the model. It is the modeler's responsibilityto detectits presenceand !o implement appropriaterules to resolveit.
2.1 Ordinary Petri Nets An ordinaryPeri Net is a directed,weighte( bipafiite graphconsistingof two kinds of nodes:placesand transitions. Placesrepresentconditionsor resourcesof the systemand areindicatedby ellipsesor circles. Transitions representeventsor processesof the systemandare indicatedby rectanglesor boxes. A tokenresidingin a placeindicatesthe presenceof dataor the satisfactionof a conditionnecessaryfor enablinga transitionrepresentinga process.An arc representsan input or output relationship betweenaplace and a transitionandis drawneitherfrom a place to a fansition or from a transitionlo a place. The thenecessary expressioninscribedon an arc characterizes numberof tokensrhatmust be presentat the places connectedby the arc to eachtransition. An initial marking is the initial distribution of tokensin the placeof the net. Presenceof n tokensin a placeindicatesthat therearen dataitems or resourcesavailablein that condition. A marking characterizesthe stateof the system or the Petri Net. Behaviorof a systemcanbe describedin termsof the systemstatesand their changes.A stateor marking in a Peti Net is changedaccordingto the transitionor firing rule: a transitiont is enabledif eachinput placepi of t is markedwith at leastw(pr, t) tokens,wherew(pr, t) is the weight of the arc from p, to t. An enabledt may or may not fire dependingon whetherthe eventactuallytakes place. Firing of an enabledt removesw(pi, t) tokens from eachinput placepi of g and addsw(t, po) tokensto eachoutputplr.e po of t wherew(t, po) is the weight of the arc from t to po. In Petri Net formalism, the weight of an arc without label is equalto unity. An exampleof the transitionrule is shownby Figure 1. Two tokensare availablein the input places p1 and p2. Transition t is enabledsincethe numberof tokensin all input placessatisfiesthe associatedarc expressionsas shown in Figure 1(a). After firing g the marking will changeto the one shownin Figure 1(b). Transition t is now no longer enabled. A set of transitionsfiring concurrentlyis called a step. Conflict ariseswhen a placeis input trotwo or more enabledtransitionsbut containsan insufficient numberof tokensto let all the transitionsoccur within a step. The
(a) The rnrking beforefiring t
(b) The nnrking after firing t
Figure l. An Illustrationof TransitionRule. 2.2
Colored Petri Nets
Tokensin ordinary Petri Net theoryare indistinguishable. firing of a ransition The enablementand subsequent dependsolely on the existenceof tokensin all the input places. The representationof complexlogical operations with ordinary Petri Nets, while feasible,leadsto very largeandcomplexnets. One way of handlingthis problem is to introducedistinguishabletokens characterizedby setsof values. A tokenwith a specific valueis saidto be a coloredoken andthe valueis referred to asa color. The collection of valuesor colors that a given tokencan take on is call a color set. Eachplaceis associatedwith a color setwhich definesthe colorsof tokensthat canresidein a particularplace. In general,the tokencolor canbe more complex,e.9.,an arrayof several componentsor attributeswhile eachattributecan takeon valuesor colors from a specificcolor set. The assignment ofcolors to the variablesin the arc expressionsis called binding. Oncethis definition is made,arcscan thenbe annotatedor inscribedto indicatethe conditionsunder which tokensof particularcolors canenablea tmnsition. In CPN, an arc expressionmay havefunctions, variables,booleans,or the usualoperations. It the numberandcolor of tokensthatenablea characterizes transitionor are generatedby the firing of a transition. A transitionis enabledwhenits inputplace(s)containsthe necessary numberof input tokensin theright colors. A specihcprocessmay be assignedto a transitionby associatingan appropriatecodesegmentwith it. In addition,for eachEansition,a guardcanbe specified. This is a booleanexpressionrestricting the conditions underwhich the transitioncanoccru. When a guardis absentfrom a transition,it is the equivalentof being true. An enabledtransitionmay fire, wherebytokensare removedfrom theinput placesandnew lokensareaddedto the outputplaces,zrsspecifiedby the associatedarc expressions.The numberand color of thesetokensneed not be preserved.
The softwareimplementationof ColoredPetri Nets usedin this gludy is Design/CPNru,version1.9. In T M ' Design/CPN"", the color setsandassociatedvariablesare definedin a "GlobalDeclarationNode" anda "Temporary DeclarationNode." Inscriptionscanbe placedon arcsand guardfunctionsin Eansitions.They arebasedon "StandardMetiaLanguage"(SML), a functional prograruninqlanguage.Detailedmaterialson Design/CPN"". version 1,.9,canbe found in Reference2. 2.3
Applicability to Present Study
CPN modelsare not only a meansfor graphically desoibing the interactionsbetweenprocesses and the correspondinginformationflows, they arealsoexecutable, i.e., they can be usedto simulatethe operationsof the modeledsystemandto collectdatafor perforrnance analysis. The model to be describedin Section4 will be usedto showthe perfomranceof the "warrior pull" of information,asrepresentedin the Copemicusarchitecture, in generating/improvingthe tactical pictures. Sincea CPN modelis an executablemodel,it requiresthat all relevantinput be specified. The level of detail of the materialdependson tl|e goalof the model. As such,CPN is a sEongknowledgeelicitationtool for developingneededinfomration. This featureis particularly desirablewhenlooking at new targeC3I architecture,suchasCopernicus,to sort out the data requirements.
3 Brief Overview of the Navv's Copernicus Architecture In November1989,the Navy adoptedSEWasa warfare mission. The Copernicusarchitecturewas implemented to supportthe SEW mission. SEW functions afe to be perfomredby a warfarecomrnnder, the SEWC,in the CompositeWarfareConrnrander(CWC) organizational context,reportingdirectly to the afloat Battle Force Commander.Thus,SEWjoins the traditional warfare areasof Anti-Air Warfare(AAW), Anti-Submarine Warfare(AS\{D, Anti-SurfaceWarfare(AS[IW), Suike Warfare(STW),MineWarfare (MIW"),andAmphibious Warfare(AMW), erc. The SEWC missionstatement incorporatesall aspectsof electronicwarfarepreviously perfomredby theElectronicWarfareCommander. Furthermore,SEWC is also responsiblefor elecfromagnetic specfum and space-based systems management. Figure2 illustratesthe four pillars of Copernicus: GLOBXS, CCC,TADIXS, andTCC. The purposeof this sectionis to presenta brief overview of the CopernicusC4I aspectof the architecturewith emphasis on the tacticalinformationexchangeprocessbetween elementsashoreandafloat. The following descriptionsof the Copernicuspillars will be limited in scopeto that neededfor an understanding of the CopernicusCPN model. Reference3 givesa moredetaileddescriptionof theNavy Copernicusarchitecture.
The flexible graphicapproachof CPN and the useof SML makeCPN an excellenttool for studyinglogical propertiesof syst€mssuchas their coordination. The "warrior pull" problemto be modeledis primarily a complicatedcoordinationprocessbetweenthe CCC and TCC. As such,CPN is an analysis0oolsuitablefor the presentstudy. of system CPN modelsare multilevel representations structures.Submodelsor pagescombineinto a hierarchy to form a singlemodel. Node fusion allows modelen to logically fold a setof nodesacrossthe submodelsor pages into a single nodewithout having to refer to them graphicallyas a single object. This facility makesit easy to describeresourcesharingandsynchronizationacrossthe hierarchy. To specify the initial statefor an executionof a hierarchicalCPN, the usermust define a setof starting pages,calledprime pages. If a pageis not declaredasa prime page,it will not be includedin the executionof the model. This featureallows the modeler!o structurethe testenvironment,i.e., the warfareareasandGLOBIXS to be includedin an execution,with greatflexibility.
ffi
r^0x
TdH cormmd ms
Figure 2. Four Pillars of the CopemicusArchitecture. 3. I
Global Information Exchange System (GLOBTXS)
virtual nets GLOBXS is a collectionof shore-based which will provide tactical information to the command centers.They providea commandandcontrol infrastructue to supportthe variouswarfaremissionsthat dependon shore-based sensors.The GLOBXS allows aggregationof shoreanalyticnodes,sensornodes, laboratoryandresearchcenters,andotherselectedactivities ino virtual networkssupportingcommunitieswith courmoninterests.
3.2
CINC Command Complex (CCC)
The CCC is functionally a complex supportingsensor da0afusion, targetuacking,commandandcontrol (C2) messaging,and tactical intelligenceprocessing.It is supportedby a virmal network imposedover metropolilan areanetworksQ\dANs). It ties togethercornmandand staff organizations.Non-organicsensordatais transmittedto the CCC throughGLOBXS. To this end,CCC actsas an "anchor"for dataandinfomlation from the GLOBXS. 3.3 Tactical Command Center (TCC) In Copernicus,TCC is a genericterm that signifies the combatC2 cent€rsof the tacticalcomrnanderandhis units. It providestactical displays,integratedinformation numagement,and accessibilityto tacticalcommunications to supportNavy war fighting missions. It supportsthe requisitebattle connectivityto afloat naval forces,joint force comnandersand the CCC. To facilitate the disseminationof tactical infonnation, local areanetworks (LANs) afloat will be usedto providehigh-speed connectivityamongthe TCC spacesonboardplatfonns. 3.4
Tactical Information Exchange System (TADIXS)
TADIXS provide virtual networksamongthe forcesalloat as well as linking betweenthe CCC and TCC. They are operationalconstructs,not communicationsnetworks,and areestablishedat the requestof andin the mix desiredby tbe tacticalcomuuurder.Operationally,the instanianeous capacityof the TADIXS is conrolled by the SEWC. The functionsof TADIXS, includingthe communications allocationand reallocationof the communication resources,will be supportedby the Communications SupportSystem(CSS). CSSprovidesthe technical systemsneededby the SEWCto controlC4I systems.
4.1 Model Framework The four pillars of the Copernicusarchitecturewere shown in Figure2. For simplicity, let us assumethat the nonorganicsensordataare sentonly to the CCC and the organicsensordataaredeliveredonly to thebat0egroup platfonns. The model focuseson CCC, TCC, and TADIXS. GLOBXS will be freatedasa resourcefor transmissionof non-organicsensordata. Emphasisis placedon the casewhenboth the CCC and TCC are interestedin the samelevel of detail within the tactical picture.
4.1.1 ccc On the shoreside,themodel beginsat the interfacewhere GLOBIXS dataenterthe CCC networks. The non-organic sensorda[aconsideredis imagery,signalintelligen@,and acoustictargettracks. Functionally, the CCC can be viewedashavingan organizationthat consistsof centers which processthe input GLOBIXS dataand input TCC data. Thesecentersincludethe SEW center,the ASW center,theFleet Intelligencecenter,and the Cryptologic SupportGroupcenter. In each@nter,thereis an anchor desk(GLOBD(Sanchordes$ which p(rcessesits input dataandforwardstheresultsto the OWC for tactical (theater)picture generation.The tacticalinformationflow in the CCC is illustratedin Figure 3.
to CSSfeaturesmulti-mediaandmedia-sharing provide communicationsflexibility, survivability, connectivity,andefficiency. More detailson CSScanbe found in Reference4. Figure 3. CCC Tactical Infonnation Flow Diagram.
4 Model Description This sectiondescribesa structuredmethodologyof modelingandevaluatingthe Copemicusarchitectuebased on the fonnalism of CPNs. The methodologyis illustratedusing a particularproblemrelatedto the tactical picturesgeneratedbythe CWC andOperationsWatch Center(OWC), respectively. Emphasisis on the data pulling process.
4.1.2 TCC On the afloat side,the modelbeginsat the interfacewhere organicsensordataentera platfonn'sdataprocessing segment.Figure 4 schematicallydepictsthe tactical informationflow in the contextof an aircraft canier (CV) battlegroupwhich in tris caseconsistsof oneCV and one cruiser(CG). Using the frameworkfor a TCC operationalmodelgiven in Reference3, the warfareareas to be includedin themodel are SEW, AAW, ASIJW, and
ASW. WarfareCommandersonboardthe CV arethe SEWC, ASUWC, and ASWC, while AAWC is onboard the CG. Also onboardthe CG are the subordinate commandersfor ASW and ASUW.
cY
Figure 4. TCC Tactical Information Flow Diagram. Eachwarfarearcacorrurumderwill combinethe availableorganicsensordataand fuseit with information he receivesfrom the CCC, to form the warfarearea tacticalpicture. He will also forward the result to ttle CWC for unified tacticalpicturegeneration. Operationally,the unified tacticalpicturewould be disributed to eachwarfareareacommander.But this processis not consideredin thepresentmodel. 4.1.3
Query and "Warrior Pull" of Informatlon
SEWCresponsibilities,functions,and organizational relationshipsare still evolving, and theproceduresfor "warrior pull" of infomrationhavenot beendefined. theproceduresdescribedhereinarebased Correspondingly, on the most up to dateinformation availableto the authorssupplemented by reasonableoperational assumptions. At aprescribedtime, the CWC and OWC exchange information about their tactical pictures:the CWC Eansmitstheprocesseddatacorrespondingto his actical picture to the OWC, and vice versa. Upon receivingthe OWC processeddata the CWC comparesthem to his own tacticalpicture. If the differenceis greaterthana preset threshol4the CWC generatesa querymessageandsends it to the CCC. In the presentmodel, we assumethat the CWC performsthe comparisonof the tacticalpicturesand sharesthe result wirh the sEWC. The sEWC is responsiblefor allocating/reallocatingthe comnunication resourcesto supportdatapulling as the situationrequires. When the CWC sendsa query messageto the CCC, this requestis frst sentto the OWC and,through the CCC networls, is disseminatedto the appropriatecenters.
The anchorsofthese centersthenrespondby sendingtheir respectiveprocesseddatato the TCC. In the model,these respmdingprocesseddataaresont,tbroughappropriate TADD(S, to the TCC LAN wherethe dataarethen distributedto therelevantwarfarecornmanders.Upon receivingtherespondingprocesseddataftom the anchor(s), the warfarecommanderwill fusethesedatawith the incomingorganicsensordataandsubordinatep,rocessed datato produceanew setof warfarccommanderprocessed data. Similarly, the OWC comparesthe receivedprocessed datafrom the CWC to his own iactical picture. The result of the comparisonis sharedwith the SEW Center. If the differenceis greater&an a presetthreshol4 the OWC generatesa querymessageand sendsit to the TCC. The SEWCenteris responsible for the shore-to-ship communicationresourceallocation/reallocation.Upon receivingthe respondingprocesseddatafrom thewarfare commander(s), eachcenterfusesthepulled datawith its incomingGLOBIXS non-organicsensordatato produce new processeddata. In this way, the CCC and TCC acquirethecapabilitiesto managethe tacticaldataderived from the non-organicas well asorganicsensors. 4.2
Model Assumptions and Scenario
This subsection describesthebasicassumptions usedin the model. They aremadefor the purposeof avoidingthe unnecessary complexitiesof the Copernicusarchitecture that arc not directly relatedto the presentstudy,yet still they are detailedenoughto allow us to illustrate the "warrior pull" processin a reasonablysimple scenario. Both the scenarioand the assumptionspresentedin the following subsectionsare usedfor illustration purposes. They are not parts of the limitations of CPN. 4.2.1 CALOW Scenario and Sensor Detection In the model, we assumethat the fusion nodeshavegood knowledgeaboutthe locationsof the friendly platfomrs andthat the friendly platformswill be filtered from the input databeforefusion takesplace. The scenariois one of contingencyandlimited objectivewarfare(CALOW) wherehostilesandneutralsconsistof four aircraft,two surfaceships,and two submergedsubmarines.We also assumetbat if a sensoris capableof detectinga certain type of threat,it will detectall instancpsof that tbreat type when they appearin the scenario. Table 1 showsthe non-organicsensorand GLOBIXS combinationsas well as the detections.Table2lists the organicsensorandplafomr combinations,by warfarearea categories,togetherwith the sensordetections.All sensorsareaddressed by their genericnames(radar, 1, sensor sensor2, etc.)and codenamesas usedin the
model. Explicit sensorparameters,suchasdataquality, operationallimitations, etc., arenot requhedfor this analysis. GLOBIXS Sensor Type
Sensor CodeName
Deteclion
2 strips
lrnagery
Salellite
IMAGERYnoT
SIGINT
HF DF
SlGlNTnor3
4 aiEran
Sensor 1
SlGlNTnorl
2 ships
Sensor 2
SlGlNTnor2
2 subrnarina
ASW
tss
ASWnor
2 strips+ 2 grbnnrines
SEW
Sensor1
SEWnorl
Sensor2
SEWno12
4aitcraft+ 2 strips 2 subrnarines
Table 1. Non-organicSensorDetection.
measuredby the ageof the dataitemsto be fused. Moreover,this measureis independentof the specificdata fusion algorithm. Considerthe following example:a nodeperfomrsdata fusion basedon two streamsof input (unprocessed) sensor dataas shownin Figure 5. In the model only the newer dataitemsfrom eachinput will be consideredin formulating the measureof daa fusion. Let hi be the time associatedwith the n-th input source'smost recent dataitem with respectto the i-th fusion occasion(at time Tr). The measureof fusion for the datasheamsat, say, TU,is denote6bVQOand is given by the averagedageof the items involved.
Q6 = [(Tu- t16)+ (T6- t26)]| 2, which,in thepresentczne,is simply theaveragedtime delayof the mostrecentdataitemswith respectto the momentof fusion. f7
ivadaoAr{
sEw
Scnsor Typc
San$r Codc Namr
Deiecrbn
Dda D€dindbn
ESM
SEWorgl
2 thb3
Rads
SEWor!2
2 Bhpe
LAMPS
ASWorg2
2srbMinc
cv, cG
Tal
ASWorgl
2 subminG
cv. cG
ld dda dream
ard dda sfeam ASW
ASUW
AAW
Red{
ASUWorgl
2 ehpe
cv, cG
tsAR
ASUWorg2
2 !hih!
CG
ESM
AAWorgl
4 airdl + 2 lhps
Radal
AAWorg2
,l aiqd + 2 shh3
CG
Table2. OrganicSensorDetection. 4.2.2 Measure of Data Fusion Input datafor fusion nodescanbe put into two obvious or unfusodsensordata, and categories,unprocessed processedor fuseddata. It is also assumedthat all nonorganicsensordataenterthe CCC throughthe GLOBIXS, andall organicdataenterthe TCC from theTADD(S systemafloat. For simplicity, let us assumethat all the input sensor dataareusefulandaccurateat the time of detectionor generation.The measureof datafusion usedin the model is the cumulativeageof the data. The underlying reasoningfor adoptingthis measureis that at the moment whenfusion takespliace,morecurrentdataitemspoduce higher quality fusedproduct. Thus, to a first approximation,the quality of the fusedproductcould be
r2r
be
Figure5. Illustrationof Most RecentDataPointsfor Fusion. This resultcanbe generalizedas follows. Sincethe input dataof a fusion nodecan con0ainboth the (unprocessed) sensordataaswell astheprocesseddat4 it is necessaryto takethe quality or ageof the input data into consideration.To accommodatethis requirement, eachdataitem is thusassociatedwith an agepafirmeterq. If the dataitem is a sensordatum,the associatedage paramet€ris given the valuezero. If the dataitem is processed data theassociatedageis givenby theaveraged time delayof the parentdata(thosedataitems from which this processeddatawascreatedthroughfusion)plus the averagedvalueof the ageparametersof theparcntdata. Following the samenotationsusedin the aboveexample, if the ageparameterof the dataitem associatedwith time t . is denotedby qni, the expressionof the averagedageof the resultat, say,TU, is given by
Qu= [(Tu- tt6) + $ 6- tz6)* Qt6* cz6]I 2. has Notethatthemeasure algorithmthusdeveloped notexplicitlytakenthetlpe andnumberof targetsinto in a multi-targetenvironment" consideration. Therefore,
the algorithm is augmentedby information on the type andnumberof 6gets. Section4.4.2 discussesthe subject in more detail. 4,2,3
Tactical Information Bxchange between CCC and TCC
Recailthat the tacticalcommanderhascontrol over the typesand tbe volume of the non-organicsensor infonnation to be sentto him or his subordinatesand he alsodetermineswhen the datashouldbe sent. This feature is expressedin themodel in tennsof queryand "Warrior Pull" of information. In principle, any anchordeskcan exchangetacticalinformationwith any warfare commander.However,therearecombinationsbetween somecomponentsof the CCC (anchordesks)and some componentsof the TCC (warfarecommanders)that their dataexchangesplay a moreimportantrole thanthe others. Without lossof generality,we will only considerthese morecrucial infonnation exchangeschemesin the model. They aredeterminedbasedon the genenalfunctionsand requirementsof theindividual anchordesksandwarfare commanders.Table 3 showsthe datadelivery scheme from anchordesksto warfarecommanders.The scheme for datasentftom warfarecommandersto anchorsis presentedin Table4.
R"*
sEwc
sEw
X
lmagery
X
SIGINT
X
AAWC
X
x
ASW
ASUWC
ASWC
X
X
x
x
x
x
x
x
Datato Warfare Table 3. Anchor DeskProcessed Commanders.
.x sEwc
SEW
x
lmagery
SIGINT
X
ASW
x
AAWC ASUWC
X
ASWC
X
Datato Anchor Table4. WarfareCommanderProcessed Desks.
4.3
Modeling of Information Attributes
The softwareimplementation_gf ColoredPetri Nets used in this report is Desigr/CPNrM, version1.9. In . T M Design/CPN"", the color setsandassociatedvariablesare definedin a "GlobalDeclarationNode" anda "Temporary DeclarationNode." Inscriptionscanbe placedon arcsand aroundtransitions. The objectsthat appearon the tacticalpicture are representedasmulti-attributetokens. Theseattributes changeas the objectEaversesthemodel !o reflect the processingperformedby the system. The attributesof tokensaredefinedby color sets. The declarationof the colorsand the variablesassociatedwith the color setsused in the model are further discussedin the following subsections. 4.3.1 Sensor Data and ProcessedData (1) DetectionCategory(AIRCRAFT,SURFACE, SUBMARINE)and SensorType (SOURCE):Tables1 and 2 list the sensortypestogetherwith their respective detectionsin termsof the categoryand the numberof threats.They aredescribedby the first threeattf,ibutesof the information tokens,in the order of aircraft, ship,and submarine.The fourth attributedenotesthe codenameof the sensor.If thetokenreprcsentsa processedor fused da[aitem, this attributeindicatesthe nodethat performs fusion to producethis data. (2) Event Time (EVENTIME): The fifth attributeof the information token is the event time. If the loken is for a sensordatum,the associatedeventtime is the time when thedataentersthemodelboundaryasdescribedin Section 4.1. For organicsensordataandmostof thenon-organic sensordata(exceptthe ASW andimagerydata),theevent time is assumedto be the sameas the detectiontime (the time when the targetis detectedby the sensor). Sincethe focus of the model is on the effect of tactical information exchangewithin andbetweentheCCC andTCC, we will not, at this time, explicitly considerthe large delaysthat might be associatedwith the input non-organicASW and imagerydata. To this end,their eventtime usedin the modelwill be theadjustedvaluesafterthesedelays,if any, areremoved. In otherwords,asfar asthemodel is concerned,they will be Featedas if therewereno input delays. This simplification seemsplausiblewithin the objectivesof the presentmodel wherethe datapulling capability is of primary interestwhile explicit fusion algorithmsarenot involved. If the token is for a processeddatum,the associatedeventtime is the time whenthis item is producedfrom datafusion. (3) Age Attribute(AGE): This attributeshowsthe ageof thedata.
4.3.2
Tactical Picture Difference
In the OWC or CWC, the tactical picturesof the CCC andTCC arecompared.The resultsareexpressedby tokenswhosecolor is a 6-[rple (dmir, dnsuf,dnsub, SOURCE,tla, dtla) in the color serCOMPARE: - dtwir, dnsuf,arlddnsubarethedifferencein threat numbersof aircraft, ship,and submarine, respectively; - SOURCEis the organizationthat perfonnsthe picture comparison; - tla is the ageof the host tactical pictureprocessed datausedin the comparison; - dtla is the differencein aseof the two tactical pictues. 4.4
Modeling of Processes
This subsectiondescribesthe net segmentsthat model differentprocesses. 4.4.1
Generating Source Data and Employing Most Recent Data Items for Fusion
Figure 6 illusffatesa sensordatagenerationprocess.The text in italics aboveeachplacedefinesthe color set associatedwith that place,while underlinedtext gives the initial marking of the place. In the example,the sensor SEWorgl generatesone output every 30 time units, starting at the 10th time units from the beginningof the model executiontime. This dataitem is thenrepresented by a color token in place A and the attributesof this token arethenumberof aircraft detecte( numberof surfaceships detecte4numberof submarinesdetected"sensorgeneric name,time of datageneration,andmeasureof time delaylageof thedata.
by the input token as soonas a new token arrivesat the inputplaceB.
ildecajlil MEASURE
Figure7. Net Segmentfor Fusionof Most RecentData Items. 4.4.2 Data Fusion Figure8 illustratesthe fusionprocesswith inputs represented by tokensof colorsml, m2, andm3, respectively. This processperformstwo tasks. The first taskis to estimatethe numberof threatswhich is equalto the union of the threatsin the individual input data. The secondtask is to estimatethe ageof the resultant. These tasksareperformedby the functionsTrack3andMetric3, respectively. 1'Fusiono+1O'l
1' 1O+10 COIJNT
Figure8. Net Segmentfor the DataFusionProcess. Figure6. Net SegmentShowingSensorDataGeneration. Figure 7 showsthe net segmentthat implementsthe rule of employing the most fresh dataitemsfrom each input sourc.efor datafusion. Furthermore,the nodefusion is also illustrat€din the figures by designatingboth places A (in Figure 6) and B (in Figure 7) to be in the same fusion grcup FG A. In this way, A and B aretreatedas one singlenodeby the model. This facility is found to be very usefulfor describingresourciesharingand synchronizationacrossthe hierarchyor pages. PlaceC reprcsentsthebuffer betweenthe input andthe datafusion processand hasan initial token of color Meas-init in the color set MEASURE. It is seenthat the data item in C is alwaysthe most fresh one sincethe token in C is replaced
The fusion taskis modeledasa periodicalprocessand is activatedby a timed tokenin the color set FUSCOLOR.In the example,the first fusionprocess takesplaceat model time l0l with respectto the beginningof the model executiontime and the fusion processrepeatsevery 50 model time units. 4.4.3 Query and Information Pulling Figure9 depictsthe queryanddatapulling process implementedin the TCC. The OWC tactical picture processed datais receivedftom placeB andthemostrecent copy of the picture datais usedto comparewith the CWC tacticalpictureprocesseddata(from placeA). Transition
Tl representsthe processof comparison.The inscription of the Tl-to-D arc showsthe conditionsthat if thereis no datafrom the OWC, the comparisonis void asimplied by the token with value Meas_init. If the OVIC tactical pictureprocesseddatais available,the comparisonprocess
usedfor transmittingthe querymessagehasnot been definedin Copernicus.Thus in the model it is assumed that any convenientlink could be usedand theselinks are not explicitly modeled. Similar procedues apply to the CCC to the TCC queryand informationpulling.
MEASURE
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Figure9. QueryandDataPulling hocess from TCC to CCC. will evaluatethe picture disoepancies. In transitionT2, arecomparedwith presetthreshold thesediscrepancies values. The processis implementedthroughthe guard functions. In the figure, theseconditionsare that the numbersof a threattype arcnot equaland themeasuresof datafusion associatedwith the two tacticalpicturesexceed a value, say 10 in the example. If any of thesethreshold conditionsis satisfied,a query token with attributes (9,9,9,ORG CWCorg,9,9)is generated and sent,through is disseminatedto network and then TADIXS, to the CCC present, TADIXS to be At the the appropriate@nters.
4.4.4 Data Transmission through TADIXS Figure 10 showsthe tactical datatransmissionupon requestor query from the CCC to the TCC. Data from anchor(placeC) is sentto the TCC LAN (placeD) throughTADXS. When a query token, which hasthe CWC codenameas the SOURCEattribute value, is presentin placeA, it immediatelyreplacesthe initial marking tokenin place B that the guardfunction in the TADXS transitionnodeis satisfied.The TADXS transmissionis modeledasa periodicprocesswhose
perioddependson the link capacityand the amountof processeddatato be fonvarded. h the example,the first fransmissionwill takeplace,if query/datapulling request is activate4 at model time 102with respectto the beginningof the model executiontime. During the ffansrnission,one copy of the datafrom placeC is fonvardedto placeD. This transmissionprocessis repeatedevery 50 model time units. Similar procedures apply to the daa transmissionfrom warfarecommanders to the CCC networks.
Recall that the emphasisof this study is on investigatingthe feasibility of modeling Copernicus. As a rnethodof studyingthis feasibility, we modeledthe data pulling activity in responseto the discrepancybetweenthe tacticalpicturesgeneratedin the CCC and TCC. For simplicity, the scopeof the model is accordinglylimited so that oncethe datapulling function is activated,it will remainactive for the rest of the model executiontime. Basedon the parametervaluesdiscussedin the previoussections,two exampleruns of the modelhave beenmade. The criteria for daa pulling arethat the type andnumberof threatsin the two tacticalpicturesarenot equalor the differenceof thetwo tacticalpictureprocessed dataagevalues@PAGE) is greaterthana thresholdvalue, say10. 4.5.1 Example 1
Figure 10. Data Forwarding from CCC to TCC Upon
Query. 4.5 The Executable Model and Examples The Copernicusarchitecturemodel consistsof ten suburodelsorpages: onefor eachGLOBXS centerashore or warfareareaafloat. Oneadvantageof decomposingthe model into submodelsis that the usercan selectthe GLOBXS centersor warfareareasto be included.as appropriateto individual s$dies. In Design/CPNru,the selectionis doneby designatingthe submodelsor pages desiredasprime pagesin thehierarchypageof themodel. The hierarchypagelists the namesof all the submodels, the globaldeclarationnode,andthe temporarydeclaration node,if applicable. Beforeexecution,the modelprime pagesmustbe specified. In order to carry out the simulation,it is necessaryto specifythe valuesof the operationparameterssuchasthe sensordetectionperiods,the TADIXS link transmission periods,and the momentswhen datafusion takesplace. In the examplesreportedhere,hypotheticalvalueswere usedfor theseparameters.They wereusedonly for illusffation purposesand shouldnot be interpretedasa result of the limitations of CPN. In an actualstudy, the bestavailableinformation shouldbe usedinstead. For illustration purpose,the sensordetectionperiods usedarebetween30 and 4Omodel time units. If more than one sensorprovidesinput to a fusion node,the relative start timesof the sensorsareoffset by values ranging from 0 to 20 time units to indicatethe asynchronicityamongthe sensordetections.The transmissionperiodsassociatedwith the TADD(S links vary between50 and 100time units. The datafusion periodsare 100 time unis for the CWC andOWC, and 50 time units for the othercentersandareawarfarenodes.
In this example,only CWC, SEWC,OWC, and SEW Centerare includedin the model execution. The resultis summarizedin Table 5. The exchangeof tacticalpicture processeddatabetweenthe OWC andCWC startedat time t = 500 modeltime units. In the OWC, the tactical picturediscrepancyis evaluatedto be 4 in the numberof aircraft, zero in the numberof ships,2 in the numberof submarines,and 15 in the tacticalpictureprocesseddata trothe age. As a result,theOWC sendsa querymessage CWC to pull data. Similar proceduresapply to the CWC alloat. In the presenceof datapulling, the centersashoreand warfarecommandenafloatwould modify their respective tacticalpictureswith referenceto the pulled data. In Table 5, it is seenthat at t = 700, the picture differenceas evaluatedby the CWC is zeroin threattype and number andthe differencein pictureprocesseddataageis 12. The agedifferencebecomes6 when t = 800. As far as the OWC is concerne{ however,the tacticalpicturesareseen to be different in threattype andnumberuntil t = 800 whenthe differencediminishestrozero. The valuesof DPAGE are 25 and6 at t = 700 and 800,respectively. Becauseof the periodicity of the variousprocesses involved,DPAGE is not a monotonicfunctionof time. It varieswith time periodicallyin regions,remotefrom thebeginningof datapulling, wheretheresulthasbeen stabilized.In this example,theperiodis foundto be 600 time units and the root meansquare(rms) valueof DPAGE over oneperiod is about7 asevaluatedby the OWC. For the CWC, the period is found to be dso 600 time units and the nns of DPAGE is about 6.
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The SEWC hasbeenfound to be a singlepoint of failure in the contextof Copernicus. This importantissue mustbe investigatedin moredetail andproperbackup plansmust be formulatedby the Navy planners. In the courseof study,the fact that CPN is a strong lmowledgeelicitationtool for developingneeded infomntion hasbeenrecognized.During the model development,it forcedus !o fabricatean appropriatetest scenarioas well asto clarify the explicit coordination schemesamongand betweenthe componentsof the CCC andthe TCC in the contextof Copernicus.
Table 5. TacticalPictureDifference. 4.5.2
Example 2
In this example,all ten submodelswere includedin the modelexecution. The paftmetervaluesusedarethe same asthosein the lastexample.The resultshowedthat the OWC startedto generateandsendquerymessages to the CWC at t = 600 andbeganto receivethepulled dataat t = 700. Similar processeswere seenfrom the CWC to the OWC at the respectivemoments. For the OWC, the period of the valuesof DPAGE is found to be 600 time units while their rms valueis about 12. For the CWC, the period of DPAGE is found also to be 600 time units and the associatedrms value is about 11. The fact that the DPAGE rms valuesin this exampleare largerthan those in ExampleI agreeswith what one would expectsincethe infonnation flows aremuchmore involved in the present caseandthereforethedifferencebetweenthe two tactical picturesis likely to increas€accordingly. In fact, we havealso tried casesin which the SEWCnode wasexcluded,but thenthe datapulling processcould not be properly activated. This is due to the fact that without the SEWC functionality the TADIXS link capacity allocationfunction, which is providedby the SEWC,is missing. Thus,the SEWC is a singlepoint of failure in the context of Copernicus. Further investigationinto this importantissue,however,is beyondthe scopeof the presentstudy.
5 5.1
Concluding Remarks Conclusion
The feasibility of using CPNsto evaluatea large military C3I architecturehasbeendemonsra@dby developinga methodologyfor modelingthe Navy's Copernicus architectue. The methodologyhasbeenillustratedusing a problemrelatedto the datapulling processin the context implementationof CPNs of Copernicus. . T Thego-ftware M usedis Design/CPN"",version1.9.
The model wasconstructedfrom existing information on battle group tactical informationflows, andfunctional decompositionsanddescriptionsof the Copernicus componentsafloat and ashore.The model frameworkhas beenderivedftom the CV battlegroupand the TCC operationalmodel given in Reference3. The CALOW scenarioused!o drive the modelexecutionwhile hypothetical,wasbasedon reasonableassumptions. Tbe measureof darafusion basedon the data cumulativeage,augmentedby information on the number of eachthreattypedetected,hasbeenusedto establisha criterion for activatingthe "warrior pull" of infornration process. We haveillustratedthe potentialfor improvementsin tacticalpictureconsistencyresultingfrom the "warrior pull" process.In addition,theexecucability of the CPN modelandtheflexibility of constructingthetest environment(selectingthewarfareareasandGLOBXS for modelexecution)havealsobeendemonstrated.In the hierarchicalCPN formalism,the model wasdevelopedas ten submodels,oneeachfor GLOBIXS centerashoreor onefor eachwarfareareaafloat. Submodelsto be included in an individual modelexecutionwereselectedby specifyingthemas prime pagesin the hierarchypage. Basedon a setof hypotheticalvaluesof the model parzuneters, two exampleswerc prcsented.In the frst example,only the CWC, OWC, SEWC,and SEWCenter wereincludedin the modelexecution. The result successfullydemonstratedthe warrior pull of information processwhenthedifferencebetweentheOWC andCWC tacticalpicturesexceededtheprescribedthresholdvalue. The secondexampleshowedthecasethat involved all ten submodelsin the model execution. The warrior pull of informationprocesswasagainobservedasexpected. Furthermore,it wasnoticed ttratthe DPAGE rms values in the secondexamplewere largerthanthosein the first example. This result wasreasonablein that, the more complicatedinformationflows involved in the second examplewould makethe differencebetweenthe two tacticalpicturesmore likely to increase.
Most of the model assumptionsinvolved in defining the tacticalinformationflow requirementsarefraceableto the fact that the conceptsof operationwhich flow from the Navy'sCopernicusarchitecturehavenot yet been fimly established.Although the model in its cunent statushas severaloversimplifying assumptions,it has the potentialto leadto more realisticmodelsbasedon functionsand technicalrequirementsthat will emergeas Copernicusbecomesbetterdefined. The CPN model, with its graphicalinterfaceand analysistools, is a testbed that haslargepotentialfor futue moredetailedC4I systemmodeling application. 5.2
Some Potential Applications of the Model
The CPN model developedis consistentwith the operationalmodel given in the CopernicusPhaseI Document[3]. One featureof CPN is that oncethe model is developedonly minor modificationswould be neededto the net configurationfor studyingsimilar problems. Nevertheless,the tokencolors or attributes,the code segments,andthe arc inscriptionswould require appropriatechangeswhich, dependingon theproblem, may not alwaysbe trivial. Somepotential applicationsof the model areoutlined in the following: (1) To investigatethe strategyand impact of groupingthe CCC anchordesksto reducethe shore-to-shipdata rcdrrndmcy (2) To investigatethe properschemesof queryand "warrior pull" of information when the CCC and TCC are interestedin different levelsof detail within the tactical picnrre (3) To investigatethe trade-offsamongtacticalpicture bandwidth(i.e.,TADIXS link capacities), consistency, andrequiredmanninglevels (4) To investigateSEWCcommunicationresource allocation/reallocationstrategiesand their impacton tacticalpictureconsistency. 5.3
Directions for Further Research
The methodologyproposedin this model canbe improved along severaldirections. First, the datafusion algorithm could be modified to explicitly incorporatethe rargettypes anda srategy to nunageredundantor old information. Secondly,the sensordatacollectionperiodsand their relativedelayscould be modeledasa stochasticprocess. The model could be modified to includemore sensors, both in typesand in numbers,to reflect the complexity of actualtactical infomration flows. One challenge associatedwith suchefforts is that it would requirean efficient CPN implementationin order to maintaina manageableMea l,anguage(ML) file supportedby the CPN tool.
To accommodatethe variablenumberof platformsin a battlegroup, the CPN model could be designedso that it canhandleflexible or variablescenarios.The recpntwork by Lu [5] that modeledorganizationalstructuresas consistingof a systemlayer anda coordinationlayer seemsto offer someapproachesfor this modification. Acknowledgments The studywasconductedunderThe MITRE Corporation FiscalYear 192 IndustrialFellowsProgramat the GeorgeMasonUniversity (GMU) Centerof Excellencein Command,Conhol,Communications, andIntelligence. The authorsexprcsstheir appreciationto The MITRE Corporationand the GMU C3I Centerfor the accommodatingsupport. References tll
tzl t3l
t4l
151
R. F. Gaylord,S. L. Hearold,A. H. Levis, andS. A.Zajdi, December1991,Accuracyof a Battle TacticalPictrre, Proceedings GroupConunander's 1991Symposiumon C2 Research, NationalDefense University,Ft. L. McNair, Washington,DC. Meta Softwarepgrporation, 1991,ReferenceManual of Design/CPN"",Cambridge,Massachusetts. CopernicusProjectOffice, August 1991,The CopernicusArchitecture, Phase I : Requirements Definition,OP-094,Office of the Chief of Naval Operations,Washington,DC. CSSProgramOffice, 3 June 1991,System 1VlSpecification for the CSS,CSS-SSS-U-B R0C0(Draft),Naval OceanSystemsCenter,San Diego,California. ZhouLu, Iuly 1992,Coordinationin Distributed IntelligenceSystems,GMU/C3I-120-TH,George MasonUniversity,Fairfax,Virginia.