SERVICE PROVISIONING IN CYBER-PHYSICAL CLOUD COMPUTING

CYBER-PHYSICAL CLOUD COMPUTING LAB UNIVERSITY OF CALIFORNIA, BERKELEY SERVICE PROVISIONING IN CYBER-PHYSICAL CLOUD COMPUTING Jigchu Hug, Clemes Krier, Christoph M. Kirsch Rj Segupt Workig Ppers CPCC-WP-2012-11-01 November 2012

Service Provisioig i Cyber-Physicl Clou Computig ABSTRACT Jigchu Hug Systems, Civil Evirometl Egieerig Uiversity of Clifori, Berkeley jigchu@berkeley.eu Christoph M. Kirsch Deprtmet of Computer Scieces Uiversity of Slzburg, Austri ck@cs.ui-slzburg.t We tke the prigm of clou computig pply it i cyber-physicl system where the servers vehicles) c move i spce crry sesors ctutors. We cll this cyber-physicl clou computig CPCC). Like regulr clou computig, CPCC customers get virtul mchie ruig o rel server. The virtul mchie is clle virtul vehicle. The CPCC server is clle rel vehicle. We efie virtul vehicles through the ie of virtul vehicle moitor logous to virtul mchie moitor. We esig service level greemet betwee clou proviers customers. Resource-level service-level metrics, coformble pplictios re iscusse through the cocepts of virtul spee, require spee, elivere spee toke bucket regultor. We show tht the me require spee is boue by the virtul spee the burstiess is boue by the bucket cpcity. We prove tht the me elivere spee is greter th the me require spee for ifiitely log computtio sequece whe the system is stble. The opposite is true whe the system is ot stble. We crete CPCC simultor implemetig first come first serve gte trvelig slesm policies. We show tht CPCC provier c host give umber of VVs with fewer RVs opertig t the sme spee while proviig service gurtees o me elivere spee elivery probbility. This work ws prtly supporte by NSF-CNS-1136141. Permissio to mke igitl or hr copies of ll or prt of this work for persol or clssroom use is grte without fee provie tht copies re ot me or istribute for profit or commercil vtge tht copies ber this otice the full cittio o the first pge. To copy otherwise, to republish, to post o servers or to reistribute to lists, requires prior specific permissio /or fee. Copyright 200X ACM X-XXXXX-XX-X/XX/XX...$5.00. Clemes Krier Deprtmet of Computer Scieces Uiversity of Slzburg, Austri ckrier@cs.ui-slzburg.t Rj Segupt Systems, Civil Evirometl Egieerig Uiversity of Clifori, Berkeley segupt@ce.berkeley.eu 1. INTRODUCTION The time of clou computig hs filly come [2]. Clou computig is moel for eblig coveiet, oem etwork ccess to shre pool of cofigurble computig resources e.g., etworks, servers, storge, pplictios, services) tht c be rpily provisioe relese with miiml mgemet effort or service provier iterctio [20]. Mjor plyers such s Amzo Web Services, IBM SmrtClou, Wiows Azure Google App Egie hve lrey me clou computig relity. Armbrust [2] summrize three ew spects i clou computig from hrwre poit of view: i) The illusio of ifiite computig resources vilble o em; ii) The elimitio of up-frot commitmet by clou users; iii) The bility to py for use of computig resources o short-term bsis s eee. Whe computtio hppes ot oly i time but lso i spce, the computtio c be crrie out by servers movig i spce with computig uit. Clou computig tht hppes both i time spce is clle cyber-physicl clou computig CPCC) [3, 11]. The key iovtios i CPCC [3] re to hve servers vehicles) move i spce crry sesors /or ctutors [11]. Exmples of movig servers vehicles) iclue fleet of ume eril vehicles UAVs) equippe with cmers or sesors gtherig t [26] or moitorig eviromet [22], i-vehicle smrtphoes s iteretcoecte sesor i ro coitio moitorig lert pplictio [7], people crryig smrt phoe i clou sourcig [15]. Like regulr clou computig, CPCC customers get virtul mchie VM) ruig o rel server. The VM is clle virtul vehicle VV). The CPCC server is clle rel vehicle RV). I [11] we efie two kis of mobility for VV, cyber-mobility, smll-time-scle

hop, physicl mobility, lrger-time-scle motio with the RV. Whe VV is bou to RV, the VV exhibits physicl mobility. Whe it migrtes it exhibits cyber-mobility. CPCC, just like regulr clou computig, is met to work t scle, i.e., t lest for hures of rel vehicles, potetilly thouss of virtul vehicles. Clou computig toy is still i the erly stges of evelopmet [31]. Curret reserch mily focus o clou computig rchitecture [27], scheulig [9], resource lloctio lo blcig [19], resource provisioig ecoomic moels [6]. Qulity of service QoS) c be fou i [17, 5, 8]. Typiclly, the QoS is specifie i cotrct, service level greemet SLA), betwee the clou provier customer. Goiri et l. [8] chrcterizes the QoS by resource-level metrics e.g., umber frequecy of processors, FLOPS, etc.) service-level metrics e.g., service executio elie). Curret clou computig proviers mily provie the resource-level metrics, e.g., Amzo EC2 str Istces. The service-level metrics is oly i vilbility, mesure i ul uptime percetge. There is o gurtee o the system time, or how log oes it tke to complete the computtio. Lee [16] coclues tht the computig time c mily be estimte i three wys: coe lysis [24], lytic bechmrkig/coe profilig [30], sttisticl preictio [10]. Akiok et l. [1] provie high performce computig bechmrks o Amzo EC2. The telecommuictio etwork service provisioig hs loger history th clou computig. Kurose [14] gve survey of QoS provisioig. The QoS gurtees re ivie ito etermiistic gurtees e.g., bou o pckets ely or loss) sttisticl gurtees e.g., o more th specifie frctio of pckets will see performce below certi specifie vlue) i [29]. I ATM Networks, Low et l. [18] provie the etermiistic QoS gurtee through regultig trffic t etwork eges usig toke bucket regultor. Toke bucket or leky bucket regultors [25, 4] re use to check complice with cotrcts betwee users etwork service proviers. Illumite by the service provisioig experieces of clou computig telecommuictio etwork, we believe goo CPCC service shoul hve three spects i its SLA, briefly summrize i Tble 1. QoS resource-level metrics: the virtul vehicle specifictio by costt: the virtul spee, v V. Just s i clou computig the customers reserve virtul mchie specifie by umber frequecy of processors, memory storge, e.g., the Amzo EC2 str Istces, i cyber-physicl clou computig, the customers reserve virtul vehicle specifie by the virtul spee v V. Coformbility: it efies the coformble pplictios tht the customers c choose check tht they re proviig em requests coformig to the specifictio of the coformble pplictios. By the coformbility efiitio, the clou provier c gurtee tht customer oes ot geerte the computtios too fst, or oes ot geerte lrge-size log-istce-prt computtios i short perio of time. We propose to use toke bucket regultor to chieve this. The toke bucket regultor provies wy to ifer the resource requiremets of computtio em. The etils of this regultio is i Sectio 3. QoS service-level metrics: We efie the require spee by the customer, vi R, i Sectio 3.2, efie the elivere spee from the system, vi D, i Sectio 4.1 for ech computtio i. The QoS service-level metrics re the me elivere spee for computtio sequece of legth, vi D, the probbility tht the elivere spee is greter th the require spee per computtio, P vi D vi R The system gurtees tht the me elivere spee is greter th the me require spee for computtio sequece of legth, provies P ) vi D vi R. Tble 1: CPCC service level greemet Resource-level Virtul spee, v V, metrics Burstiess, c. Service-level Gurtee tht v D > v R, metrics Provie P ) vi D vi R. We use toke bucket regultors to esure coformble pplictio. Oce RV begis to pproch computtio loctio it c ot be iterrupte util the RV hs reche the loctio complete the computtio. This is ifferet to clou computig, where proviers my migrte VMs rbitrrily betwee the oes, computtios my be suspee rbitrrily resume lter [20]. So we regulte the computtios t their rrivl usig toke bucket regultor, iste of cotrollig them t rutime. Our cotributios re s follows, we efie virtul vehicle through the otio of virtul vehicle moitor followig the forml efiitio of virtul mchie [21] i Sectio 2. We lso efie the stbility of the CPCC system i this sectio. We efie coformble pplictios usig toke bucket regultor i Sectio 3, efie the require spee, vi R, its hrmoic me, v R. We show tht the hrmoic me require spee is upper boue by the virtul spee the bursti- ).

ess of the require spee is upper boue by the bucket cpcity c i Theorem 1. We efie the elivere spee, vi D, its hrmoic me, vd, i Sectio 4. The elivere performce is mesure by v D the probbility tht the elivere spee is greter th the require spee for computtio. We show i Theorem 2 tht v D v R whe the computtio sequece legth goes to ifiity whe the system is stble, v D < v R whe is lrge eough whe the system is ot stble. Sectio 5 itrouces the simultor implemetig the cocepts i Sectios 2, 3, 4, shows the simultio results i Figures 4 5. Simultio shows tht uer G-TSP, 100 RVs with spee 1 m/s c host 200 VVs with virtul spee 1 m/s while the me computtio size is 0.25 s, host 400 VVs with spee 1 m/s while the computtio size is 0. The me elivere spee is greter th v V 1 m/s for ll the me require spee rge llowe by the SLA. The elivery probbility per computtio is greter th 90% for most rge of the me require spee. The provier c host give umber of VVs with fewer RVs opertig t the sme spee while proviig service gurtees o me elivere spee elivery probbility. 2. THE CPCC SYSTEM A CPCC system is compose of K N iepeet virtul vehicles VVs) the ifrstructure tht hosts the K VVs i covex regio A of re A. The ifrstructure iclues M N rel vehicles RVs), lloctor tht lloctes the RVs resource) to the VVs ems). The CPCC system is show i Figure 1. 2.1 Rel Vehicle The ifrstructure of the CPCC system is compose of M rel vehicles RVs) the lloctor. We ssume tht the lloctor hs cetrl iformtio of the system hs full cotrol o the RVs subject to vehicle ymics. Usully the vehicle spee is ot costt cosierig ccelertio ecelertio, yw costrit, or the ffectio of the eviromet. Exmples of the ymics of ume eril vehicles UAVs) c be fou i [23] the ymics of crs c be fou i [28]. We ssume the j-th RV trvels t costt spee v j, j 1,..., M whe efiig the cocepts i Sectios 3 4. We focus o homogeeous system where the ymics of ech RV re the sme. We thus omit j i the followig cotext. 2.2 Virtul Vehicle The CPCC system provies K virtul Vehicles VVs). The k-th VV is efie by costt virtul spee, v V k, k 1,..., K, i the SLA betwee customer CPCC provier. A VV c be reserve by customer to host col- # Customers VV s): K.! # Rel Vehicles RV s): M.!!!!!!! {T k i }! {T K i }! {T1 i }! CPCC System! RV 1! RV 2! RV 3! RV 4! L k i! C k i-1! C k i! RV 5! RV 6! D k i! RV 8! RV 7! Figure 1: CPCC system. {T 1 i }! {T k i }! {T K i }! lectio of computtios i time spce tht must be orere ito sequece to be execute, subject to costrits tht certi computtios must be performe erlier th others. We represet the collectio of computtios hoste by the k-th VV s irecte cyclic grph DAG), C k, E k), where C k { } Ci k, N is the vertex set with ech vertex, Ci k, represetig ech computtio, E k is the ege set with ech ege represetig ech costrit. Algorithms for topologicl orerig my be use to geerte vli sequece of computtios tht stisfies the costris i E k. Relbel { } Ci k such tht it is vli sequece, C1 k C2 k... C. k The Ci k Ti k, Xi k, T Ci) k is the i-th computtio execute by the k-th VV, i 1,...,, where Ti k, Xi k TCi k re the rrivl time poit), loctio requiremet computig time itervl) of Ci k. Whe the system is stble, ech computtio will evetully be complete eprts the system. Let Ti k be the eprture time poit) of the i-th computtio. I this rticle we focus o homogeeous system where these vlues re i.i.. i k. We thus omit k i the followig cotext. Let F X.) be the experiece istributio of ll the X i s, f X.) be the pf. Defie X i X i 1 1) where. is the Euclie orm efie o regio A, i 1, 2,.... X0 k X v, which is the iitil positio of the RV llocte to the k-th VV, ssume X v is rom vrible with istributio F X.). To the customers, the VV is just like RV. Followig the efiitios of virtul mchie virtul mchie moitor by Popek et l. [21]. A virtul vehicle VV) is tke to be efficiet, isolte uplicte of the rel vehicle. We efie virtul vehicles through the ie of virtul vehicle moitor VVM). The behvior of VV is ot exctly the sme s RV. We will show i Sectio 4 tht VV is ot limite to oly oe RV t time, but my execute computtios o severl RVs i prllel i ifferet plces. This behvior mes tht VV is somethig more cpble th RV. 2.3 Virtul Vehicle Moitor

A lloctor is cotrol progrm tht lloctes the RVs resources) to the computtios ems) hoste by the VVs. Whe computtio rrives, the lloctor etermies which RV the computtio goes to. Followig the efiitio of virtul mchie moitor [21], the virtul vehicle moitor VVM) c be efie s follows: v V! Tsks % c! CPCC % Defiitio 1. A virtul vehicle moitor VVM) is y cotrol progrm tht stisfies the three properties of efficiecy, resource cotrol, equivlece. Defiitio 2. A virtul vehicle VV) is the eviromet crete by the virtul vehicle moitor VVM). Oe c check tht the lloctor stisfies these properties thus the lloctor is the VVM. Aitiolly, the eviromet crete by the VVM provie to the customer is VV. The CPCC system is show i Figure 1. The rrows i the sme color represet the computtios from the sme VV. L k i is the istce betwee Ck i Ci 1 k, Dk i is istce betwee Ci k the computtio execute prior to Ci k by the sme RV. Uer the VVM implemetig certi policies, ech vehicle will execute set of computtios possibly from ll the VVs. Whe C i rrives, it first wits for RV to be llocte to it wit time), the it wits for the vehicle to trvel to it trvel time), the it spes some time uer executio executio time), where the executio time iclues the migrtio time computig time. Defie the ottios s follows: T i is the system time of C i, efie s the ifferece betwee the rrivl of C i, T i, the time C i is complete, T i. T i is compose of the witig time, T W i, the service time, T Si. T W i is the witig time of C i, efie s the ifferece betwee Ti the time whe RV becomes vilble strts to serve C i. T Si is the service time, efie s the ifferece betwee the time whe RV strts to serve C i T i. T Si is compose of the trvel time, T Di, the migrtio time, T Mi, the computig time, T Ci. T Di is the trvel time, efie s the time itervl betwee whe the RV is vilble whe the RV reches C i. T Di is etermie by D i s show i Figure 1, the ymics of the RV executig C i. T Di Di v whe we ssume the RV hs costt spee v. A migrtio time, T Mi, is icurre if C i is execute o vehicle ifferet from tht of C i 1. So T Mi > 0 if migrtio hppes, T Mi otherwise. Figure 2: Toke bucket regultor. The reltios re summrize i equtio 2). { Ti T i T i T W i + T Si T Si T Di + T Mi + T Ci 2) Defiitio 3. The CPCC system is si to be stble if T i T i istributio E[T ] is fiite. 3. CONFORMABILITY Differet customers hve iiviul time, loctio, computtio size requiremets. Ielly, the CPCC system shoul llow ll kis of requiremets. But the requiremets cot be elivere if there re too my requiremets i short perio of time. We pply toke bucket regultor o the requiremet rrivls, which gives lrge freeom o computtio rrivls while mkig high gurtee o QoS service-level metrics possible. 3.1 Toke Bucket Regultor We use toke bucket regultor s show i Figure 2 to regulte the computtio rrivls tht c be hoste o ech VV. Defie γ i + v V T Ci 3) i 1, 2,..., ssume T0. The bucket is empty t time 0. Tokes re e to the bucket t rte v V. Ech toke represets 1 meter tht the customer c use the VV to trvel. The computig cost of T Ci is lso coverte to the equivlet cost of meters through v V. The bucket c hol t most c tokes. Deote by γt) the mout of tokes i the bucket t time t, γ0). The iflow tokes re iscre whe the bucket is full, thus γt) c. Whe C i rrives, clculte γ i, if γ i γ Ti ), γ i tokes re tke from the bucket, C i is set to the cyberphysicl clou. If γ i > γ Ti ), o tokes re tke from the bucket, C i is cosiere to be o-coformt. No-coformt computtios re ot llowe by the toke bucket regultor. It is the customers resposiblity to provie coformt computtios. I prctice, o-coformt computtios re simply be iscre. Plese otice tht here the mout of tokes is i rel umbers.

Let γ T + ) i eote the mout of tokes i the bucket right fter the rrivl of the i-th computtio, we hve: γ { T + ) γ T i i ) γ i, if γ i γ Ti ) γ Ti ), ) if γ i > γ Ti ) + v V t T + γt) mi { c, γ T + i 1 i 1)}, T i 1 < t T i 4) where i 1, 2,..., T + 0, γ0). Uer the sme v V c, T Ci re substitutble. The customers c geerte computig itesive tsks with lrge T Ci smll, or geerte trvelig itesive tsks with smll T Ci lrge. The lrger v V is, the lrger or more frequet the computtios c be. The lrger c is, the more vrit the computtio rrivls c be. The CPCC provier c provie ifferet vlues of v V c with ifferet prices tht the customers c choose from bse o their ow ees, just like the Amzo EC2 provies ifferet istces with ifferet computig cpcities ifferet prices. 3.2 Require Spee from Customer Defie the require spee of C i by the customer: v R i T i T i 1 T Ci 5) where T0 L 1 X 1 X v, where X v is the iitil vehicle positio. Defie the me require spee for computtio sequece of legth : v R L i T i Ti 1 T Ci) 6) v R is the weighte hrmoic me of vi R, where the weights re. Theorem 1. A computtio sequece of legth regulte by the toke bucket regultor stisfies mx 1 1 2 2 v R i v R v V 7) i 1 v R i v V ) T i T i 1 T Ci ) c 8) Proof. Uer the toke bucket regultor, strtig with zero iitil creits, the umber of creits use by computtio rrivls is less th the mout of creit rrive i the sme time, i.e., outflow of creit iflow of creit. For computtio sequece of legth, + v V T Ci v V T i Ti 1), i 1, 2,..., ssume T0. Thus we hve v R Li T i T i 1 T Ci) vv Sice the cpcity of the toke bucket is c, y comformt subsequece of computtios {C i } 2 i 1, 1 2, will ot use more th c plus the rrivl of creits i the time itervl ] T 1 1, T 2. 2 i 1 + v V 2 i 1 T Ci v V T 2 T 1 1) + c v V 2 i 1 T i Ti 1) + c, 1 1 2. Plug i 5), we hve mx 1 1 2 2 i 1 v R i v V ) T i T i 1 T Ci) c Remrk: The left h sie of 8) is clle the mximum burstiess of the computtio sequece, {C i }. Defiitio 4. A computtio sequece of legth, {C i }, is si to be complit if 7) 8) hol. The coformbility efiitio sys tht the me require spee of customer is upper boue by the virtul spee i the SLA. A the mximum burstiess of the computtio sequece is upper boue by the toke bucket cpcity, i.e., the require spee of customer c be greter th the virtul spee i the SLA, but cot be so log such tht 8) is violte. 4. DELIVERED PERFORMANCE A customer oes ot kow the policy use by the lloctor, or the rrivl processes of other customers, so customer oes ot kow T W i, T Di T Mi for ech C i. A customer cosiers the CPCC system to be blck box oly observes the rrivl time, Ti, computig time, T Ci, loctio, X i eprture time, Ti, of C i. A customer believes tht Ti is etermie by the loctio the eprture time of C i 1, curret job iformtio Ti, T Ci, X i ), the revele elivere) spee of the VV, vi D. 4.1 Delivere Spee from Provier Defie the virtul service time, TSi V, s the service time of C i erive by the customer bse o the iformtio of X i 1, Ti 1 Ti, T ) Ci, X i, Ti. Sice Ti Ti, there re two cses: T i 1 < T i, i.e., C i rrives fter the completio of C i 1. The the virtul vehicle is vilble whe C i rrives, it serves C i from T i to T i, T V Si T i T i, which is the system of C i. T i 1 T i, i.e., C i rrives before the completio time of C i 1. The C i ees to wit util C i 1 is complete the virtul vehicle becomes vilble. The VV serves C i from T i 1 to T i, T V Si T i T i 1, which is the iter-eprture time of C i. Thus we hve TSi V mi { Ti Ti, Ti Ti 1 } i 1, 2,... T 0. 9)

Plese otice tht the virul service time, TSi V is ot ecessrily the rel service time, T Si, of C i s show i 2). Let vi D be the elivere spee, we hve T V Si v D i The elivere spee is vi D TSi V T Ci + T Ci 10) 11) Let Ti c be the time whe RV strts executig C i, i.e., Ti c T i T Ci, the Ti Ti c T i. Whe T i 1 < T i, vi D > 0, whe Ti 1 T i, there re two cses: T i 1 T c i, i.e., RV strts to compute C i fter the completio of C i 1, v D i > 0. Ti 1 > T i c, i.e., other RV strts to compute C i before the completio of C i 1. C i 1 C i re execute i prllel, this is ot llowe i sequetil computig whe we use oly oe RV to host the VV, but it is possible whe more th oe RVs c execute the computtios hoste by the VV. The customer will hve the illusio tht the VV suely geertes copy t time Ti c loctio X i, strts excutig C i. Defie the me elivere spee for computtio sequece of legth : v D L i ) 12) T V Si T Ci v D is the weighte hrmoic me of vi D, where the weights re. Theorem 2. Whe the CPCC system is stble, lim v D v R ) 0. Whe the CPCC system is ot stble, N > 0, s.t. > N implies v D v R < 0. Proof. Whe the system is stble, ech of, Ti Ti 1 T Ci, Ti T i T Ci Ti T i 1 T Ci re ieticlly istribute coverge i istributio. Thus TSi V T Ci mi { Ti T i, T i T i 1} TCi re ieticlly istribute coverge i istributio. So lim Li, lim T lim V Si T Ci) exist, where lim Y exists v D i T i T i 1 T Ci) mes tht Y coverges i istributio. So lim v R lim lim lim T i T i 1 T Ci) Li T i T i 1 T Ci) exists. This limit oes ot go to ifiity becuse v R v V by Theorem 1 A lim v D lim Li T V Si T Ci) lim lim T V Si T Ci) exists. If this limit goes to ifiity, the lim v D v R 0, so we ssume tht ) this limit is fiite. v D Li Li TSi V T Ci) Ti T i 1 T Ci) LiT T 0 T +T 0 ) Ti T i 1 T Ci) Ti T i 1 T Ci) Li T T ) Ti T i 1 T Ci) Ti T i 1 T Ci). v D v R There re two cses: If lim Li Ti T i 1 T Ci), the Li T i T i 1 T Ci) lim v D lim. the ) lim v D v R 0 sice v R v V. If lim Li T i T i 1 T Ci) is fiite, the lim T T ) T i T i 1 T Ci), becuse lim T T) T is fiite, lim T i T ) i 1 T Ci). Thus lim v D v R lim Li T i T i 1 T Ci) lim T T ) T i T i 1 T Ci) 0 ) Whe the system is ot stble, lim T i Ti, Ti Ti 1 is fiite. So there N 1 > 0, s.t., i > N 1 implies tht Ti T i > Ti T i 1. Let M N 1 T i Ti T i + T i 1), the M is fiite. So there N > N 1 > 0, s.t., i > N implies tht Ti T i > Ti T i 1 + M. So ) T i Ti ) > T i Ti 1 whe > N. Sice T0 T0, the T i Ti 1) T > T T i Ti 1). So ) T V { Si mi T i Ti, T i T i 1}) > ) T i Ti 1, the v R > v D, whe > N. 5. SIMULATOR The simultor emostrtes iformtio-cquisitios--service of mobile sesor etworks for cyber-physicl clou computig CPCC) s propose i [3]. It offers fleets up to severl ozes of helicopters their sesors i such wy tht prticiptig pplictios o ot recogize the ifferece betwee simulte rel flights. I itio, the simultor llows itegrtio of exterl hrwre for i-the-loop tests. Bse o the JNvigtor project [13] the ESE CPCC clss project [12] the implemettio provies the simultio of physicl helicopter swrms, the simultio of sesors, the virtul bstrctio of utoomous vehicles virtul vehicles), the migrtio of virtul vehicles mog flyig physicl helicopters rel vehicles). Curretly the sim-

Simulte Plt i) get positio Sesor Simultio k) get sesor vlues ) uplo computtio tsks Toke Bucket Regultor Simulte Rel Vehicle A j) cotol comms h) get GPS positio Customer Grou Sttio b) coformt tsks c) query vilble virtul vehicles Autopilot g) ew set course Rel Vehicle Mpper f) query vilble virtul vehicles Virtul Vehicle RTE ) owlo computtio results e) perform vehicle migrtio Virtul Vehicle RTE Grou Sttio Mpper l) iitite vehicle migrtio m) perform vehicle migrtio ) iitite vehicle migrtio Figure 3: System overview Simulte Rel Vehicle B e) perform vehicle migrtio ultor supporte sesor types re GPS receiver, photo cmer, thermometer, brometer, sor. Figure 3 provies overview of the simultor system. It cosists of grou sttio GS) umber of simulte moel helicopters, tht is, simulte rel vehicles RVs). The GS cotis the pplictios toke bucket regultor TBR), virtul vehicle ru-time eviromet VVRTE), grou sttio mpper GSM) tht provie web iterfce for uploig ew computtio tsks, owloig computtio results, miisterig VVs. A RV mily comprises moel helicopter plt simultor with itegrte flight cotrol system, utopilot, sesor simultor, rel vehicle mpper RVM), VVRTE. The TBR esures the coformbility of computtio rrivls, s escribe i sectio 3. It forwrs coformt computtio rrivls to the GS VVRTE iscrs o-coformt computtio rrivls. The GS VVRTE cts s cotier holig VVs with their stte, i.e., their icomplete complete tsks. The GSM ecies which RVs shoul process icomplete VV tsks comms the GS VVRTE to migrte the VVs ccorigly. The RV VVRTEs execute VVs tht perform iformtio cquisitio missios. VVs o ot ccess RV sesors irectly, but vi the RV VVRTE. As comme by the RVM, RV VVRTEs migrte VVs to other RV VVRTEs the GS VVRTE. VV tsks tht RV c ot process withi its re of opertios, cuse the RVM to iitite migrtios of the cocere VVs to equte RVs. Bse o the ees of ufiishe VV tsks, the RVM clcultes set course ses it to the utopilot for executio. After VVs hve complete ll their tsks, the RVM comms the migrtio bck to the GS VVRTE. The plt simultor emultes the helicopter s flight ymics iertil mesuremet uit. The itegrte flight cotrol system FCS) opertes ttitue ltitue of the simulte vehicle. The utopilot stirs the simulte vehicle log vehicle cotrol lguge VCL) script efie trjectory by issuig cotrol comms to the FCS. The flow of opertio, s isplye i Figure 3, is s follows. A customer uplos ew computtio tsks to the TBR by usig the GS web iterfce ). The TBR verifies the coformbility forwrs coformt computtio rrivls to the GS VVRTE b). The GSM queries the VVs vilble i the GS VVRTE hvig ufiishe tsks c) iitites migrtios to eligible RVs ). The GS VVRTE migrtes VVs to RVs s comme by the GSM e), e.g., to RV A. The RVM o RV A queries the RVs loe i the RV VVRTE hvig ufiishe tsks f), clcultes ew RV set course ses it to the utopilot for executio g). To stir the RV log the set course the utopilot retrieves the curret RV positio from the simulte GPS receiver h) issues cotrol comms to the simulte plt j). For the clcultio of the RV s positio i GPS coorites, the simulte GPS receiver polls the curret positio of the simulte plt i). After the RV hs reche VV tsk positio, the cocere VV cptures the require sesor vlues k). If the curret tsk of VV is ot i the flyig rge of the RV, the RVM iitites migrtio to suitble RV l) the RV VVRTE performs the orere migrtio m). Oce ll tsks of VV hve bee complete, the RVM iitites migrtio bck to the GS VVRTE l) the RV VVRTE executes the requeste migrtio e). Now the customer my owlo the computtio results from the GS VVRTE by usig the GS web iterfce ). Whe performig computtio, RV hovers t the require loctio. After completio, the RV procees to the ext loctio to couct the ext computtio. T Di is the trvel time betwee two loctios, which is etermie by vector D i s show i Figure 1, the ymics of the RV executig computtio C i. We require tht the RV trvels t verge spee v clculte T Di Di v. Sice the RV hovers whe executig computtio, the RV hs to ccelerte ecelerte betwee two loctios. The simultor pplies equtio 13 to stir the RV from loctio X i 1 to loctio X i. X i T ) is the esire RV loctio t time

T, where 0 T T Di. The RV strts t time T reches X i t time T T Di. ) T X i T ) X i 1 + D 2 T i 3 2 TDi 2 T Di 13) Curretly, the RVM provies two policies for clcultig ew RV set courses: First Come First Serve FCFS) policy Gte Trvelig Slesm Policy G- TSP). The policies cosier oly tsk positios withi the ccorig RV s rge of opertio work s follows. The FCFS policy cuses RV to fly to the positio of the tsk hvig the erliest rrivl time. The G-TSP policy tkes spshot of the positios of the ctive tsks of ll curretly vilble VVs i the RV s VVRTE. The, it clcultes TSP tour strtig t the curret RV positio, trversig ll tsk positios, eig t the RV s epot positio. After tht, the policy removes the epot positio from the TSP tour cuses the RV to perform the TSP tour. Ay tsks rrivig urig the tour re igore for ow. After the RV hs fiishe the tour, the G-TSP policy tkes spshot gi strts from the begiig. Tble 2: Simultio setup Simultio Prmeters Are Size 10 m 10 m Cell Size 1 m 1 m # VVs, K 200 400 # RVs, M 100 Virtul spee, v V 1 m/s RV spee 1 m/s Toke bucket cpcity, c 4 m Me computig time, E [T Ci ] 0 0.25 s Migrtio time, T Mi 0 # Computtios per VV 100 Policies FCFS G-TSP The simultio setup is summrize i Tble 2. The simultio ws oe o squre regio of size 10 m 10 m. There re 100 RVs, ech trvels t 1 m/s. The regio ws ivie ito 100 10 10) squre cells, ech with size 1 m 1m. Assig oe vehicle to ech cell. Ech vehicle serves its ow cell iepeetly uer FCFS or G-TSP. The toke bucket regultor hs toke rrivl rte v V 1 m/s bucket cpcity c 4 m. The migrtio time of ech computtio, T Mi. Cses tht the system hosts 200 400 VVs with virtul spee v V 1m/s, uiformly istribute tsk size with me 0 0.25 s re simulte results re show i Figure 4 5. Both figures give the results for the rge of me require spee up to v V 1 m/s s llowe i the SLA. Me elivere spee E[v D100 ] 7 6 5 4 3 2 1 0 v V 1, c4, #RV100, v1, 10 FCFS: #VV 200, T Ci G TSP: #VV 200, T Ci 0.4 0.5 0.6 0.7 0.8 0.9 1 Me require spee E[v R100 ] G TSP: #VV 200, E[T Ci ].25 FCFS: #VV 400, T Ci G TSP: #VV 400, T Ci Figure 4: Me elivere spee with icresig me require spee. Figure 4 shows tht the me elivere spee of computtio sequece of legth 100, v D100 or E [ v D100], ecreses s the me require spee, v R100 or E [ v R100], icreses. Uer FCFS, whe #VVs 200 computtio size, the me elivere spee is greter th v V 1, but whe #VVs 400, the me elivere spee flls below v V 1 whe the me require spee is greter th 0.9 m/s. Uer G-TSP, the me elivere spee is still greter th v V whe #VVs 400 computtio size. So G-TSP is better policy. Icresig the umber of VVs will ecrese the me elivere spee uer the sme me require spee uer FCFS G-TSP. Figure 5 shows tht the elivery probbility, ), ecreses s the me require spee i- P Vi D > Vi R creses. Uer G-TSP, whe #VVs 200 T Ci, P V D i > V R i ) 0.9 whe the me ) require is less > Vi R flls quickly to 0.55 th 0.9 m/s. But P V D i whe the me require spee pproches v V 1. The elivery probbility is high for most rge of me elivere spee llowe by the SLA. Similr ptter follows for the cses whe #VVs 200, E [T Ci ].25 #VVs 400, T Ci uer G-TSP, where P ) Vi D > Vi R 0.9 whe the me require is less th 0.8. To host the sme #VVs with the sme E [T Ci ], FCFS hs lower elivery probbility th G-TSP which iictes tht G-TSP is better. Higher #VVs lrger E [T Ci ] results i lower P ) Vi D > Vi R uer the sme me require spee. From the results we kow tht uer G-TSP, 100 RVs with spee 1 m/s c host 200 VVs with virtul spee 1 m/s while the me computtio size is 0.25 s host 400 VVs with spee 1 m/s while the computtio size is 0. The me elivere spee is greter th v V 1 m/s for ll the me require spee rge llowe

1 v V 1, c4, #RV100, v1, 10 service gurtees o me elivere spee elivery probbility. ) v R i P v D i 0.9 0.8 0.7 0.6 0.5 0.4 FCFS: #VV 200, T Ci G TSP: #VV 200, T Ci G TSP: #VV 200, E[T Ci ].25 FCFS: #VV 400, T Ci G TSP: #VV 400, T Ci 0.4 0.5 0.6 0.7 0.8 0.9 1 Me require spee E[v R100 ] Figure 5: Delivery probbility with icresig me require spee. by the SLA. The elivery probbility per tsk is greter th 90% for most rge of the me require spee. The provier c host give umber of VVs with fewer RVs opertig t the sme spee while proviig service gurtees o me elivere spee elivery probbility. 6. CONCLUSION This pper tkes the cocept of cyber-physicl clou computig CPCC) itrouce i [11] esigs service provisioig moel tht mkes CPCC s service possible. We efie the virtul vehicle through the ie of virtul vehicle moitor VVM) followig the forml efiitio of Popek et l. [21]. We esig service level greemet SLA) betwee the clou provier customer. The SLA iclues resource-level metrics, coformbility efiitios, service-level metrics. The resource-level metrics is virtul spee, costt provie by the CPCC provier. The coformble pplictio is efie through toke bucket regultor. The service-level metrics iclue the me elivere spee the probbility tht the elivere spee is greter th the require spee for computtio. We show tht the me require spee is boue by the virtul spee the burstiess of the require spee is boue by the bucket cpcity i Theorem 1. We show i Theorem 2 tht v D v R whe the computtio sequece legth goes to ifiity whe the system is stble, v D < v R whe is lrge eough whe the system is ot stble. The virtul vehicle moitor, implemetig FCFS G-TSP policies, is simulte the elivere performce is give i Figures 4 5. The simultio shows tht the provier c host give umber of VVs with fewer RVs opertig t the sme spee while proviig 7. REFERENCES [1] S. Akiok Y. Murok. HPC Bechmrks o Amzo EC2. I Avce Iformtio Networkig Applictios Workshops WAINA), 2010 IEEE 24th Itertiol Coferece o, pges 1029 1034, pril 2010. [2] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Ktz, A. Kowiski, G. Lee, D. A. Ptterso, A. Rbki, I. Stoic, M. Zhri. Above the Clous: A Berkeley View of Clou Computig. Techicl Report UCB/EECS-2009-28, EECS Deprtmet, Uiversity of Clifori, Berkeley, Feb 2009. [3] S. Crcius, A. Hs, C. Kirsch, H. Pyer, H. Röck, A. Rottm, A. Sokolov, R. Trummer, J. Love, R. Segupt. Iformtio-Acquisitio-s--Service for Cyber-Physicl Clou Computig. I Proc. Workshop o Hot Topics i Clou Computig HotClou), 2010. [4] R. L. Cruz. A clculus for etwork ely. Prt I. Network elemets i isoltio. IEEE Trsctios o Iformtio Theory, 371):114 131, J. 1991. [5] J. Fito, I. Goiri, J. Guitrt. SLA-rive Elstic Clou Hostig Provier. I Prllel, Distribute Network-Bse Processig PDP), 2010 18th Euromicro Itertiol Coferece o, pges 111 118, feb. 2010. [6] A. Ger C. H. Xi. Lerig Curves Stochstic Moels for Pricig Provisioig Clou Computig Services. Service Sciece, 31):99 109, 2011. [7] A. Ghose, P. Bisws, C. Bhumik, M. Shrm, A. Pl, A. Jh. Ro coitio moitorig lert pplictio: Usig i-vehicle Smrtphoe s Iteret-coecte sesor. I Pervsive Computig Commuictios Workshops PERCOM Workshops), 2012 IEEE Itertiol Coferece o, pges 489 491, mrch 2012. [8] I.. Goiri, F. Julià, J. O. Fitó, M. Mcís, J. Guitrt. Resource-level QoS metric for CPU-bse gurtees i clou proviers. I Proceeigs of the 7th itertiol coferece o Ecoomics of gris, clous, systems, services, GECON 10, pges 34 47, Berli, Heielberg, 2010. Spriger-Verlg. [9] Y.-C. Hsu, P. Liu, J.-J. Wu. Job sequece scheulig for clou computig. I Clou Service Computig CSC), 2011 Itertiol

Coferece o, pges 212 219, ec. 2011. [10] M. A. Iverso, F. Ozguer, G. J. Folle. Ru-Time Sttisticl Estimtio of Tsk Executio Times for Heterogeeous Distribute Computig. I Proceeigs of the 5th IEEE Itertiol Symposium o High Performce Distribute Computig, HPDC 96, pges 263, Wshigto, DC, USA, 1996. IEEE Computer Society. [11] C. Kirsch, E. Pereir, R. Segupt, H. Che, R. Hse, J. Hug, F. Lolt, M. Lipputz, A. Rottm, R. Swick, R. Trummer, D. Vizzii. Cyber-Physicl Clou Computig: The Biig Migrtio Problem. I Desig, Automtio Test i Europe, 2012. [12] M. Kleber, C. Krier, A. Schröcker, B. Zechmeister. ESE Cyber-Physicl Clou Computig Project clss project for the Embee Softwre Egieerig Course, Witer 2011/2012. [13] C. D. Krier. JNvigtor - A Autoomous Nvigtio System for the JAvitor Qurotor Helicopter. Mster s thesis, Uiversity of Slzburg, Austri, 2009. [14] J. Kurose. Ope issues chlleges i proviig qulity of service gurtees i high-spee etworks. SIGCOMM Comput. Commu. Rev., 231):6 15, J. 1993. [15] N. Le, E. Miluzzo, H. Lu, D. Peebles, T. Chouhury, A. Cmpbell. A survey of mobile phoe sesig. Commuictios Mgzie, IEEE, 489):140 150, sept. 2010. [16] G. Lee. Resource Alloctio Scheulig i Heterogeeous Clou Eviromets. PhD thesis, EECS Deprtmet, Uiversity of Clifori, Berkeley, My 2012. [17] G. Loi, F. Pzieri, D. Rossi, E. Turrii. SLA-Drive Clusterig of QoS-Awre Applictio Servers. IEEE Trs. Softw. Eg., 333):186 197, Mr. 2007. [18] S. Low P. Vriy. A New Approch to Service Provisioig i ATM Networks. IEEE/ACM Trsctios o Networkig, 1:547 553, 1993. [19] S. T. Mguluri, R. Srikt, L. Yig. Stochstic moels of lo blcig scheulig i clou computig clusters. I A. G. Greeberg K. Sohrby, eitors, INFOCOM, pges 702 710. IEEE, 2012. [20] P. Mell T. Grce. The NIST Defiitio of Clou Computig, Versio 15, Oct 2009. [21] G. J. Popek R. P. Golberg. Forml requiremets for virtulizble thir geertio rchitectures. Commu. ACM, 177):412 421, July 1974. [22] S. Rthim, Z. Kim, A. Soghiki, R. Segupt. Visio Bse Followig of Loclly Lier Structures usig Ume Aeril Vehicle. I Decisio Cotrol, 2005 2005 Europe Cotrol Coferece. CDC-ECC 05. 44th IEEE Coferece o, pges 6085 6090, 2005. [23] S. Rthim, R. Segupt, S. Drbh. A Resource Alloctio Algorithm for Multivehicle Systems With Noholoomic Costrits. Automtio Sciece Egieerig, IEEE Trsctios o, 41):98 104, j. 2007. [24] B. Reist D. K. Giffor. Sttic epeet costs for estimtig executio time. SIGPLAN Lisp Poiters, VII3):65 78, July 1994. [25] J. Roberts C.. P. M. Committee. Performce Evlutio Desig of Multiservice Networks: COST 224 : Fil Report, October 1991. EUR Series). Commissio of the Europe Commuities, Directorte-Geerl Telecommuictios, Iformtio Iustries, Iovtio, 1992. [26] A. Ry J. Herick. A moe-switchig pth pler for UAV-ssiste serch rescue. I Decisio Cotrol, 2005 2005 Europe Cotrol Coferece. CDC-ECC 05. 44th IEEE Coferece o, pges 1471 1476, ec. 2005. [27] W.-T. Tsi, X. Su, J. Blsooriy. Service-Oriete Clou Computig Architecture. I Iformtio Techology: New Geertios ITNG), 2010 Seveth Itertiol Coferece o, pges 684 689, pril 2010. [28] G. Veture, P.-J. Ripert, W. Khlil, M. Gutier, P. Boso. Moelig Ietifictio of Psseger Cr Dymics Usig Robotics Formlism. Itelliget Trsporttio Systems, IEEE Trsctios o, 73):349 359, sept. 2006. [29] D. Verm, H. Zhg, D. Ferrri. Gurteeig ely jitter bous i pcket switchig etworks. I Proc. Tricomm, pges 35 43, Chpel Hill, North Croli, 1991. [30] J. Yg, I. Ahm, A. Ghfoor. Estimtio of Executio times o Heterogeeous Supercomputer Architectures. I Proceeigs of the 1993 Itertiol Coferece o Prllel Processig - Volume 01, ICPP 93, pges 219 226, Wshigto, DC, USA, 1993. IEEE Computer Society. [31] Q. Zhg, L. Cheg, R. Boutb. Clou computig: stte-of-the-rt reserch chlleges. Jourl of Iteret Services Applictios, 1:7 18, 2010. 10.1007/s13174-010-0007-6.