Auomaed Allocaion of ESA Ground Saion Nework Services Sylvain Damiani (), Holger Dreihahn (), Jörg Noll (), Marc Niézee (), and Gian Paolo Calzolari () () VEGA, Aerospace Division Rober Bosch Sraße 7, D-6493 Darmsad, Germany; Email: Firsname.Lasname@vega.de () European Space Agency, European Space Operaions Cenre Rober Bosch Sraße 5, D-6493 Darmsad, Germany; Email: Gian.Paolo.Calzolari@esa.in Absrac The ESTRACK Planning Sysem (EPS) operaionally plans he use of he ESAs ESTRACK ground saion nework. I uses an incremenal planning approach o successively build up he ESTRACK Managemen Plan using feedback provided by is user missions. The sysem is configured wih a specificaion of he user missions needs and he neworks consiuens capabiliies. The planning process maches boh elemens o creae a plan ha is free of conflics and serves he needs of all missions. To build he plan, a consrain nework is consruced from he dynamic inpu o he sysem and is configuraion. The nework is buil incremenally exploiing he periodic naure of he communicaion reques imings required by he user missions. The resuling CSP conains emporal binary consrains, linear consrains and disjuncions of binary consrains. Is consisency is checked in wo seps: firs he DTP (Disjuncive Temporal Problem) par is solved and hen he remaining linear consrains are checked using Linear Programming algorihms. Fuure developmens of EPS will include a more sophisicaed resource modeling and he inclusion of more missions and exernal users. Advanced feaures like acive consrains and global opimizaion are conceivable. The ESA ground saion nework (ESTRACK) The European Space Agency (ESA) runs a number of ground saions o suppor is own missions and he missions of indusry conracors. 8 saions owned by ESA plus 3 cooperaive saions form he basis of he Esa TRACKing nework, ESTRACK. I also includes conrol and communicaion faciliies. ESTRACK currenly suppors 0 operaional ESA science missions. I provides services for daa downlink and he uplink of commands o saellies in orbi. In addiion o he Copyrigh 006, American Associaion for Arificial Inelligence (www.aaai.org). All righs reserved. regular ESA missions, ESTRACK suppors requess from exernal users (e.g. NASA). The mission s requess for saellie-o-ground communicaion are coordinaed for he ESTRACK nework as a whole. Unil now planning and scheduling of ESTRACK was done manually, suppored by a se of ools. The SCUT (Spacecraf Commimen Uilizaion Tool) is an analysis ool ha was used o prove he capabiliy of ESTRACK o suppor a se of missions. A se of rules defined he missions communicaion needs. The rules were applied o build a saring ground saion allocaion plan. They had o be configured o ensure he producion of a conflic free plan. Auomaed conflic resoluion or inelligen search algorihms were no used. The saring plan was loaded ino a scheduling ool, where an operaor had o edi i. The ool was hen used o generae he saion schedules. The planning as i was performed covered he needs of he ESTRACK nework. In he fuure, more missions will have o be cared for and he nework will grow by he number of saions. In order o coordinae his growing number of users and providers efficienly, an Auomaed Planning Sysem is called for. An auomaed sysem using an inelligen planning algorihm is able o exploi a flexible assignmen of communicaion services o user missions. In he following secions of his paper, a deailed problem descripion is presened. Once he scene is se, a model is demonsraed ha suppors he soluion of he given planning problem. Algorihms ha are used for he soluion of he planning problem are discussed and firs operaional resuls are presened. Finally plans for he fuure developmen of he sysem are discussed. Planning he ESTRACK nework An Auomaed Planning Sysem can cope wih he fuure demand of ground saion planning. This planning sysem is called he ESTRACK Planning Sysem (EPS). The planning sysem has o dynamically assign he missions requess o services ha ground saions offer. Insead of
assigning a ground saion o a mission, he services, a ground saion can offer, are idenified and parameerized. Any mission ha is using he ESTRACK nework may reques hese services. This adds flexibiliy and robusness o he planning process. The sysem is flexible enough, so ha a new mission or ground saion can be added by changing he sofware s configuraion daabase. The sofware will find a ground saion ha fulfills he communicaion requiremens of he new mission. Upon he unavailabiliy of a ground saion he sysem should be robus enough o find an alernaive saion wih he required specificaion. The ESTRACK nework suppors differen ypes of missions ha have very differen communicaion needs: Earh observaion missions wih frequen shor (several per day) communicaion periods. Missions on highly ellipical orbis (asronomy) wih long infrequen communicaion periods. Missions siuaed in one of he Sun-Earh Lagrange poins wih daily repeaed communicaion. Inerplaneary missions wih very specific needs and feaures (long one way ligh ime). Planning sraegies have been developed ha can cope wih hese very diverse communicaion requiremens. EPS defines for each ground saion a se of services i offers o he user missions. Some of he services may be muually exclusive (hey canno be used a he same ime) ohers may be used in one or several insances ogeher wih oher services. An example of his would be ha one mission uses a saions anenna and online equipmen o command a spacecraf while a couple of oher missions rerieve recorded daa from he same saion using is backend equipmen. The underlying resource model is par of a fuure developmen and is discussed in he las chaper of his paper. The firs implemenaion of EPS assumes an exclusive usage of one ground saion per mission in he same ime slo. This amouns considering ha each saion has exacly one complee communicaion processing chain (e.g. one anenna, one I/F equipmen, one baseband equipmen ) and ha all he services of his chain are exclusive. Wha s more, hose services are booked simulaneously when a mission books he saion. Sysem Conex The EPS [0] is one of he hree elemens of he ESTRACK Managemen Sysem (EMS) []. The EMS is one of he building blocks of ESAs EGOS iniiaive. The Esa Ground Operaions Sofware EGOS includes sofware sysems covering all relevan ground sysems of a space mission (see: hp://www.egos.esa.in/poral/egosweb/index.hml). The ESTRACK Scheduling Sysem (ESS) uses he planning producs of EPS o generae ground saion schedules from. The ESTRACK Conrol Sysem disribues schedules o he ground saions, sars and sops hem and moniors heir execuion. The exernal Inerfaces o he EMS are shown in Figure and explained in Table. EMS User Fligh Dynamics Mission Planning File Server Proxy 4 Exernal Provider (scheduling office) Forma Converer 3 5 EMS Operaor Posiions Planner MMI EMS ESTRACK Planning Sysem Online MMI Planning Producs 7 ESTRACK Coordinaion Sysem ESTRACK Scheduling Sysem SMF 6 Mission Operaions Cenre ESTRACK Ground Saion Communicaions Nework Managemen Figure he EMS in is operaional conex Table Exernal inerface o EMS Submission of mission requess and dynamic mission defined daa (even files) Rerieval of views of he ESTRACK Managemen Plan (EMP). Transmission of schedules and/or service insance configuraions. 3 Oupu of relevan porions of he ESTRACK Managemen Plan; Inpu of plans received from he exernal provider. 4 Inerface depending on he exernal provider, for he Deep Space Nework (DSN). Includes submission of he long erm reques and recepion of Saion Allocaion Files (SAF) and Seven Day Schedules (SDS). 5 Transmission of service insance configuraions. 6 Schedule disribuion, monioring and conrol. 7 Operaional saus informaion exchange. The inpus o he EPS are configuraion daa and even files, as well as requess and availabiliy plans from exernal users. The user missions are configured in a Mission Model ha ailors heir communicaion requiremens. In he Ground saion Model he capabiliies of ground saions are sored. The dynamic inpus o he sysem are even files which conain mission specific ime markers needed o aach aciviies o. These markers mainly denoe he visibiliy of ground saions bu may also express he imings of any oher even relevan o a mission (e.g. an operaor shif or an illuminaion condiion) The EPS produc is he ESTRACK Managemen Plan (EMP). Excerps of he EMP are called plan-views. Planviews are sen o he user missions as feed-back and should be inerpreed by heir mission planning sysems as saion allocaion plans. They are also used by he ESS o creae he saion schedules.
Planning Process The planning of he EMS operaions is an ieraive process beween he user missions and he EPS. Evens Fligh Dynamics Evens/ Refine Planning Session Commi Frozen EMP Missions Time Plan View Plan View Figure EPS overall planning cycle Figure shows in deail how he planning process sars wih he recepion and preparaion of evens from he missions and is fligh dynamics sysems. From his poin on, he figure depics an inward direced spiral, where he ime poins inwards and he mauriy of he EMP also increases on he inwards direcion. On updaes o even files he cycle can be resared a his level. The presence of even files allows for a firs planning session and an updae of he EMP. A planning session is one run of he rules and algorihms described laer in his paper. The resul of a planning session is a poenially incomplee se of aciviies which are added o he EMP. Plan views are creaed as defined by he missions and made available o hem. The missions can hen send refinemens. Upon recepion of refinemens, he EPS may perform a replanning of he affeced ime range and repor he resul back o he missions in plan views. There may be several refinemen cycles a his level (or none). As a las sep, he missions commi he communicaion segmens he EPS has planned for hem. Sessions are frozen (i.e. he sessions imings canno be alered anymore) by he EPS, a a defined ime before heir scheduling. Given his planning cycle i is obvious ha he planner has o cope wih an incomplee se of dynamic inpu daa. As a consequence he EMP canno be compleed for all user missions and is herefore coninuously evolving. I conains ime ranges where i is compleely planned and areas where i is planned only for some of he user missions. Addiional planning sessions complee he parly planned areas. Previously planned aciviies have o be impored ino a new planning session, because hey consrain he resource usage for his session. Planning Objecive and Sraegy The aim of he planning process is o produce a valid plan. A valid plan implemens he Mission Agreemens for all missions on a finie planning period. The curren requiremens for he ESTRACK Managemen Sysem do no call for he creaion of an opimized plan. There is no need o find and evaluae several plans as he firs valid plan can be chosen. A number of crieria guide he decision and conflic resoluion process. If here is a choice of using an ESTRACK saion agains an exernal saion (e.g. from he DSN nework), he ESTARCK saion is used. This is o exploi he ESTRACK nework as much as possible. Some missions require a long coninuous conac o ground saions o fulfill heir communicaion requiremens. To implemen hese, i is ofen necessary o hand over he conac o he spacecraf from one ground saion o he nex. The planner ries o reduce he number of hand-overs o a minimum. Table Mission\Saion Saniago Maspalomas Kiruna ERS 7 6 5 XMM 3 4 N/A Cluser 8 The case of a concurren usage of he same ground saion service by wo missions is called a conflic if he service canno be shared. To resolve conflics, he planner uses a prioriy and preference scheme. The scheme associaes o each mission ground saion pair a unique number. An example of his is given in Table. The usage of a ground saion for a cerain mission may also be compleely ruled ou (denoed by N/A). If he missions Cluser and XMM ried o use a service of he Maspalomas ground saion ha canno be shared a he same ime, his resuls in a conflic. According o he example given in Table, he XMM reques would have o be moved because i has he lower prioriy (bigger number). The scheme used here mixes prioriies (as explained) and preferences. I is used for he case where a mission requess a service ha can be implemened by wo differen ground saions. The ground saion preferences of one mission are deduced by picking he saion wih he highes number from he Cluser row. This prioriy and preference scheme has been used for he firs implemenaion of he EPS.
EPS Model This secion provides a logical EPS model and defines he EPS componens and heir inerrelaionships. Figure 3 shows he logical EPS model. Mission specific communicaion requiremens are represened by he Mission Model. The Mission Model conains for all paricipaing missions he informaion, a which periodic cycles a mission requires a se of ground saion services o communicae wih a spacecraf. In ha conex, he abiliy of a ground saion o provide elecommand, elemery, ranging services ec, is referred o as a ground saion service. <<Requiremen>> Mission Model (from Mission Model)..n <<Dynamic Resource>> Prediced Evens <<Sysem>> EPS <<Auxilliary Requiremen>> Planning Crieria <<Oupu>> ESTRACK Managemen Plan (from Plan) <<Saic Resource>> Ground Saion Model (from Ground Saion Model) Figure 3 Overall EPS model The ground saion model conains all ground saions available for planning. I describes he capabiliies of each ground saion in erms of services available a each ground saion. Ground saions can be seen as saic resources, because hey do no change during a planning cycle. The dynamic resource aspec is provided o he EPS in form of prediced evens: Among oher hings, hey include he informaion, a which imes a spacecraf is visible from a paricular ground saion. Finally, he EPS planning process is guided by Planning Crieria which include bu are no limied o ground saion preferences and prioriies of he missions. Mission Model The EPS planning process is performed o saisfy he requiremens expressed in he Mission Model. The EPS Mission Model can be decomposed as shown in Figure 4. I conains a Mission Agreemen for every mission which is planned by he EPS. Each Mission Agreemen conains in urn a lis of required User Services. A User Service groups he required ground saion services and expresses heir emporal aspec by a so called Sanding Order. The emporal aspec expressed by a Sanding Order is he requesed periodiciy (e.g. every second orbi, wice a week, ec). Consrain 0..n +Required Services Mission Model..n Mission Agreemen Mission..n User Service Basic Period Selecor..n Service (from Ground Saion Model) Sanding Order Basic Period Figure 4 EPS Mission Model In he conex of he EPS, he requesed periodiciy for User Service provisioning is referred o a Basic Sanding Order Period (BSOP). BSOPs can be specified based on differen unis: orbis, hours, days, weeks, and monhs. The User Service has a Basic Period Selecor o selec every n h basic period as an implemenaion inerval for he User Service. Figure 5 shows an example for a Basic Sanding Order Period of hree orbis and a Basic Period Selecor of. In his example, he User Service would be implemened wihin he orbis labeled Seleced BSOPs. Basic Sanding Order Period: 3 orbis Basic Period Selecor: Seleced BSOPs Figure 5 Basic Sanding Order Period In addiion, a User Service can be consrained. Consrains aached o a User Service affec he way i is implemened: Consrains can have a emporal aspec or can affec he way resources (e.g. ground saions) are used. The following examples of consrains shall provide an idea on how a user service can be consrained: The User Service shall be provided for a leas and a mos for 3 hours. A User Service shall be provided imes wihin a Basic Sanding Order Period (BSOP). The minimum duraion for each service provisioning
is hour, he overall service provisioning wihin he BSOP shall be four hours. Two consecuive provisions of a user service mus occur wihin a leas 48 hours bu no before 4 hours Ground Saion Model Service provisioning is planned based on he ground saion resources published by he Ground Saion Model. The Ground Saion Model as depiced in Figure 6 specifies he available ground saions and heir capabiliies. Ground Saion Model..n Ground Saion +Suppored Services..n Service Figure 6 EPS Ground-Saion Model The capabiliies of a ground saion are expressed as Suppored Services. Noe ha a Service required wihin a Mission Agreemen of he Mission Model can only be insaniaed for ground saions which suppor exacly he required Service. Figure 7 ESTRACK Managemen Plan The erm Service Insance is used for a Service which is insaniaed for a paricular ime inerval. Figure 7 presens he relaionship beween he various objecs sored on he ESTRACK managemen plan. In he firs version of he EPS, all Service Insances have he duraion of he Service Session. Prediced Evens and Service Opporuniy Windows The missions paricipaing in he EPS planning process feed on a regular basis heir prediced evens ino he EPS. In ha conex, prediced evens are: Acquisiion Of Signal (AOS) / Loss Of Signal (LOS) evens for he saellie / ground saion combinaions of a mission Sar and end of operaor shifs All oher evens relevan o planning of ground saion allocaion Before he acual planning of ground saion allocaion is performed by he EPS, a preprocessing of he prediced evens is performed. According o mission specific rules, he prediced evens are combined o Service Opporuniy Windows (SOWs). SOWs are periods of ime for which he service provisioning for a se of Services is possible. Figure 8 shows an example, how wo SOWs are generaed: The overlap of ground saion / spacecraf visibiliies and he operaor shif are combined o wo SOWs. Each SOW is associaed wih he ground saion providing he service opporuniy. ESTRACK Managemen Plan Planning resuls are sored on he ESTRACK Managemen Plan as so called Operaional Service Sessions (OSS). Operaional Service Sessions group Services provided by one ground saion for a paricular period of ime. facs spacecraf visibiliy (STATION A, SPACECRAFT X) spacecraf visibiliy (STATION B, SPACECRAFT X) operaor shif (SPACECRAFT X) ime <<Oupu>> ESTRACK Managemen Plan..n Operaional Service Session Used Saion Mission Sar Time Ground Saion (from Ground Saion Model) End Time +Service Insances..n Service (from Ground Saion Model) SOWs Generae SOW Generae SOW SOW (STATION A, SPACECRAFT X) SOW (STATION B, SPACECRAFT X) Figure 8 Service Opporuniy Window (SOW) generaion ime
The rules on how o creae SOWs are expressed as saemens formulaed in he Language for Mission Planning (LMP). For deails on LMP please refer o []. SOW generaion rules are par of he Mission Agreemen of each mission and are associaed o User Services. This allows individual SOW generaion per User Service. Noe ha SOW generaion rules are no shown in Figure 4 in order no o overload he figure. Planning Algorihms We now presen some deails on he algorihms used for a planning session. Remember ha planning sessions are riggered by he EMS Operaors following modificaions of he requess or updaes concerning spacecraf o ground saion visibiliies knowledge (see Figure ). As poined ou before, he aim of a planning session is o assign o each Seleced BSOP a se of OSSes (Service Sessions wih deermined sar and end imes) implemened on SOWs. These OSSes mus be such ha all he requiremens in he Mission Model and all he resource consrains are respeced. We inroduce he concep of Candidae Operaional Service Sessions (COSSes) which are OSSes whose sar and end imes are ime variables. We say ha a BSOP is planned if we have been able o generae a se of COSSes ha implemen he associaed User Service wihin he corresponding ime slo. Once one or more BSOPs are planned, he sar and end imes of all he associaed COSSes consiue he variables of a emporal consrain nework. The domains of hese variables are deermined by he sar and end imes of he supporing SOWs, while he consrains beween hose variables are provided by he User Service and he used resources. Given ha, a valid plan on he se of planned BSOPs can be generaed if and only if he underlying emporal consrain nework is consisen. The mapping beween hose dedicaed conceps and he erms radiionally used in he planning communiy is he following: BSOPs are exended goals generaed from he mission model; ground saions are unary resources, and SOWs express emporal availabiliies of hose resources; COSSes are performed acions on a parial plan; OSSes consiue ogeher an insaniaed plan. Example. For example, consider he case of wo planned BSOPs B and B for wo differen User Services. B is planned wih one COSS C implemened on a SOW S, B wih one COSS C implemened on a SOW S. We For his secion we simply call he Seleced BSOPs BSOPs. Inpu: a plan wih all previously planned/ commied BSOPs; new BSOPs o plan; SOWs. N s s e e S Generae C Che COSSes S for his ebsop s and apply hem o he plan C C d s s e e S C C S e s C C d Plan Y e s consisen e s C C C? C Success: reurn an insanciaed plan Sill unplanned BSOPs? Selec a new BSOP Repair limi exceeded? Perform a repair Failure: reurn conflicing BSOPs Figure 9 General algorihm assume ha S and S overlap and are suppored by he same ground saion. We furher assume ha he minimum duraion of he service for B (resp. B) is d (resp. d ). We noe s A (resp. e A ) he sar (resp. end) ime of he inerval A. The variables of he underlying emporal consrain nework associaed o B and B are s e C, C, s e C and C (he SOWs sar and end imes are consans). The consrains beween hose variables are he following: To sum up, he general problem can be decomposed ino wo basic problems: generaion of he COSSes for each BSOP consisency check of he underlying consrain nework We shall see ha he former can be seen as a selecion problem and he laer as a scheduling problem. If he consrain nework proves o be inconsisen, a repair mus be performed, by modifying he se of so far generaed COSSes. Figure 0 provides an insigh of he global algorihm. I akes as an inpu new BSOPs o plan and he available Y N N Y
SOWs; i exends a plan conaining he curren implemened COSSes associaed o BSOPs planned during a previous planning session. On success, i reurns a plan composed of OSSes; on failure, i reurns informaion helping he EPS Operaors o ake a correcive acion. The inernal seps are described in he following subsecions. BSOP selecion Noe firs ha wo opions were available in order o implemen all he BSOPs: eiher plan all he BSOPs, hen check he consisency of he global underlying consrain nework, and perform some repairs if necessary; or plan one new BSOP, check he consisency of he underlying consrain nework, performing a repair if necessary, hen plan he following BSOP, and so on (incremenal approach). We chose he incremenal approach essenially in order o make he repairs easier. Thus, a each pass in sep Selec a new BSOP of he general algorihm, a BSOP is heurisically picked and removed from he se of unplanned ones. In our implemenaion, he BSOPs are ordered by increasing end ime and pu in a queue (earlies deadline firs heurisic), wih he hope o limi he exen of he possible repairs o he near pas. However his needs o be confirmed by experimens. COSS generaion Afer a BSOP has been seleced, we have o generae he COSSes ha will be applied o he plan. These COSSes are suppored by a subse of he SOWs available for his BSOP and mus respec he consrains of he User Service..SOW filering.handover deerminaion 3.COSS generaion available SOWs A(3) A(3) handover C A B BSOP C(5) D(3) E() B(6) C B(6) COSSs D(3) handover C3 D GS GS GS3 GS4 GS GS4 GS GS4 The firs sep of he generaion is he filering of all he SOWs ha can be proven useless (any COSS generaed on hem will break some of he consrains specified in he User Service). This is he case when a minimum service disance is required beween wo consecuive BSOPs of he same User Service: all he SOWs ha sar oo early can be discarded for he COSS generaion of he second BSOP. Secondly, he SOWs ha will acually suppor he COSSes mus be seleced. Wihou hand-overs, he selecion of he SOW o use for a BSOP would be sraighforward: jus ake he SOW wih he highes preference. Bu he need for hand-overs muliplies he number of possible ses of COSSes. We hus use an opimizaion algorihm ha is able o generae suiable sequences of SOWs ha will suppor he COSSes, aking ino accoun he preferences on he ground saions for he mission as well as mos of he consrains and preferences specified in he User Service. This algorihm (no presened here) is based on dynamic programming and has been designed for his specific problem. From he sequence of SOWs o use for he curren BSOP, we obain he se of COSSes. Then we deduce he new variables and consrains o add o he global emporal consrain nework. Noe ha each consrain is relaed o a se of ime poins which are hemselves eiher he sar or he end ime of a given COSS implemened for a unique BSOP. Figure shows as an example a BSOP wih five available SOWs A, B, C, D, and E. For each SOW, he corresponding ground saion preference level for he mission is indicaed beween parenheses. During SOW filering, for some reason C is eliminaed. Assuming, for example, ha he minimum service duraion is such ha several SOWs are necessary, he handover plan generaed a sep is he following: firs use SOW A, hen coninue on SOW B, and finish on SOW D. This resuls in generaing hree COSSes C, C and C3 (one for each used SOW), wih all associaed consrains. We give here he consrains relaed o he handovers: s C s C3 = = e C e C hd( GS, GS4) hd( GS4, GS) where hd(gsi,gsj) is he minimum handover duraion beween ground saions GSi and GSj for his mission. Consisency check Once he COSSes have been generaed for some planned BSOPs, he resuling consrain nework mus be proven consisen o guaranee ha a feasible plan of OSSes can be oupu. Differen ypes of emporal consrains. The naure of he acual consrains of his nework deermines he used consisency check mehod. An analysis of he problem provides hree kinds of consrains o be handled: Figure 0 The 3 seps of COSS generaion for a BSOP
. binary consrains, of he form i j b where i, j are he variables and b is a consan, widely sudied in Simple Temporal Problems [] (STPs). The consisency check of he associaed nework is a cubic funcion of he number of variables. Precedence consrains and minimum handover duraion consrains are examples of binary consrains.. linear consrains, of he form a b, widely sudied in Linear Programs [6] (LPs). The consisency check of he associaed nework is polynomial, and i has he same complexiy as he complee solving: i can be seen as solving he phase one of he simplex algorihm. The oal service duraion is an example of a linear consrain. I defines he sum of he duraions all service insances, implemened for one BSOP. 3. disjuncions of binary consrains, of he form C k, k where each C k is a binary consrain, widely sudied in Disjuncive Temporal Problems [8] (DTPs) which are NP-complee. These consrains are necessary o express ha a unary resource (a ground saion for example) can be used by only one COSS a he same ime, hus requiring an ordering beween he COSSes. The las consrain in Example is an example of a disjuncive consrain. Noe ha he general problem is hus o check he consisency of a Disjuncive Linear Program (cons-dlp). However, i is imporan o sress ha in our case binary consrains consiue he majoriy of he consrains while here are comparaively few linear consrains, and ha he disjuncions conain only binary consrains. For a planning horizon of one week, we roughly evaluae he number of ime variables o several hundreds, wih a few consrains per variable. A branch and bound general approach. One efficien way o solve a disjuncive problem (DTP or cons-dlp) is o check he consisency of a mea Consrain Saisfacion Problem (mea-csp). The variables of his mea-csp are he disjuncions, he domain of each variable is he associaed se of disjuncs, and he consrains beween he variables are implici [9]. Thus an assignmen o some variables is consisen if and only if he associaed simple problem (STP or LP) is consisen. The search for a soluion consiss in he exploraion of a ree, each node represening a parial assignmen of he mea-csp. Common CSP solving echniques as well as dedicaed ones can be used. Common echniques comprise conflic direced branch and bound and no-good recording. Dedicaed ones comprise removal of subsumed variables for DTPs [9] and induced uni clause relaxaion for DLPs [3]. i i i Alhough he simplex algorihm is no polynomial, i is sill very efficien. Le s consider again Example. We furher assume ha s e s e d = d = 0, S = 5, S = 5, S = 0 and S = 5. To check he consisency of he consrain nework, we associae a variable D of he mea-csp o he disjuncive e consrain, wih domain { D, D }, where D : s C C 0 e and D : s C C 0. During he search, D is firs assigned o D, bu he underlying nework is inconsisen, so D is hen assigned o D. The underlying nework is now consisen, hus a valid plan can be consruced wih he planned BSOPs B and B and wih associaed COSSes C and C. Furhermore, in his plan, C necessarily precedes C. Selecion of he search sraegies. From an analysis of our problem, we have been able o derive several search sraegies o efficienly solve he mea-csp. Firsly, given ha binary consrains are he majoriy of he consrains, and ha STPs are far easier o solve han LPs, a sensible approach is o solve he DTP par of our problem, and check he linear consrains wih LP only if a successful leaf is reached. Secondly, in case of failure, we need o pinpoin he se of culpri consrains in order o derive he incriminaed COSSes, hus o idenify he incriminaed BSOPs. Conflic direced sraegies are clearly well suied o his as hey use discovered conflics o guide he search. Thirdly, he mea-csp is a dynamic CSP. Each ime a new BSOP is planned and COSSes are generaed (resp. a COSS is removed consequenly o a repair acion), new ime variables may be added (resp. removed), hus modifying he implici consrains of he mea-csp. New emporal consrains may also be added (resp. removed), hus modifying he pool of variables of he mea-csp. To cope wih his, we will follow advice provided in [7] and experimen no-good recording and oracles. Repair As saed in he COSS generaion subsecion, COSSes are generaed wihou a guaranee ha he former underlying consrain nework augmened wih he new variables and consrains is consisen. If i no he case, he incriminaed COSSes mus be deeced and a repair acion (o modify he COSSes from one BSOP) chosen. Idenificaion of he incriminaed COSSes. When he mea-csp is proven inconsisen he aim, for a repair, is o idenify a leas one Minimal Unsaisfiable Subse [4] (MUS) of he emporal consrains. A MUS is a se of conflicing consrains such ha as soon as one of hese consrains is removed, he resuling se is no longer conflicing. In our case, removing a COSS whose sar or end ime is involved in a MUS enables o solve he conflic idenified by his MUS. See [5] and [] for algorihms o generae MUSes for DTPs and LPs. Selecion of he COSS o remove. Among he COSSes idenified in a MUS, one mus be removed. This choice akes ino accoun general preferences such as mission o ground saion prioriies in case of a conflic on a resource,
and heurisics favoring he sabiliy of he nework in order o avoid endless repairs. Failure repor. The repair process menioned above is local, hus i is no guaraneed o end wih a soluion. To preven an endless repair loop, a sopping crierion is provided, such as a maximum number of repairs, or a maximum ime spen in repair. If his limi is reached, he sysem repors a failure o he EPS Operaors ogeher wih a se of User Services he degradaion of which should allow solving he exraced conflics. Consrucion of he oupu Once all he BSOPs have been successfully planned, i means ha a LP, amongs hose explored in he mea-csp ree, has been proven consisen. To obain a final oupu plan, i is necessary o fix he sar and end imes of all he COSSes, hus creaing OSSes. To do his, he soluion of he LP solved a he end of he las consisency check can be used. Assuming ha preferences can be ranslaed in a linear funcion of he ime variables o opimize, i is also possible o solve a las DLP, his ime looking for opimaliy and no only consisency. Implemenaion The developmen of he ESTRACK Planning Sysem has been iniiaed by he European Space Agency in Sepember 005. EPS is a componens of he ESA Ground Operaion Sofware (EGOS), he laes ESA sofware infrasrucure supporing he developmen of ground sysems. The sysems will run on PC/LINUX plaforms. The core funcionaliy of he sysems is developed in C++, and he user inerface using ECLIPSE/JAVA/SWT. In line wih he ESA sofware re-use policy, he implemenaion of he sysem is based on reuse of sofware and design, mosly from he wo following sources. The Enhanced Kernel Library for Operaional Planning Sysems (EKLOPS) developed by VEGA for ESA as par of he Mars-Express and Venus-Express mission planning sysems (see []). This se of libraries suppors all aspecs of he developmen of an operaional planning sysem for space mission and provides he core of he planning funcionaliy required for he developmen of EPS. The ESOC Ground Operaions Sofware (EGOS), which provides infrasrucure componens for generic funcionaliy such as sysem processes locaion, sysem processes managemen, sysem processes monioring and conrol, sysem saic/dynamic configuraion managemen, services Managemen Framework (SMF), Users and Privileges managemen, Evens/Alarms managemen, Files managemen, and Generic File Transfer. This approach ensures a safe developmen of he sysems a low cos. EPS will be ready for operaion before he end of 006. Operaional Resuls The operaional resuls provided below have been obained wih he firs operaional release of he sysem. The differences wih he feaures described in he algorihm secion are he following: he linear consrains are no checked, he consisency check solves a DTP, using an adaped version of Epiliis algorihm [9]; he choice of he BSOP o modify for conflic resoluion is direcly based on he no-goods of he mea-csp reurned by Epiliis following he failure, no on MUSes; a basic form of oracle is used beween wo calls of Epiliis: he valid assignmen of he mea-csp obained afer planning a BSOP is he sar poin of he new consisency check when planning he nex BSOP 3 ; all no-goods are conserved. We presen resuls for he planning of he communicaions for 5 saellies and for weeks. The BSOPs are based on he orbis of hose spacecraf (roughly days). During each orbi, for he firs saellie (XMM), one conac is required beween wo absolue daes, and 3 handovers are allowed. For he ohers (Cluser), conacs are required and no handover is allowed; addiionally each conac mus las a leas 5 hours and mus be separaed by a leas hours from he preceding one. For his insance, he planning lased 94 seconds. 9 aciviies (COSSes), 533 binary consrains and 5 disjuncive consrains were generaed. Only repairs were necessary: his is a small number bu fairly represenaive of curren EPS problems which are underconsrained. As he SSOW generaion ime was negligible compared o he consisency check, we now focus on he laer. Figure shows he evoluion of he consisency check compuaion ime as more and more BSOPs are planned. 4 kinds of behavior of he consisency check can be poined ou: (a) represens successful consisency checks wihou backrack, (b) successful wih backrack ones, (c) failed ones, (d) successful ones sared from scrach (unlike (a), (b) and (c) which ake advanage of he oracle). The regular rise of he compuaion ime is direcly due o he increase of he size of he generaed Simple Temporal Neworks. We also noe ha in such loosely consrained problems, proving inconsisency (case (c)) is more difficul 3 Provided ha he forward check is successful wih hose new mea-consrains (see [9] for more deails on Epiliis implemenaion).
han proving consisency (cases (a) and (b)). To finish wih, wha srikes when comparing cases (d) o he oher cases is he benefi of he use of he oracle, whose impac is expeced o increase as more and more BSOPs are planned. Compuaion ime (seconds) 3 5.4 6.4,5,5 0,5 0 (a) (c) (d) (a) 0 0 40 60 80 00 0 40 60 80 Figure Consisency check compuaion ime Fuure Work Rank of he consisency check The ESTRACK Planning Sysem presened in his paper is he firs version of a major componen of he ESA ground sysems infrasrucure, EGOS. The full scope of requiremens ha was defined for his sysem is expeced o be implemened in laer versions of he sysem. The coming requiremens can be pared in hree groups. The firs group adds he daa inpu mechanisms for a second se of ESA missions. The second group conains he requiremens o handle requess from and offers o exernal users. The hird and bigges group deals wih he granulariy of ground saion services. As menioned in he inroducion o his paper, in he curren implemenaion a ground saion can only be used by one spacecraf a a ime. The nex version of EPS will define discree resources for ground saion ha will allow for he parallel use of a ground saion by several missions. I will be possible o use differen services and/or several insances of he same service a he same ime. In addiion o he requiremens ha are already defined, advanced feaures may be considered for fuure versions of he EPS. One is he implemenaion of acive consrains. This concep would suppor he visual ediion of finalized scheduled plans. The ediion would be performed by he EPS operaor who wans o ailor a specific plan o his needs. The consisen consrain nework, which is an inermediae resul of he planning process, would be kep wih he plan. Each ediion he operaor performs would cause a reassessmen of he consrain nework including a possible repair acion. Thus he plan would be kep consisen and valid during manual ediion. (b) (a) References [] Chinneck, J., and Dravnieks, E. 99. Locaing Minimal Infeasible Consrain Ses in Linear Programs. ORSA Journal on Compuing 3():57 68. [] Decher, R.; Meiri, I.; and Pearl, J. 99. Temporal Consrain Neworks. Arificial Inelligence 49(-3): 6-95. [3] Li, H., and Williams, B. 005. Generalized Conflic Learning For Hybrid Discree Linear Opimizaion. Proceedings of he Elevenh Inernaional Conference on Principles and Pracice of Consrain Programming (CP). [4] Liffion, M., and Sakallah, K. 004. On Finding All Minimally Unsaisfiable Subformulas. Proc. 8h Inernaional Conference on Theory and Applicaions of Saisfiabiliy Tesing (SAT-005) 73 86. [5] Liffion, M.; Moffi, M.; Pollack, M.; and Sakallah, K. 005. Idenifying Conflics in Overconsrained Temporal Problems. Proceedings of he 9h Inernaional Join Conference on Arificial Inelligence. [6] Schrijver, A. 998. Theory of Linear and Ineger Programming. John Wiley and Sons. [7] Schwarz, P., and Pollack, M. 005. Two Approaches o Semi-Dynamic Disjuncive Temporal Problems. ICAPS Workshop on Consrain Programming for Planning and Scheduling. [8] Sergiou, K., and Koubarakis, M. 998. Backracking algorihms for disjuncions of emporal consrains. Proc. of AAAI-98. [9] Tsamardinos, I., and Pollack, M. 003. Efficien Soluion Techniques for Disjuncive Temporal Reasoning Problems. Arificial Inelligence 5(- ):43-90. [0] EMS Sofware Requiremens Specificaion, DOPS- ESOC-EMS-SRS-000-OPS-GIB Issue.3, 005-0- [] Sudy on ESTRACK Managemen and Scheduling, Final Repor, RN GSS-EMS-SDY-FR-000, Issue.0, s February 005 [] Noll, J. and Seel, R. 005. EKLOPS: An Adapive Approach o a Mission Planning Sysem. Proc. Of IEEE Aerospace conf.