Size: px
Start display at page:

Download "H.Bowman@ukc.ac.uk,G.Faconti@cnuce.cnr.itandM.Massink@guest.cnuce.cnr.it"

Transcription

1 3Dept.ofComputerScience,U.ofYork,Heslington,York,YO15DD,UK SpecicationandVericationofMedia 1ComputingLab.,U.ofKent,Canterbury,Kent,CT27NF,UK HowardBowman1,GiorgioP.Faconti2andMiekeMassink3 2CNR-IstitutoCNUCE,ViaS.Maria36,56126-Pisa-Italy ConstraintsusingUPPAAL? 1Introduction usedisthereal-timemodelcheckeruppaal. timediastream.thestreamisdescribedinatimedautomatanotation. Weverifythatthestreamsatisescertainqualityofserviceproperties, inparticular,throughputandend-to-endlatency.thevericationtool Abstract.Wepresenttheformalspecicationandvericationofamul- Theacceptanceandutilityofabroadrangeofapplicationsystemsissubstantiallyaectedbytheirabilitytopresentinformationinaneectiveandappealing informationneedswillvaryfromusertouserandfromsituationtosituation. tionproblem.furthermore,inthevastmajorityofnon-trivialapplicationsthe telligiblepresentationsperse.appropriatedesigndecisionsmustbedrawnthat leadtoanegraincoordinationofcommunicationmediaandmodalities.this mayevenbecomeaharderandmorecomplextaskthansolvingtheapplica- waytohumanusers.rapidprogressinthedevelopmentofmultimediatechnologypromisesmoreecientformsofman/machinecommunication.however,the useofmultimediaforconveyinginformationdoesnotguaranteeeectiveandin- Consequently,amultimediasystemshouldbeabletoexiblygeneratevarious ualrequirementsofusersandsituations,resourcelimitationsofthecomputing comprehensionofaparticulardesignspaceeitherbycontributingcomplementaryinformationorbyprovidingcriteriaaddressingequivalentrequirements.in reasoninganddecisions.dierentkindsofanalysiscontributetoaugmentthe thosecontributionsneedtoberelatedtooneanothertohelpsupportdesign system,andsoforth. addition,somedesignissuesmayberaisedbyoneparticularkindofanalysis manycomponentscontributingtothedesignofaninteractivesystem.otherdisciplinesprovidecomplementaryviewsandperspectivesondesignproblemsand Inthisrespect,technologybasedtechniquesandmodelsarejustoneoutof presentationsforoneandthesameinformationcontentinordertomeetindivid-?therstauthoriscurrentlyonleaveatcnuceunderthesupportoftheeuropean ResearchConsortiumforInformaticsandMathematics(ERCIM).

2 anotherdiscipline. fromadiscipline,butonlysolvedifanotherkindofanalysisisappliedfrom theliteratureofbothsoftwareengineeringandhuman/computerinteraction.althoughsignicantconceptualprogresshasbeenmadeinbothofthesedirections, theirgeneralapplicationrequiresustounderstandhowthebasicapproachescan nologybutrequirethatsystemdesignersbeinformedbothofwhyrequirements requirementscannotbeboundedinastraightforwardmannertoaspecictech- cognitivepsychology.withthecurrentstateoftheartinsystemdesign,these alizingmoreanalyticapproachesintothepracticalitiesofdesignexistalreadyin havebeenformulatedandhowtheycanpossiblybesatised.techniquesfor representingdesigndecisions,andframeworksforcommunicatingandcontextu- disciplinesdistantfromtechnologyandcomputersciencesuchassemioticsand Insuchascenario,manysystemrequirementsaregeneratedandderivedfrom actuallybeusedinpracticalsettings;thisremainsanopenissue. formultimediaobjects[11].examplesofapplicationsthatcanbedescribedare ispresented,integratingsystemconcernswiththenecessaryrepresentationof thatarelocatedintheabstractmodel,suchasthepresentationenvironment modeling.themodelisabstractsinceitidentiesthebasiccomponentsofapresentationsystemandrelatesthem.thedetailsareaddressedbyspecicmodels thecontextualizedknowledgeaboutdomainproblem,designprocess,anduser MediaPresentationSystems.Thisclassofsystemshasbeencharacterizedin [5]whereaReferenceModelforIntelligentMulti-MediaPresentationSystems Here,werefertoaparticularclassofinteractivesystems,namelyMultiindirectinteractionwiththemediaobjectstinguishingfeaturesbeingthecontinuityoftheinvolvedmedia,andthekindof teleconferencesandautomaticgenerationofmultimediahelpsystems,theirdis- underlyingtechnologyanditisdiculttopredictthedemandofcomputational resourcesrequiredtoachievethequalityofservicesetbytheend-user. tersreectperceivablepropertiesofthemediaobjectswithnodirectlinktothe sliderseachdealingwithaspecicparameter.theissueisthatsomeparame- algorithms,allocationofband)andtheglobalqualityofservice.in[2],forexample,itissuggestedthataudio/videoqualityofservicebecontrolledbyseparate themechanismsinuencingtheirpresentation(i.e.compression/decompression tionofthemediaobjectsthemselves(i.e.thevideocontent);rather,itaddresses Interactioninthesesystemsisindirectsinceitdoesn'tconcernthemanipula- ofasinglemediastreamsinceitdemandsintra?streamsynchronization,i.e. therelationshipbetweenmediaobjectswithinthesamedatastreamthusadding synchronization.however,continuityplaysalsoanimportantroleinthecontext timeconstraints,distinguishingtheseapplicationsfromtraditionalprotocols. mustsatisfyinter?mediasynchronizationconstraintsasinthecaseofthelip- Usualtechniquessuchasretransmissionofdataincaseoffaultsorlossesareno longerapplicableandthevericationofsystemthroughputandlatencyagainst thetimeconstraintsbecomesamust.asanexample,video/audiostreams Continuityreferstomediastreamsconveyingdigitalobjectswithassociated tothroughputandlatencyafurtherconstraintonjitter.

3 ofservicethatcanbeoeredbythemediumoverwhichtheinformationis thosesystemsistoimplementnewideasdirectlyinaprototypeandtomeasure theperformance.thisapproachisnotalwayssatisfactory.thecomplexityofthe transported.specicationandvericationofreal-timeaspectsof(multi)media systems.thequalityandtheusabilityofthosesystemsiscruciallydependent systemsishoweveradicultproblem.themostcommonapproachtobuilding tweenthequalityofthepresentationofmultimodalinformationandthequality ontheirperformancewithrespecttotimeliness.oftenthereisatrade-obe- Consequently,timingplaysanimportantroleinmultimediapresentation behaviourofthedistributedalgorithmsisoftenconsiderableandtheircorrectnessisdiculttoestimatebymeretesting.furthermore,itisoftenveryhard Thishasbeenillustratedforexamplein[10]whereanAudio/Videoprotocolhas beenanalyzedthathadbeendevelopedinanindustrialsetting. tondthecausesofrareerrorsandtoimprovetheimplementationaccordingly. issuesforthesingledatastreamcase.thisallowsustosetupabasicframework forfurtherworkonmulti-(inter-)mediasynchronizationwhileenablingtheinvestigationofthecapabilitiesandthepracticaluseofformalnotationsandtheir associatedtoolswithsmallsizeexperiments. Inthispaper,werestrictouranalysistotheinvestigationofanumberof 2ASimpleMediaStream Themostbasicrequirementforsupportingmultimediaistobeabletodene constraintmodelingusingsuchamultimediastream. Inthispaper,wewilldiscussandillustrateanumberofaspectsrelatedtomedia continuousowsofdata;suchstructuresaretypicallycalledmediastreams[4]. sinkinandplay,whichrespectivelytransferpacketsfromthesourcetothe Medium,fromtheMediumtotheSinkanddisplaythemattheSink. fromnowonsimplyrefertoasthemedium).thescenarioisthatthesource processgeneratesacontinuoussequenceofpackets1whicharerelayedbythe components:asource,asinkandacommunicationmedium(whichwewill MediumtoaSinkprocesswhichdisplaysthepackets.Threebasicinter-process communicationactionssupporttheowofdata(seegure1again),sourceout, Thebasicmediastreamisasdepictedingure1.Ithasthreetoplevel Howevertoourknowledge,noformalvericationshavebeenperformed.Thisis onecontributionofthispaper. similartothelotos/qtlspecicationthatappearsin[4]. Formaldescriptionsofmediastreamshavebeengivenbefore,e.g.[4]etc. 1Thesecouldbevideoframes,soundsamplesoranyotheriteminacontinuousmedia {TheMediumisunreliable;itmaylooseandreorderpackets. {AllcommunicationbetweentheSourceandtheSinkisasynchronous. tiationofdataparameterswillspecializethescenario. transmission.inthiswaythescenarioremainscompletelygeneric.however,instan- Thefollowinginformaldescriptionofthebehaviourofthestreamiskept

4 Fig.1.AMultimediaStream Process Process play sourceout sinkin tainqualityofserviceproperties.conceptually,thesepropertiescanbeviewed Thenwefocusonourmainobjective:tocheckthatthissystemsatisescer- {TheSourcetransmitsapacketevery50ms(i.e.20packetspersecond). {PacketsthatdonotgetlostarriveattheSinkbetween80msand90ms {WhenevertheSinkreceivesapacket,itneeds5mstoprocessit,afterwhich Insection4,wewillpresentanUPPAALdescriptionofthisbasicbehaviour. aftertheirtransmission.thisisthelatencyofthemedium. itisreadytoreceivethenextpacket. propertiesthatwewishtoverifyare: asbeingderivedfromuserpresentationrequirements.thequalityofservice 1.Throughput.WewouldliketoensurethattheSinkprocessreceivespacketsattherateofbetween: 2.Latency.Wewillcheckthefollowinglatencyproperty: Clearly,thereisadirectlinkbetweentherateoflossoftheMediumand thethroughputatthesink.thus,theavourofourinvestigationofthis Wewillalsobuildintothesystemthepossibilitythatitcangointoanerror propertywillbetodeterminewhataretheboundsontherateatwhichthe stateandhalt,ifthethroughputpropertyisinvalidated. Mediumloosesmessagesinordertosatisfythisthroughputproperty. 15and20packetspersecond. 3.Jitter.Jitterisdenedasthevarianceofdelay.Itensuresthatthereisnot anunacceptablevariabilityaroundtheoptimumpresentationtime,e.g.if onepacketispresentedquiteearlyandthenextispresentedrelativelylate anunacceptablestutterinthepresentationwillresult.afullanalysisofjitter wouldrequirestochastictechniques[9]tobeemployed.thisisclearlynot whichputsanupperboundontheend-to-endtransmissiondelay. Theend-to-enddelaybetweenasourceoutactionanditscorrespondingsinkinactioncannotbemorethan95ms.

5 possiblewiththevericationtechnologywehaveavailabletous.however, timesystems.ithasbeendevelopedatbricsindenmarkandatuppsala UPPAALisatool-suiteforthespecicationandautomaticvericationofreal- 3IntroductiontoUPPAAL boundonjitter.apartfromnotingthatwecouldextendourlatencyanalysis todothis,wedonotconsiderthepropertyanyfurtherinthispaper. placingbothanupperandlowerboundonthelatencywouldimposeacrude specicationcanbeusedbythegraphicalsimulator`simta'orbeautomatically thetoolautographortextuallybymeansofanormaltexteditor.thegraphical Thebehaviourofanetworkofautomatacanbeanalyzedbymeansofthesimulatorandreachabilitypropertiescanbecheckedbymeansofthemodelchecker. ofextendedtimedautomatawithglobalreal-valuedclocksandintegervariables. UniversityinSweden.InUPPAALareal-timesystemismodeledasanetwork togetherwithalewithrequirementstobecheckedonthemodel.there- thatshowsapossibleviolationoftheproperty.thistracecanbefedbacktothe propertyissatisedornot.itthepropertyisnotsatisedatraceisprovided quirementsareformulasinasimpletemporallogiclanguagethatallowsforthe formulationofreachabilityproperties.themodelcheckerindicateswhethera InUPPAAL,automatacanbespeciedintwoways.Graphicallybyusing translatedintotextualformandusedasinputforthemodelchecker`verifyta' ofthecongurationofthenetwork.inthecongurationtheglobalreal-time labeled.anetworkofautomataconsistsofanumberofautomataandadenition nodes,whicharecalledlocations,andtheedges,whicharecalledtransitions,are 3.1TheUPPAALmodel UPPAALautomataconsistofnodesandedgesbetweenthenodes.Boththe simulatorsothatitcanbeanalyzedwiththehelpofthegraphicalpresentation. clocks,theintegervariables,thecommunicationchannelsandthecomposition ofthenetworkaredened. {aguardonclocksanddatavariablesexpressingunderwhichconditionthe {asynchronizationorinternalactionthatisperformedwhenthetransition Thelabelsonedgesarecomposedofthreeoptionalcomponents: withacomplementaryactioninanotherautomatonisenforcedfollowing istaken.incasetheactionisasynchronizationactionthensynchronization transitioncanbeperformed.absenceofaguardisinterpretedastheconditiontrue. {anumberofclockresetsandassignmentstointegervariables asaninternalactionsimilarto-actionsinccs. ceivingonthechannela.absenceofasynchronizationactionisinterpreted a?denotecomplementaryactionscorrespondingtosendingrespectivelyre- similarsynchronizationrulesasinccs[14].givenchannelnamea,a!and

6 Thelabeloflocationsconsistsalsoofthreeparts: {thenameofthelocationwhichisobligatory. Intheconguration,thefollowingaspectsofthenetworkaredened: {anoptionalmarkingofthelocationbyputtingc:infrontofitsnameindicatingthelocationascommitted.thisoptionisusefultomodelatomicity {aninvariantexpressingconstraintsonclockvalues,indicatingtheperiod duringwhichcontrolcanremaininthatparticularlocation. {thechannelnamesthatarethenamesoftheactions.channelscanbedened {declarationsofglobalclockandintegervariables transitionmustbeperformed(ifany)withoutanydelayorinterleavingof otheractions. oftransition-sequences.whencontrolisinacommittedlocationthenext asnormalcommunicationchannelsorurgentchannels.whenachannelis thatchannelandnoinvariantcanbedenedonthelocationfromwhich urgentnotimingconstraintscanbedenedonthetransitionlabeledby thecurrentvalueforeachclockandintegervariable.allclocksproceedatthe thattransitionleaves.urgentactionshavetohappenassoonaspossible, samespeed.therearethreetypesoftransitionsinanuppaalmodel: controllocationforeachcomponentofthenetwork.thevalueassignmentgives controlvectorandvavalueassignment.thecontrolvectorindicatesthecurrent {thelistofnamesofautomatathesystemiscomposedof. Formally,thestatesofanUPPAALmodelareoftheform(l;v),wherelisa i.e.withoutdelay,butinterleavingofotheractionsisallowedifthisdoesnot causedelays. DelayAdelaytransitioncanoccurwhennourgenttransitionsareenabled, InternaltransitionsSuchtransitionscanoccurwhenanautomatoninthe SynchronizationAsynchronizationtransitioncanoccurwhentherearetwo networkisatalocationinwhichitcanperformaninternalaction.the guardofthattransitionhastobesatisedandtheremustbenoother betweens1ands2canonlybetakenwhenthevalueofclockyisgreaterthan AnexampleofanUPPAALspecicationisgiveninFigure2.Thetransition transitionsenabledthatstartfromacommittedlocation. isallowedbytheinvariantsofthecurrentcontrollocations. noneofthecurrentcontrollocationsisacommittedlocationandthedelay automatawhichareinlocationsthatcanperformcomplementaryactions. orequalto3.thisholdsalsoforthetransitionbetweenr1andr2becausethe Theguardsofbothtransitionsmustbesatisedandtheremustbenoother automataaandbaresynchronizedonchannela.thetransitionmusthappen beforeyisequalto6becauseoftheinvariantatlocations1.ifthisinvariant wouldnotbetherecontrolcouldhaveremainedins1andinr1indenitely.

7 A Config y >= 3 b? a! clock x, y; y := 0 int n; n == 3 chan a; chronizationonactionb.thisisbecausebhasbeendeclaredasanurgentchannel urgent chan b; s1 s2 s3 s4 system A, B; (y <= 6) y 4 ingthetransitionbetweens2ands3inabothtransitionsbetweenthosetwo intheconguration.notethatiftheguardy>=4wouldnothavebeenlabel- locationswouldhavebeenenabled!thisisbecauseurgencyonlypreventsthe Fig.2.ExampleofanUPPAALspecication B x 2 a? n := 3 b! tionr2canbeannotatedasacommittedlocation.thisforcestheactionbto x := 0 n := n + 1 happenwithoutdelayorinterferenceofotheractions. enabledatthesametime.topreventinterleavingactionsinthiscasetheloca- passingoftime,butdoesnotpreventtheoccurrenceofotheractionsthatare Whencontrolisins2andr2theonlytransitionthatispossibleisthesyn- r1 c:r3 r4 dierentclockvalueshaverunsstartingfromlthatare\verysimilar".alurand Dilldescribedexactlyhowtoderivethesetsofclockvaluesforwhichthemodel vationmadebyaluranddillwasthatstateswiththesamelbutwithslightly shows\similar"behaviour[1].thesetsofclockvaluesarecalledtimeregions. state,i.e.thecontrolvectorl,andthevalueofallitsclocksanddatavariables. Clearlythisleadstoamodelwithinnitelymanystates.Theinterestingobser- Thefuturebehaviourofanetworkoftimedautomataisfullydeterminedbyits 3.2SimulationandModelChecking Regionscanbederivedfromtheguards,theinvariantsandthereset-setsinthe UPPAALmodel.Sinceclockvariablesintheconstraintsarealwayscompared oftheseconstraintsetsforsimulationandmodelcheckingcanbefoundin[15]. withintegersandbecauseineverymodelthereisamaximumintegerwithwhich areconjunctionsofatomicclockanddataconstraints.detailsonthecalculation aclockiscomparedthestatespaceofamodelcanbepartitionedintonitely manyregions.thismakesmodelcheckingfordensetimedecidable. InUPPAALtheregionsarecharacterizedbysimpleconstraintsystemswhich

8 properties.theyareformulasofthefollowingform: Thepropertiesthatcanbeanalyzedbythemodelcheckerarereachability ande<>,where,informally,a[]requiresallreachablestatestosatisfyand E<>requiresatleastonereachablestatetosatisfy. lalocationofaiorvinwhereviisavariable,nanaturalnumberand whereaisanatomicformulaoftheform:ai:lwhereaiisanautomatonand arelationinf<;<=;>;>=;==g.thebasictemporallogicoperatorsare,a[] ::=aj1and2j1or2j1implies2jnot ::=A[]jE<> formedinuppaalrangingfromsmallexamplestorealindustrialcasestudies, e.g.[3,7,12]. inglanguagethatisascloseaspossibletoahigh-levelreal-timeprogramming languagewithvariousdatatypesthe,currentversionisratherrestrictive.for exampleitdoesnotallowassignmentofvariablestoothervariablesandthereis novalue-passinginthecommunication. Despitetheserestrictions,quiteanumberofcase-studieshavebeenper- AlthoughthenalaimofthedevelopersofUPPAAListodevelopamodel- 4StreamexampleformalizedinUPPAAL 4.1Thebasicmodel guardt1==50enablesthesendingofsourceoutatexactly50msafterthelast sentevery50ms.tomakethismorepreciseweassumethattherstpacketis sentattimeequal0andalllaterpacketsexactly50msoneaftertheother.this Considerthestreamexampleintroducedinsection2.Thesimplestpartofthe one.theinvariantatenforcesthattheenabledtransitionreallyhappens location(indicatedbyadoublecircle)isannotatedascommittedtoenforcethat therstpacket(sourceout!)issentimmediately.toassurethateveryfollowing packetissentexactly50msafterthepreviousone,aclockt1isintroduced.the exampleisthesource.intheinformalspecicationitissaidthatapacketis att1==50.whenthetransitionisperformedt1isresetandthebehaviour behaviourismodeledasanuppaalautomatonwithtwolocations.theinitial repeatsitself. itmaylooseandreorderpackets.atrstsightweshouldmodelthemedium packet.wheneveritreceivesapacketitplaysitimmediatelyduringthenext thatitactsasaninnitebuer,ithasalatencyofbetween80msand90ms, 5ms.Thisbehaviourismodeledbyanotherautomatonwithtwolocations.In theinitiallocationtheautomatonwaitsforapacketfromthemedium.whenit arrivesatimert2issetthatisusedtomodelthe5msdelaycausedbyplaying ofthepacketbeforecontrolreturnstotheinitiallocation. TheSinkisrequiredtoalwaysacceptapacket,exceptwhenitisplayinga Thethirdparttomodelisthemedium.Whatisknownofthemediumis

9 asaninnitestructure.however,ifweareonlyinterestedinthethroughputof andatmost90ms. medium.thesinkinactionfollowingthesourceoutisdelayedbyatleast80ms fromthesource.atthatpointatimerisstartedtomodelthelatencyofthe thatwemodelthemediuminsuchawaythatitalwaysallowsthesourceto performthenextsourceout.wewillshowthatthemediumcanbemodeledby themedium,theorderinwhichpacketsarriveisirrelevant.whatisrelevantis locations(seefigure3).attheinitiallocationthebuercanreceiveasourceout twoindependentone-place-buers.werstmodelthemediumassumingthat itdoesnotloosepackets.eachbuerismodeledasanautomatonwithtwo Source Place1 Place2 buers,weshouldprovethatitisneverthecasethatwhenthesourcewishes theyareinlocation.inuppaalthissituationcanbeformalizedas: toperformasourceout,i.e.whent1==50,bothone-place-buersarefull,i.e. Tobesurethatitwascorrecttomodelthemediumbyonlytwoone-place- E<>(t1==50andPlace1:andPlace2:) Fig.3.UPPAALspecicationofmediastream belessthan45mstherearegoingtobeproblems.inourmodelwecaneasily constraintsusedinthemodel.ifthetimebetweenpacketsatthesourcewould toguaranteethatthesourcecanalwayssenditspacketdependsonthetime whichusingtheuppaalmodelcheckercanbeshownnottohold. ItisimportanttonotehoweverthattheminimalnumberofPlacesneeded Config c:state0 sourceout! t1 == 50 sourceout! t1 := 0 (t1 <= 50) clock t1, t2, t3, t4; int l; chan sourceout, sinkin, play; system Source, Sink, Place1, Place2; sinkin! t4 > 80 sourceout? t4 := 0 (t4 <= 90) sinkin! t3 > 80 sinkin? t2 := 0 play t2 == 5 sourceout? t3 := 0 (t3 <= 90) (t2 <= 5) Sink

10 timebetweenpacketssentbythesourcethen: latency.letpbethenumberofplaces,mthemaximallatencyanddtheinterval ofplacesneededasafunctionofthetimebetweenthepacketsandthemaximal exampleitisnotdiculttondageneralformulathatgivestheminimalnumber verifythisbymeansofthereachabilitypropertyweformulatedbefore.inthis retransmissionprotocol[7]. modelcheckingcanbefoundinthedescriptionofacasestudyonabounded Ingeneralhowever,timedependentbehaviourcanbeveryhardtopredictand holdbetweenparametersofthesystem.aninterestingillustrationofthisuseof amodelcheckercanbehelpfultogetagoodintuitionabouttherelationsthat p=dm=de(+) 4.2Modelingamediumwithlosses Inthissectionwerelaxtheassumptionthatthemediumdoesnotloosepackets. Weassumethatthelossesarelimitedtonotmorethan4packetspersecond. thenextsection). andweneedtoadapttheautomatamodelingtheplaces.wemodeltheloss containsmoreadditionsthanjustthenewmedium;thesewillbeexplainedin thenumberoflosses.thetransitionisguardedbyaconstraintonthemaximal numberoflosses.figure4showsthenewmedium(infact,thisspecication automatathatmodeltheplaces.furtherweaddaglobalvariablelthatrecords ofapacketbyanadditionalinternaltransitionfromtointhe TomodelthisweneedaMonitorthatkeepstrackofthepassingseconds 5VerifyingQualityofServicewithUPPAAL whenitisbelowthethresholdof15packetspersecondanerrorissignaled. 5.1Throughput Letusassumethatthethroughputofthemediumischeckedeverysecondand earlierinthispapercanbeveriedusinguppaal. Inthissectionweinvestigatehowthequalityofservicepropertiesidentied i.e.ifx<15,thisisbecausethepossibilityoftoomanyframesarriving,i.e. forthemonitorandthesinkareshown. generated.assoonasthesinkreachesstateitwillsynchronizeonthe thetimerstartsagain.ifthethroughputistoolowanurgentactionerroris erroractionandthemediastreamwillbestopped.infigure4theautomata xwhichisupdatedeverytimeasinkinactionoccurs.themonitorchecks thevariablexeverysecond.ifthethroughputissucientthenxisresetand TheMonitorthatwepresentonlyforcesanerroriftoofewframesarrive, ThenumberofpacketsthatarriveattheSinkiscountedbyaglobalvariable

11 catersforthissituation. necessarywecouldeasilyaddanextrabranchinthetransitionsystemwhich x>20,cannotarisebecauseoftheparametersofthesystem.however,ifitwas rateoflossinthemedium.usinguppaalwecanshowthatiftheconstraint hold.assuggestedearlier,theobviousparameterthataectsthroughputisthe ourspecicationsatisestheformula: ourthroughputproperty.specically,wecancheckunderwhatcircumstances Satisfactionofthisformulaimpliesthatourthroughputrequirementdoesnot Inaddition,wecanuseUPPAALtodeterminetheparametersthatbound l<4isassociatedwiththelossactioninthemedium,asitisingure4,then thestopstatecanbereached,anduppaalprovidesasampletrace.however, ifwechangetheconstrainttol<3thenthestopstatecannotbereached.thus, thisgivesusaclearboundonthenumberoferrorsthatanacceptablemedium E<>(Sink:Stop) shouldallow. hastwooutgoingtransitions,errorandsinkin,ifisreachedatatime atarateofaframeevery50msthenthissituationcannotarise(interestingly,if itwastransmittingattherateofaframeevery53msthesituationcouldindeed pointinwhichbothtransitionsareenabledtheneventhougherrorisanurgent ananalysiscanbemadethatshowsthataslongasthesourceistransmitting action,eithertransitionmaybetaken.thiswouldclearlybeundesirableasone wouldlikethesystemtostopassoonasitisinerror.however,usinguppaal arise). AsubtlepointthatarisesfromthisspecicationisthatsinceinSink notalwaysbethecase.infact,inrealworldsystems,communicationmediums easilydiscernedbyinspectionfromtheautomataspecicationgiven,thiswill Althoughinfact,upperandlowerboundsforlatencyofthestreamcanbevery 5.2VerifyingLatency somemeansofidentifyingcorrespondingpackets,e.g.bymeansoftimestamps wemustrelatecorrespondingsourceoutandplayactions.inordertodothis latencydelays.furthermore,inthepresenceofcongestion,analysisoflatencyis farfromstraightforward.thus,eventhoughanalysinglatencyisrathersuperuousinourstreamscenario,itisavaluableexercisetodeterminethesuitability ofuppaalinthisrespect. havehighlycomplexreal-timebehaviour.forexample,theremaybeanumberof dierentpotentialroutesthatframescantake,eachaccumulatingverydierent orsequencenumbers,mustbeincluded. numbering.theobviouspropertythatwewouldliketoverifyis: So,letusformulateourbasiclatencypropertywiththerequiredsequence Therstthingtonoteisthatinordertoexpressourlatencyrequirement 8x2IN:(2(play(x))3-95sourceout(x)))

12 Source Place1 Place2 Config c:state0 sourceout! t1 == 50 sourceout! t1 := 0 (t1 <= 50) sinkin! t4 > 80 clock t, t1, t2, t3, t4; int x, l; urgent chan error; chan sourceout, sinkin, play, stop, loss; system Source, Sink, Place1, Place2, Monitor; t == 1000 t == 1000 x >= 15 x < 15 x <= 20 l := 0 l := 0 x := 0 x := 0 t := 0 t := 0 error! (t <= 1000) sourceout? t4 := 0 l < 4 loss l := l + 1 Monitor (t4 <= 90) Stop sinkin! t3 > 80 error? Stop )islogicalimplicationand3-tpisapasttenseoperatorstatingthat,pmust contrastwiththebranchingtimeoperatorsusedinuppaal.2pisthealways/henceforthoperator(i.e.inthefutureitisalwaysthecasethatpholds), statesthatitisalwaysthecasethat,ifaplayoccursthenatsomepointnot wheretheoperatorsusedarelineartimetemporallogicoperators[13],which Fig.4.UPPAALspecicationofmediastreamwithQoSMonitor holdnomorethanttimeunitsbeforethecurrentmoment.so,theformula morethan95msbeforeasourceoutmusthavetakenplace.thesignicanceof thepastoperatoristhatitallowsforlossinthesystem,i.e.itonlyenforcesa timingconstraintontheplaysthatarisefromsuccessfullyreceivedpackets. themoment,letusconcentrateontherst.theproblemisthatweneedto arenotsupportedatpresentbyuppaal. reasonsforthis. 2.expressingdatapassingactions 1.Innitedatasets,suchasthenaturalnumbers;and Wewillshowhowtohandlethesecondofthesedicultiesshortly,butfor However,thispropertycannotbeveriedusingUPPAAL.Therearetwo resultingautomatonandthestatespaceexplosionproblemifwecankeepthe boundthesetofsequencenumbersusedandinfact,itwillgreatlysimplifythe sizeofthisboundverysmall. numbersthatwedonotgettwopacketswiththesamesequencenumberinthe Whatwewouldliketoensureisthatwehaveasucientnumberofsequence sourceout? t3 := 0 sinkin? x := x + 1 t2 := 0 play t2 == 5 (t3 <= 90) l < 4 loss l := l + 1 (t2 <= 5) Sink

13 systematthesametime.thisisasimilarrequirementtotheboundingofthe sizeofthemediuminvestigatedinsection4.1.infact,wecanuseformula(+) behavingsystem.importantlythough,wereplacemintheformulawiththe statedtheretoderivethattwosequencenumbersaresucientinacorrectly passingactionsbyincludingamorediscriminatingsetofactionsandincluding extratransitions2.thesinkinfigure5isagoodillustrationoftheapproach. actionsinuppaalarenotdatapassinghowever,wecangettheeectofdata desiredlatencyvalueratherthantheknownone. Specically,ratherthanreferingtoactionssinkinandplayaswasthecase wehavetoadaptourautomataspecicationaccordingly.nowasalreadynoted, sinkin1?,play0?andplay1?.thus,wehaveattenedoutourdatatypeintoa inourearlierformulationsofthestream,nowitreferstoactionssinkin0?, morediscriminatingsetofactionnames. Havingdecidedthattwosequencenumbers,i.e.1and0,willbesucient operators3.wecouldthoughreformulatethepropertyas: Theformulathatwewouldliketoverifyoverthisautomatais: Unfortunatelyafurtherproblemremains:UPPAALdoesnotsupportpast whichavoidsthepastoperator.howeverwepreferanalternativeapproach 8x2f0;1g:(2(sourceout(x))395(play(x)_loss(x))))() 8x2f0;1g:(2(play(x))3-95sourceout(x)))() thatavoidsthereferencetoloss.thisisbecauselatencyisanend-to-endpropertyandformulatingintermsofactionslocaltocomponentsofthecommunicationpathseemsconceptuallyunsatisfactory.thus,wewouldliketoview themediumasablackboxandformulateourpropertypurelyintermsofthe \end-point"actionssourceoutandplay. willimplicitlyreducelatencyvalues.thus,areasonablestrategyistodetermine Inthepresenceofcongestion,losswillrelievecongestionandthusallowingloss knowingthatifitisadded,thisboundwillstillbevalid.thisisthestrategy toloosepackets.themediumisasshowninfigure5. upperboundsonlatencyonastreamspecicationwhichdoesnotallowloss, thatweadopt. Inordertodothis,letusconsidertheinterplaybetweenlossandlatency. 2Thisisinfactastandardapproachinprocessalgebrasforgettingfromadatapassing 3Actually,thereisinanycasearathersubtleproblemwiththisformula,todowiththe So,letusworkwithabasicmediumwhichdoesnotcontainthepossibility latency. interplaybetweenthepossibilitytoloosemessagesandnotknowingtheend-to-end calculustoabasiccalculus,seeforexample[14]. Nowthepropertythatwehavetocheckis: 8x2f0;1g:(2(sourceout(x))395play(x)))

14 ordertomatchactiondenotationsintheautomaton). quantier,whichisnotsupportedinuppaal(note:wewritea(n)asanin whichcan,inthestandardway,beexpandedouttoavoidtheuniversal algorithm,composethetestingautomatoninparallelwiththesystemandverifyasimplereachabilityproperty.thisstrategyisnotyetimplementedinthe istoderiveatestingautomatonfromthepropertyusingaformoftableau UPPAALtool,sotheautomatonhasbeenderivedbyhandusingtheinformal veriedusinguppaal.astrategyoutlinedin[12]canthoughbeusedtoverify sucha\boundedliveness"propertyusingreachabilityanalysis.theapproach However,thisisnotareachabilitypropertyandcanthus,notbedirectly 2(sourceout0)395play0)^2(sourceout1)395play1) usedtochecksourceout1'sandplay1's. algorithmstobefoundintheliterature[12]. areexpressedinadierentlogictoanythatwehaveseensofar:stl,atimed thatsourceout0sandplay0sarecorrectlymatched.asimilarapproachcanbe automatonthatisderivedfromtheformula.itisshowninfigure5alongwith thefullrevisedstreamspecication.infact,thisisthescenariousedtocheck modallogic.ourpropertycan,withrelativeease,beexpressedinthislogic however,ratherthanintroduceanotherlogic,wewillgostraighttothetesting Notethatsgout0isaprobeactionthathasbeeninsertedatappropriate Theboundedlivenesspropertiesacceptedbythetestingautomatonapproach currenceofsourceoutstothetestautomaton. placesinthesystem.itisinserted(usingacommittedstate)tosignaltheoc- Thepropertythatwecheckis: applicable. forcheckinglatencywhichcanbeappliedtosystemsthatarenotsoeasily directlydeduciblebyinspectionofthesystem.thus,thecontributionofthis interpreted.itisclearthatthestrategywehavedocumentedisindeedgenerally Howeverasindicatedearlier,thisisnotaveryinterestingresultbecauseitis sectionisnotthisverication,butrathertheinvestigationofageneralstrategy which,whencheckedwithuppaaldoes,aswouldbehoped,failtohold. E<>(Tester:bad) 6ConcludingRemarks WehaveinvestigatedthesuitabilityofUPPAALforthevericationofmultimediasystems.Thespecicationandanalysisofasimplemultimediastreacationofgenerallyapplicablestrategiesforcheckingreal-timequalityofservice properties,specically,checkingthroughputandlatency. somecriticismsoftheapproachcanbehighlighted.[6]considersanumberof waspresentedforthispurpose.themainresultsofthispaperaretheidenti- AlthoughourexperienceswithUPPAALhavegenerallybeenfavourable,

15 c:state0 Source Place1 Place2 sourceout0! c:s01 sgout0! (t1 <= 50) t1 == 50 sourceout1! sgout0! sinkin0! t4 > 80 sourceout0? t4 := 0 sinkin1! t3 > 80 sourceout1? t3 := 0 (t1 <= 100) c:s02 t1 == 100 sourceout0! t1 := 0 (t4 <= 90) (t3 <= 90) Config clock t, t1, t2, t3, t4; chan sourceout0, sourceout1, sinkin0, sinkin1, play0, play1, sgout0; system Source, Sink, Place1, Place2, Tester; st1 sgout0? t := 0 st3 t <= 95 play0? t > 95 bad st4 Tester sinkin1? t2 := 0 sinkin0? t2 := 0 play1! t2 == 5 State3 (t2 <= 5) t := 0Fig.5.TheStreamwithTestingAutomata play0! t2 == 5 (t2 <= 5) Sink suchcriticisms.onecriticismisthoughparticularlyworthconsideringhereas itarisesdirectlyfromourcasestudy.itisthatduetoexpressivenesslimitations directlyverifythestandardtemporallogicformulationsofqualityofservice, ofthetemporallogicacceptedbytheuppaalmodelcheckeritisdicultto ratherthebasicsystemspecicationhastobeadaptedinorderthatchecking thepropertycanbereducedtocheckingareachabilityproperty.thiscanmost noticeablybeseeninthelatencyvericationwherethebasicsystemspecication hastobeadaptedthroughcompositionofatestautomataandadditionofprobe actions.consequentlythevericationisnot\transparent"tothebehavioural arichersetoftemporallogicproperties.thus,wehopethatvericationthat specication. avoidssuchinvasiveadaptationofthebasicsystemspecicationmaybepossible withkronos.ongoingresearchisinvestigatingapplicationofkronostothe multimediastreamcasestudy. Otherreal-timemodelcheckingtools,inparticularKRONOS[8],support

16 WewouldliketothankStavrosTripakisofSPECTRE-VERIMAGandPaul timedautomataanduppaalrespectively. Acknowledgements References PetterssonofUPPSALAwhoeldedqueriesthatwehadonmodelcheckingof 2.V.BellottiandA.MacLean.Integratingandcommunicatingdesignperspec- 1.R.AlurandD.Dill.Atheoryoftimedautomata.TheoreticalComputerScience, 3.JohanBengtsson,W.O.DavidGrioen,KareJ.Kristoersen,KimG.Larsen, (126):183{235,1994. ingsofthe8thinternationalconferenceoncomputer-aidedverication,lncs tiveswithqocdesignrationale.technicalreportid/wp29,esprit7040- FredrikLarsson,PaulPettersson,andWangYi.Vericationofanaudioprotocol withbuscollisionusinguppaal.inr.alurandt.a.henzinger,editors,proceed- AMODEUS, H.Bowman,G.Faconti,J-P.Katoen,D.Latella,andM.Massink.Automaticveri- 4.G.S.Blair,L.Blair,H.Bowman,andA.Chetwynd.FormalSpecicationofDistributedMultimediaSystems.UniversityCollegeLondonPress,September ,pages244{256,NewBrunswick,NewJersey,USA,July M.Bordegoni,G.Faconti,S.Feiner,M.Maybury,T.Rist,S.Ruggieri,P.Trahanias, ComputerStandardsandInterfaces,1998. andm.wilson.astandardreferencemodelforintelligentpresentationsystems. cationofalipsynchronisationalgorithmusinguppaal.acceptedatfmics'98, Amsterdam,TheNetherlands,May KlausHavelund,ArneSkou,KimG.Larsen,andKristianLund.Formalmodelling 8.C.Daws,A.Olivero,S.Tripakis,andS.Yovine.ThetoolKRONOS.InHybrid 9.P.G.HarrisonandN.M.Patel.PerformanceModellingofCommunicationNetworksandComputerArchitectures.Addison-Wesley,1993transmissionprotocolmustbeontime!InProceedingsofthe3rdInternational 7.P.R.D'Argenio,J.-P.Katoen,T.C.Ruys,andJ.Tretmans.Theboundedre- andanalysisofanaudio/videoprotocol:anindustrialcasestudyusinguppaal. LNCS1217,pages416{431,Enschede,TheNetherlands,April1997. SystemsIII,LNCS1066.Springer-Verlag,1996. WorkshoponToolsandAlgorithmsfortheConstructionandAnalysisofSystems, InProceedingsofthe18thIEEEReal-TimeSystemsSymposium,pages2{13,San 15.WangYi,PaulPettersson,andMatsDaniels.Automaticvericationofreal-time 14.R.Milner.CommunicationandConcurrency.Prentice-Hall, Z.MannaandA.Pnueli.TheTemporalLogicofReactiveandConcurrentSystems. 12.HenrikEjersboJensen,KimG.Larsen,andArneSkou.Modellingandanalysis 11.I.Herman,G.Reynolds,andJ.VanLoo.PREMO:Anemergingstandardfor Springer-Verlag,1992. SPINWorkshop,RutgersUniversity,NewJersey,USA,August1996. multimedia.parti:overviewandframework.ieeemultimedia,3:83{89,1996. ofacollisionavoidanceprotocolusingspinanduppaal.inproceedingsofthe2nd Francisco,California,USA,3-5December1997. nationalconferenceonformaldescriptiontechniques,berne,switzerland,4-7 October1994. communicatingsystemsbyconstraintsolving.inproceedingsofthe7thinter-

Finance & CS. Banks. Consumer/Personal Loans. Deposits vs Loans. Credit Cards. Commercial/Business Loans

Finance & CS. Banks. Consumer/Personal Loans. Deposits vs Loans. Credit Cards. Commercial/Business Loans Banks Finance & CS Why do banks pay interest to you for your deposit? Banks also need to pay for staff, ATM machines, buildings Philip Chan How do banks make money? Deposits vs Loans Banks make money by

More information

Practical Aspects of IP based Take Over Mechanisms. Christof Fetzer, Neeraj Suri AT&T Labs Research, Florham Park, NJ TU Darmstadt, Germany

Practical Aspects of IP based Take Over Mechanisms. Christof Fetzer, Neeraj Suri AT&T Labs Research, Florham Park, NJ TU Darmstadt, Germany Practical Aspects of IP based Take Over Mechanisms Christof Fetzer, Neeraj Suri AT&T Labs Research, Florham Park, NJ TU Darmstadt, Germany Motivation Problem: What is a good way to increase the availability

More information

RAID5 Scaling. extremesan Performance 1

RAID5 Scaling. extremesan Performance 1 RAID5 Scaling Objective: Show Linear Scaling of extremesan in RAID 5 sets under increasing load Config: 4 volumes of 4 drive RAID 5, 4 initiators, each with 2 connections. Sequential Read/Write test. Results:

More information

Prevention, Detection, Mitigation

Prevention, Detection, Mitigation Thesis for the Degree of DOCTOR OF PHILOSOPHY Multifaceted Defense Against Distributed Denial of Service Attacks: Prevention, Detection, Mitigation Zhang Fu Division of Networks and Systems Department

More information

NVIDIA Tools For Profiling And Monitoring. David Goodwin

NVIDIA Tools For Profiling And Monitoring. David Goodwin NVIDIA Tools For Profiling And Monitoring David Goodwin Outline CUDA Profiling and Monitoring Libraries Tools Technologies Directions CScADS Summer 2012 Workshop on Performance Tools for Extreme Scale

More information

Implementation of Full -Parallelism AES Encryption and Decryption

Implementation of Full -Parallelism AES Encryption and Decryption Implementation of Full -Parallelism AES Encryption and Decryption M.Anto Merline M.E-Commuication Systems, ECE Department K.Ramakrishnan College of Engineering-Samayapuram, Trichy. Abstract-Advanced Encryption

More information

Lecture 3: Evaluating Computer Architectures. Software & Hardware: The Virtuous Cycle?

Lecture 3: Evaluating Computer Architectures. Software & Hardware: The Virtuous Cycle? Lecture 3: Evaluating Computer Architectures Announcements - Reminder: Homework 1 due Thursday 2/2 Last Time technology back ground Computer elements Circuits and timing Virtuous cycle of the past and

More information

Dalhousie University CSCI 2132 Software Development Winter 2015 Lab 7, March 11

Dalhousie University CSCI 2132 Software Development Winter 2015 Lab 7, March 11 Dalhousie University CSCI 2132 Software Development Winter 2015 Lab 7, March 11 In this lab, you will first learn how to use pointers to print memory addresses of variables. After that, you will learn

More information

Ayurvedic Principles of Siebel Performance

Ayurvedic Principles of Siebel Performance Oliver Seiffert, Raoul Mayr 15.11.2009 Ayurvedic Principles of Siebel Performance About Me My Session for You Session s Objective Application Architect, with 13+ years of experience in IT projects and

More information

Performance of STAR-System

Performance of STAR-System Performance of STAR-System STAR-System Application Note Stuart Mills Performance of STAR-System STAR-Dundee s new software stack, STAR-System, provides a high performance software stack for accessing STAR-Dundee

More information

CloudCmp:Comparing Cloud Providers. Raja Abhinay Moparthi

CloudCmp:Comparing Cloud Providers. Raja Abhinay Moparthi CloudCmp:Comparing Cloud Providers Raja Abhinay Moparthi 1 Outline Motivation Cloud Computing Service Models Charging schemes Cloud Common Services Goal CloudCom Working Challenges Designing Benchmark

More information

High-performance vnic framework for hypervisor-based NFV with userspace vswitch Yoshihiro Nakajima, Hitoshi Masutani, Hirokazu Takahashi NTT Labs.

High-performance vnic framework for hypervisor-based NFV with userspace vswitch Yoshihiro Nakajima, Hitoshi Masutani, Hirokazu Takahashi NTT Labs. High-performance vnic framework for hypervisor-based NFV with userspace vswitch Yoshihiro Nakajima, Hitoshi Masutani, Hirokazu Takahashi NTT Labs. 0 Outline Motivation and background Issues on current

More information

White paper: Developing agile project task and team management practices

White paper: Developing agile project task and team management practices White paper: Developing agile project task and team management practices By Vidas Vasiliauskas Product Manager of Eylean Board 2014 The case Every one of us seeks for perfection in daily routines and personal

More information

White Paper. Cloud Performance Testing

White Paper. Cloud Performance Testing White Paper Cloud Performance Testing Table of Contents Introduction and Background Information...2 Challenges & Limitations of On-Premise Model. 2 Cloud Scope and Service Models... 3 Why Cloud for Performance

More information

Online and Scalable Data Validation in Advanced Metering Infrastructures

Online and Scalable Data Validation in Advanced Metering Infrastructures Online and Scalable Data Validation in Advanced Metering Infrastructures Chalmers University of technology Agenda 1. Problem statement 2. Preliminaries Data Streaming 3. Streaming-based Data Validation

More information

Megastore: Providing Scalable, Highly Available Storage for Interactive Services

Megastore: Providing Scalable, Highly Available Storage for Interactive Services Megastore: Providing Scalable, Highly Available Storage for Interactive Services J. Baker, C. Bond, J.C. Corbett, JJ Furman, A. Khorlin, J. Larson, J-M Léon, Y. Li, A. Lloyd, V. Yushprakh Google Inc. Originally

More information

1 Introduction This document describes the service Performance monitoring for the GTS Virtual Hosting service.

1 Introduction This document describes the service Performance monitoring for the GTS Virtual Hosting service. 1 Introduction This document describes the service for the GTS Virtual Hosting service. 2 Description of Performance Monitoring System The Performance Monitoring System is operated on a BaseN solution

More information

System Architecture. CS143: Disks and Files. Magnetic disk vs SSD. Structure of a Platter CPU. Disk Controller...

System Architecture. CS143: Disks and Files. Magnetic disk vs SSD. Structure of a Platter CPU. Disk Controller... System Architecture CS143: Disks and Files CPU Word (1B 64B) ~ 10 GB/sec Main Memory System Bus Disk Controller... Block (512B 50KB) ~ 100 MB/sec Disk 1 2 Magnetic disk vs SSD Magnetic Disk Stores data

More information

AlphaTrust PRONTO - Hardware Requirements

AlphaTrust PRONTO - Hardware Requirements AlphaTrust PRONTO - Hardware Requirements 1 / 9 Table of contents Server System and Hardware Requirements... 3 System Requirements for PRONTO Enterprise Platform Software... 5 System Requirements for Web

More information

Overview of Network Measurement Tools

Overview of Network Measurement Tools Overview of Network Measurement Tools Jon M. Dugan Energy Sciences Network Lawrence Berkeley National Laboratory NANOG 43, Brooklyn, NY June 1, 2008 Networking for the Future of Science

More information

Changes only affecting customers using SWIFT codewords, Intermediary Institutions, or with other special requirements

Changes only affecting customers using SWIFT codewords, Intermediary Institutions, or with other special requirements Bankline File Import Guide 1. Introduction This document describes the changes effective April 2008 for the Bankline Internet Banking Import File Layout User Guide. In overview, the changes are as follows.

More information

How to write a design document

How to write a design document How to write a design document Øystein Dale oystedal@ifi.uio.no February 23, 2015 First off Writing a design document is something new for most of you. Before: Read mandatory assignment/exam description,

More information

Advanced Virtual DJ configuration Using ASIO4ALL and Timecoded vinyls

Advanced Virtual DJ configuration Using ASIO4ALL and Timecoded vinyls Advanced Virtual DJ configuration Using ASIO4ALL and Timecoded vinyls This document will explain how to configure Virtual DJ to use the TimeCoded Vinyls and an external mixtable. The goal is to play the

More information

Networking Virtualization Using FPGAs

Networking Virtualization Using FPGAs Networking Virtualization Using FPGAs Russell Tessier, Deepak Unnikrishnan, Dong Yin, and Lixin Gao Reconfigurable Computing Group Department of Electrical and Computer Engineering University of Massachusetts,

More information

Benchmarking Virtual Switches in OPNFV draft-vsperf-bmwg-vswitch-opnfv-01. Maryam Tahhan Al Morton

Benchmarking Virtual Switches in OPNFV draft-vsperf-bmwg-vswitch-opnfv-01. Maryam Tahhan Al Morton Benchmarking Virtual Switches in OPNFV draft-vsperf-bmwg-vswitch-opnfv-01 Maryam Tahhan Al Morton Outline VSPERF test specification updates VSPERF in practice Future work Summary VSPERF test specification

More information

Benchmarking Methodology for Virtualization Network Performance

Benchmarking Methodology for Virtualization Network Performance Benchmarking Methodology for Virtualization Network Performance draft-liu-bmwg-virtual-network-benchmark-00 Vic Liu Dapeng Liu Bob Mandeville Brooks Hickman Guang Zhang Speaker: Vic Liu China Mobile Tes$ng

More information

Testing Cloud Application System Resiliency by Wrecking the System

Testing Cloud Application System Resiliency by Wrecking the System Volume 3, No.5, May 2014 International Journal of Advances in Computer Science and Technology Tanvi Dharmarha, International Journal of Advances in Computer Science and Technology, 3(5), May 2014, 357-363

More information

MASTER DATA ACQUISITION USING eotd Dr Salomon de Jager PiLog

MASTER DATA ACQUISITION USING eotd Dr Salomon de Jager PiLog MASTER DATA ACQUISITION USING eotd Dr Salomon de Jager PiLog ECCMA 10 th Anniversary Conference 27 th to 29 th October 2009 Cataloging at Source - the last piece of the puzzle Master Data Management Quadrants

More information

C-GEP 100 Monitoring application user manual

C-GEP 100 Monitoring application user manual C-GEP 100 Monitoring application user manual 1 Introduction: C-GEP is a very versatile platform for network monitoring applications. The ever growing need for network bandwith like HD video streaming and

More information

Power efficiency and power management in HP ProLiant servers

Power efficiency and power management in HP ProLiant servers Power efficiency and power management in HP ProLiant servers Technology brief Introduction... 2 Built-in power efficiencies in ProLiant servers... 2 Optimizing internal cooling and fan power with Sea of

More information

Comparing Power Saving Techniques for Multi cores ARM Platforms

Comparing Power Saving Techniques for Multi cores ARM Platforms Comparing Power Saving Techniques for Multi cores ARM Platforms Content Why to use CPU hotplug? Tests environment CPU hotplug constraints What we have / What we want How to

More information

NTE2053 Integrated Circuit 8 Bit MPU Compatible A/D Converter

NTE2053 Integrated Circuit 8 Bit MPU Compatible A/D Converter NTE2053 Integrated Circuit 8 Bit MPU Compatible A/D Converter Description: The NTE2053 is a CMOS 8 bit successive approximation Analog to Digital converter in a 20 Lead DIP type package which uses a differential

More information

MAUI: Dynamically Splitting Apps Between the Smartphone and Cloud

MAUI: Dynamically Splitting Apps Between the Smartphone and Cloud MAUI: Dynamically Splitting Apps Between the Smartphone and Cloud Brad Karp UCL Computer Science CS M038 / GZ06 28 th February 2012 Limited Smartphone Battery Capacity iphone 4 battery: 1420 mah (@ 3.7

More information

How NOT to Do Scrum. Patterns and Anti-patterns. Revised July 2013. First presented at New York City Scrum User Group June 17, 2010

How NOT to Do Scrum. Patterns and Anti-patterns. Revised July 2013. First presented at New York City Scrum User Group June 17, 2010 How NOT to Do Scrum Patterns and Anti-patterns Revised July 2013 First presented at New York City Scrum User Group June 17, 2010 V 2.2 2010, 2013 Qualytic Consulting What this is about Patterns Practices

More information

Page 1 Addressing Performance Throughout the Life Cycle

Page 1 Addressing Performance Throughout the Life Cycle Page 1 Addressing Performance Throughout the Life Cycle Mike Koza - Subject Matter Expert Compuware Corporation Page 2 Agenda This session will address performance in the following life cycle areas: Requirements

More information

What s going on with iphone touch performance?

What s going on with iphone touch performance? What s going on with iphone touch performance? - A performance comparison between Apple iphone 5S and iphone 5C Apple released two new iphones to market few weeks ago, the new flag ship model 5S and the

More information

Power Management in the Linux Kernel

Power Management in the Linux Kernel Power Management in the Linux Kernel Tate Hornbeck, Peter Hokanson 7 April 2011 Intel Open Source Technology Center Venkatesh Pallipadi Senior Staff Software Engineer 2001 - Joined Intel Processor and

More information

means the charges applied by Ancar B Technologies Limited which recur annually;

means the charges applied by Ancar B Technologies Limited which recur annually; This Service Schedule is supplemental to the Master Service Agreement Net-L1-3. CONTENTS Schedule 1 - DEFINITIONS... 1 Schedule 2 - MANAGED INTERNET ACCESS SERVICE PRODUCT INFORMATION... 3 1 MANAGED INTERNET

More information

Know your Cluster Bottlenecks and Maximize Performance

Know your Cluster Bottlenecks and Maximize Performance Know your Cluster Bottlenecks and Maximize Performance Hands-on training March 2013 Agenda Overview Performance Factors General System Configuration - PCI Express (PCIe) Capabilities - Memory Configuration

More information

Informatica Master Data Management Multi Domain Hub API: Performance and Scalability Diagnostics Checklist

Informatica Master Data Management Multi Domain Hub API: Performance and Scalability Diagnostics Checklist Informatica Master Data Management Multi Domain Hub API: Performance and Scalability Diagnostics Checklist 2012 Informatica Corporation. No part of this document may be reproduced or transmitted in any

More information

MULTIPRON. E1, Gigabit Ethernet, RS232/485 Tester MULTIPRON

MULTIPRON. E1, Gigabit Ethernet, RS232/485 Tester MULTIPRON MULTIPRON E1, Gigabit Ethernet, RS232/485 Tester MULTIPRON 10/100/1000 Mbit/s Ethernet transmission data monitoring and analysis (two Gigabit Ethernet interfaces, 2x 100/1000Mbit/s SFP and 2x 10/100/1000Mbit/s

More information

IPSec Virtual Private Networks Conformance and Performance Testing Sample Test Plans

IPSec Virtual Private Networks Conformance and Performance Testing Sample Test Plans IPSec Virtual Private Networks Conformance and Performance Testing Sample Test Plans Contents 1. IPSec Conformance Test...3 2. Tunnel Scalability Test...5 3. Tunnel Setup Rate Test...7 4. Re-Key Tests...

More information

COMPARATIVE STUDY ON PERFORMANCE TEST METHODOLOGIES TRADITIONAL AND CLOUD

COMPARATIVE STUDY ON PERFORMANCE TEST METHODOLOGIES TRADITIONAL AND CLOUD COMPARATIVE STUDY ON PERFORMANCE TEST METHODOLOGIES TRADITIONAL AND CLOUD K.MANGAIYARKARASI 1 K.K.SURESHKUMAR 2 Dr.N.M.ELANGO 3 1 Research Scholar, Department of Computer Science (P.G), Kongu Arts and

More information

Adaptive Medium Access Control (MAC) for Heterogeneous Mobile Wireless Sensor Networks (WSNs).

Adaptive Medium Access Control (MAC) for Heterogeneous Mobile Wireless Sensor Networks (WSNs). 2008 Adaptive Medium Access Control (MAC) for Heterogeneous Mobile Wireless Sensor Networks (WSNs). Giorgio Corbellini 1 Challenges of the Ph.D. Study of urgency in sensed data Study of mobility in WSNs

More information

Alcatel OmniPCX Enterprise

Alcatel OmniPCX Enterprise Alcatel OmniPCX Enterprise VoIP board IP configuration Maintenance 1 OBJECTIVE: Check the IP configuration of the different VoIP boards VoIP board IP configuration Example with an INTIPA board cplstat

More information

project collects data from national events, both natural and manmade, to be stored and evaluated by

project collects data from national events, both natural and manmade, to be stored and evaluated by Joseph Sebastian CS 2994 Spring 2014 Undergraduate Research Final Paper GOALS The goal of my research was to assist the Integrated Digital Event Archive (IDEAL) team in transferring their Twitter data

More information

Scaling Database Performance in Azure

Scaling Database Performance in Azure Scaling Database Performance in Azure Results of Microsoft-funded Testing Q1 2015 2015 2014 ScaleArc. All Rights Reserved. 1 Test Goals and Background Info Test Goals and Setup Test goals Microsoft commissioned

More information

Understanding and Detec.ng Real- World Performance Bugs

Understanding and Detec.ng Real- World Performance Bugs Understanding and Detec.ng Real- World Performance Bugs Gouliang Jin, Linhai Song, Xiaoming Shi, Joel Scherpelz, and Shan Lu Presented by Cindy Rubio- González Feb 10 th, 2015 Mo.va.on Performance bugs

More information

IT Quality and Software Test

IT Quality and Software Test IT Quality and Software Test Lesson 9 Incident Management Quiz V1.0 Uwe Gühl Winter 2011/ 2012 1. Incident Management Incident Report What do you consider to be the most important information in an incident

More information

Fall 2014 to Summer 2016 Course Rotation Computer Information Systems Fall 2014 Courses Format

Fall 2014 to Summer 2016 Course Rotation Computer Information Systems Fall 2014 Courses Format Fall 2014 to Summer 2016 Course Rotation Computer Information Systems Fall 2014 Courses Online CS154 Technology: Database CS180 Structure & Logic CS220 Survey of Programming Languages CS242 Database Theory

More information

BUS312A/612A Financial Reporting I. Homework 10.6.2014 & 10.8.2014 Receivables Chapter 7

BUS312A/612A Financial Reporting I. Homework 10.6.2014 & 10.8.2014 Receivables Chapter 7 BUS312A/612A Financial Reporting I Homework 10.6.2014 & 10.8.2014 Receivables Chapter 7 Chapter 7- You should be able to: Identify elements of cash Identify the types of receivables Explain accounting

More information

25GE host/cable options

25GE host/cable options 25GE host/cable options Summary of thinking after talking to a number of people Mark Nowell & Gary Nicholl From dudek_111914_25ge_adhoc: 6 configs for AutoNeg to deal with. Historical Note: Autoneg is

More information

Host Power Management in VMware vsphere 5.5

Host Power Management in VMware vsphere 5.5 in VMware vsphere 5.5 Performance Study TECHNICAL WHITE PAPER Table of Contents Introduction...3 Power Management BIOS Settings...3 Host Power Management in ESXi 5.5... 5 Relationship between HPM and DPM...

More information

Medium Access Control with Dynamic Frame Length in Wireless Sensor Networks

Medium Access Control with Dynamic Frame Length in Wireless Sensor Networks Journal of Information Processing Systems, Vol.6, No.4, December 2010 DOI : 10.3745/JIPS.2010.6.4.501 Medium Access Control with Dynamic Frame Length in Wireless Sensor Networks Dae-Suk Yoo* and Seung

More information

APPLICATION NOTE GaGe CompuScope 14200-based Lightning Monitoring System

APPLICATION NOTE GaGe CompuScope 14200-based Lightning Monitoring System APPLICATION NOTE GaGe CompuScope 14200-based Lightning Monitoring System Challenge A customer needed to upgrade an older data acquisition unit for a real-time lightning monitoring system. Unlike many lightning

More information

Pinos. Wim Taymans. Principal Software Engineer October 8, 2015. Wim Taymans. Gstreamer Conference Dublin

Pinos. Wim Taymans. Principal Software Engineer October 8, 2015. Wim Taymans. Gstreamer Conference Dublin Pinos Principal Software Engineer October 8, 2015 1 Pinos what Daemon that manages access to multimedia streams Capture streams (from v4l2, pulseaudio, ) Upload streams 2 Pinos history GStreamer conference

More information

Change Request Process Overview

Change Request Process Overview Industry Best Practices Process Overview by Garth Wilcox This white paper outlines a process for requesting and managing changes to an application during the product development cycle. It also discusses

More information

Service Design Best Practices

Service Design Best Practices Service Design Best Practices James Hamilton 2009/2/26 Principals of Amazon Amazon Web Services e: James@amazon.com w: mvdirona.com/jrh/work b: perspectives.mvdirona.com Agenda Overview Recovery-Oriented

More information

Performance Management Framework

Performance Management Framework Purpose of the framework: To explain how we manage in Poole. It applies to all directly managed services of the Council. Introduction: Effective management at the council will: Ensure our goals are prioritised

More information

Routing Overlays and Virtualization. Nick Feamster CS 7260 March 7, 2007

Routing Overlays and Virtualization. Nick Feamster CS 7260 March 7, 2007 Routing Overlays and Virtualization Nick Feamster CS 7260 March 7, 2007 Today s Lecture Routing Overlays: Resilient Overlay Networks Motivation Basic Operation Problems: scaling, syncrhonization, etc.

More information

Scalable Internet/Scalable Storage. Seif Haridi KTH/SICS

Scalable Internet/Scalable Storage. Seif Haridi KTH/SICS Scalable Internet/Scalable Storage Seif Haridi KTH/SICS Interdisk: The Big Idea 2 Interdisk: The Big Idea I: 3 Interdisk: The Big Idea I: Internet is global data communication 4 Interdisk: The Big Idea

More information

Host Power Management in VMware vsphere 5

Host Power Management in VMware vsphere 5 in VMware vsphere 5 Performance Study TECHNICAL WHITE PAPER Table of Contents Introduction.... 3 Power Management BIOS Settings.... 3 Host Power Management in ESXi 5.... 4 HPM Power Policy Options in ESXi

More information

Conference on. Model-Based Validation of In-Vehicle Networks

Conference on. Model-Based Validation of In-Vehicle Networks Conference on University of Applied Sciences Prof. Dr.-Ing. Wolfhard Lawrenz (organisation) Salzdahlumer Str. 46/48 D-38302 Wolfenbüttel, Germany AUTOSAR Conformance Testing Characteristics and Challenges

More information

Assignment 2: Microsoft Project Toolset. Eric Palmer & Mahindra Bheodari. Kennesaw State University. IS 8100 Spring 2015

Assignment 2: Microsoft Project Toolset. Eric Palmer & Mahindra Bheodari. Kennesaw State University. IS 8100 Spring 2015 Assignment 2: Microsoft Project Toolset 1 Assignment 2: Microsoft Project Toolset Eric Palmer & Mahindra Bheodari Kennesaw State University IS 8100 Spring 2015 Assignment 2: Microsoft Project Toolset 2

More information

TESTER HARDWARE OVERVIEW. What s an ASIC Tester?

TESTER HARDWARE OVERVIEW. What s an ASIC Tester? TESTER HARDWARE OVERVIEW CS/ECE 6712 What s an ASIC Tester? Like a logic analyzer But with a pattern generator so that you can program in the sequence of signals to send to your chip With a comparison

More information

Bob Boothe. Education. Research Interests. Teaching Experience

Bob Boothe. Education. Research Interests. Teaching Experience Bob Boothe Computer Science Dept. University of Southern Maine 96 Falmouth St. P.O. Box 9300 Portland, ME 04103--9300 (207) 780-4789 email: boothe@usm.maine.edu 54 Cottage Park Rd. Portland, ME 04103 (207)

More information

Successful Scalability Principles - Part 1

Successful Scalability Principles - Part 1 Title Successful Scalability Principles - Part 1 Ronald Bradford http://ronaldbradford.com 2011.05 Necessary Principles System Architecture Data Availability Best Practices Being proactive OUTLINE 1 1

More information

Voltage Measurement with A PIC Microcontroller

Voltage Measurement with A PIC Microcontroller Voltage Measurement with A PIC Microcontroller Ryan Popa 03/30/2012 Design Team 3 Abstract The purpose of this application note is to explain how to measure a voltage using a PIC18F4520 microcontroller.

More information

Performance Testing. Why is important? An introduction. Why is important? Delivering Excellence in Software Engineering

Performance Testing. Why is important? An introduction. Why is important? Delivering Excellence in Software Engineering Delivering Excellence in Software Engineering Performance Testing An introduction. Why is important? Why is important? 2 1 https://www.youtube.com/watch?v=8y8vqjqbqdc 3 4 2 Introduction Why is important?

More information

DOE/OE Transmission Reliability Program. Data Validation & Conditioning

DOE/OE Transmission Reliability Program. Data Validation & Conditioning DOE/OE Transmission Reliability Program Data Validation & Conditioning Jianzhong Mo mo@electricpowergroup.com Kenneth Martin martin@electricpowergroup.com June 3-4, 2014 Washington, DC 2 Presentation Introduction

More information

How To Write A Paper On Csp And Object-Z

How To Write A Paper On Csp And Object-Z Renementandvericationofconcurrentsystemsspecied TechnischeUniversitatBerlin,FBInformatik,FGSoftwaretechnik, GraemeSmithandJohnDerricky inobject-zandcsp ycomputinglaboratory,universityofkent,canterbury,ct27nf,uk.

More information

Chapter 6: distributed systems

Chapter 6: distributed systems Chapter 6: distributed systems Strongly related to communication between processes is the issue of how processes in distributed systems synchronize. Synchronization is all about doing the right thing at

More information

How to Build a Massively Scalable Next-Generation Firewall

How to Build a Massively Scalable Next-Generation Firewall How to Build a Massively Scalable Next-Generation Firewall Seven measures of scalability, and how to use them to evaluate NGFWs Scalable is not just big or fast. When it comes to advanced technologies

More information

Liteon True Speed White Paper SPEED UP NETWORK STORAGE PERFORMANCE WITH LITEON TRUE SPEED TECHNOLOGY

Liteon True Speed White Paper SPEED UP NETWORK STORAGE PERFORMANCE WITH LITEON TRUE SPEED TECHNOLOGY SPEED UP NETWORK STORAGE PERFORMANCE WITH LITEON TRUE SPEED TECHNOLOGY 1 Contents Introduction... Migrating from Hard Disk Drive to Solid State Disk... It s all in the IOPS... Liteon True Speed... Reliable

More information

OpenSoC Fabric: On-Chip Network Generator

OpenSoC Fabric: On-Chip Network Generator OpenSoC Fabric: On-Chip Network Generator Using Chisel to Generate a Parameterizable On-Chip Interconnect Fabric Farzad Fatollahi-Fard, David Donofrio, George Michelogiannakis, John Shalf MODSIM 2014 Presentation

More information

AE EHR Database Servers

AE EHR Database Servers AE EHR Database Servers Systems Maintenance Embrace the new world of healthcare Agenda AE EHR Databases: Dynamic data Static data Third Party Databases Server Specifications SQL Services Connectivity Tools/Jobs

More information

ACCOUNTING CS Report Options Comparison with Write-Up CS

ACCOUNTING CS Report Options Comparison with Write-Up CS ACCOUNTING CS Report Options Comparison with Write-Up CS and Trial Balance CS General information... 1 Print options... 2 Date, filtering, and sorting print options... 2 Regions and sections to include...

More information

FIRE AND BURGLAR ALARM SYSTEM BASED ON Central Panel «KODOS A-20» User Guide

FIRE AND BURGLAR ALARM SYSTEM BASED ON Central Panel «KODOS A-20» User Guide FIRE AND BURGLAR ALARM SYSTEM BASED ON Central Panel «KODOS A-20» CONTENTS PURPOSE... 2 DEVICE APPEARANCE... 3 HOW TO START OPERATING THE DEVICE... 4 USER RIGHTS ON MANAGING THE SYSTEM... 6 HOW TO VIEW

More information

Determining Overhead, Variance & Isola>on Metrics in Virtualiza>on for IaaS Cloud

Determining Overhead, Variance & Isola>on Metrics in Virtualiza>on for IaaS Cloud Determining Overhead, Variance & Isola>on Metrics in Virtualiza>on for IaaS Cloud Bukhary Ikhwan Ismail Devendran Jagadisan Mohammad Fairus Khalid MIMOS BERHAD Contents 1. Introduc>on 2. Tes>ng Methodologies

More information

Thread level parallelism

Thread level parallelism Thread level parallelism ILP is used in straight line code or loops Cache miss (off-chip cache and main memory) is unlikely to be hidden using ILP. Thread level parallelism is used instead. Thread: process

More information

Performance Testing for Managers. Presented by Stuart Moncrieff at SIGiST Melbourne on June 15 th, 2011

Performance Testing for Managers. Presented by Stuart Moncrieff at SIGiST Melbourne on June 15 th, 2011 Performance Testing for Managers Presented by Stuart Moncrieff at SIGiST Melbourne on June 15 th, 2011 What will be covered? Performance Testing as it applies to: Large multi-user enterprise IT applications

More information

Experiences with Using IBM zec12 Flash Memory

Experiences with Using IBM zec12 Flash Memory Experiences with Using IBM zec12 Flash Memory Session 14119 August 13, 2013 Mary Astley ATS - IBM Corporation 2013 IBM Corporation Trademarks The following are trademarks of the International Business

More information

October2013 VB-Audio Software V.Burel Configuring System Settings VB-CABLE revision 0 VB-AUDIO CABLE

October2013 VB-Audio Software V.Burel Configuring System Settings VB-CABLE revision 0 VB-AUDIO CABLE VB-AUDIO CABLE Virtual Audio Device working as Virtual Audio Cable Configuring VB-CABLE System Settings How to configure VB-CABLE Latency and Internal Sample rate. How to configure HiFi-CABLE Latency HiFi-CABLE

More information

CS:APP Chapter 4 Computer Architecture. Wrap-Up. William J. Taffe Plymouth State University. using the slides of

CS:APP Chapter 4 Computer Architecture. Wrap-Up. William J. Taffe Plymouth State University. using the slides of CS:APP Chapter 4 Computer Architecture Wrap-Up William J. Taffe Plymouth State University using the slides of Randal E. Bryant Carnegie Mellon University Overview Wrap-Up of PIPE Design Performance analysis

More information

IAT-1710E Integrated Access Tester

IAT-1710E Integrated Access Tester IAT-1710E Integrated Access Tester Features A number of ways to verify channel bandwidth, support for symmetric and asymmetric RFC2544 test Original high-speed PING test function, can be arbitrary set

More information

A/R Journal Entries GAAP. Add Invoice Line. Cancel Line from Invoice Maintenance. Cancel Balance via Write-Off Invoice Balances Routine

A/R Journal Entries GAAP. Add Invoice Line. Cancel Line from Invoice Maintenance. Cancel Balance via Write-Off Invoice Balances Routine CHAPTER 6 A/R Journal Entries This chapter will review the automated journal entries made by the module. The entries are separated into a GAAP and Non-GAAP section. GAAP Add Invoice Line An accrual entry

More information

The new frontier of the DATA acquisition using 1 and 10 Gb/s Ethernet links. Filippo Costa on behalf of the ALICE DAQ group

The new frontier of the DATA acquisition using 1 and 10 Gb/s Ethernet links. Filippo Costa on behalf of the ALICE DAQ group The new frontier of the DATA acquisition using 1 and 10 Gb/s Ethernet links Filippo Costa on behalf of the ALICE DAQ group DATE software 2 DATE (ALICE Data Acquisition and Test Environment) ALICE is a

More information

KNOWLEDGE GRID An Architecture for Distributed Knowledge Discovery

KNOWLEDGE GRID An Architecture for Distributed Knowledge Discovery KNOWLEDGE GRID An Architecture for Distributed Knowledge Discovery Mario Cannataro 1 and Domenico Talia 2 1 ICAR-CNR 2 DEIS Via P. Bucci, Cubo 41-C University of Calabria 87036 Rende (CS) Via P. Bucci,

More information

Virtual machines and operating systems

Virtual machines and operating systems V i r t u a l m a c h i n e s a n d o p e r a t i n g s y s t e m s Virtual machines and operating systems Krzysztof Lichota lichota@mimuw.edu.pl A g e n d a Virtual machines and operating systems interactions

More information

Software Engineering. How does software fail? Terminology CS / COE 1530

Software Engineering. How does software fail? Terminology CS / COE 1530 Software Engineering CS / COE 1530 Testing How does software fail? Wrong requirement: not what the customer wants Missing requirement Requirement impossible to implement Faulty design Faulty code Improperly

More information

Imam Mohammad Ibn Saud Islamic University College of Computer and Information Sciences Department of Computer Sciences

Imam Mohammad Ibn Saud Islamic University College of Computer and Information Sciences Department of Computer Sciences 1121-1122 In the Name Of Allah, the Most Beneficent, the Most Merciful Imam Mohammad Ibn Saud Islamic University Department of Computer Sciences Program Description of Master of Science in Computer Sciences

More information

CS 6290 I/O and Storage. Milos Prvulovic

CS 6290 I/O and Storage. Milos Prvulovic CS 6290 I/O and Storage Milos Prvulovic Storage Systems I/O performance (bandwidth, latency) Bandwidth improving, but not as fast as CPU Latency improving very slowly Consequently, by Amdahl s Law: fraction

More information

AMD GPU Architecture. OpenCL Tutorial, PPAM 2009. Dominik Behr September 13th, 2009

AMD GPU Architecture. OpenCL Tutorial, PPAM 2009. Dominik Behr September 13th, 2009 AMD GPU Architecture OpenCL Tutorial, PPAM 2009 Dominik Behr September 13th, 2009 Overview AMD GPU architecture How OpenCL maps on GPU and CPU How to optimize for AMD GPUs and CPUs in OpenCL 2 AMD GPU

More information

Latency in High Performance Trading Systems Feb 2010

Latency in High Performance Trading Systems Feb 2010 Latency in High Performance Trading Systems Feb 2010 Stephen Gibbs Automated Trading Group Overview Review the architecture of a typical automated trading system Review the major sources of latency, many

More information

CS521 CSE IITG 11/23/2012

CS521 CSE IITG 11/23/2012 CS521 CSE TG 11/23/2012 A Sahu 1 Degree of overlap Serial, Overlapped, d, Super pipelined/superscalar Depth Shallow, Deep Structure Linear, Non linear Scheduling of operations Static, Dynamic A Sahu slide

More information

Lead Free Legislation: The Affect on the Plumbing Industry

Lead Free Legislation: The Affect on the Plumbing Industry Lead Free Legislation: The Affect on the Plumbing Industry Safe Drinking Water Act (SDWA) Effective December 16, 1974 SDWA is the principal federal law in the U.S. intended to ensure safe drinking water

More information

ACTIVE SEATING FOR PEOPLE WITH A KYPHOTIC SPINE. - backrest cushion for the kyphotic spine

ACTIVE SEATING FOR PEOPLE WITH A KYPHOTIC SPINE. - backrest cushion for the kyphotic spine ACTIVE SEATING FOR PEOPLE WITH A KYPHOTIC SPINE - backrest cushion for the kyphotic spine Netti Kyphotic is designed for users who require optimum stabilization of their spinal curvature. The upholstery

More information

IP Address Classes (Some are Obsolete) 15-441 Computer Networking. Important Concepts. Subnetting 15-441 15-641. Lecture 8 IP Addressing & Packets

IP Address Classes (Some are Obsolete) 15-441 Computer Networking. Important Concepts. Subnetting 15-441 15-641. Lecture 8 IP Addressing & Packets Address Classes (Some are Obsolete) 15-441 15-441 Computer Networking 15-641 Class A 0 Network ID Network ID 8 16 Host ID Host ID 24 32 Lecture 8 Addressing & Packets Peter Steenkiste Fall 2013 www.cs.cmu.edu/~prs/15-441-f13

More information

RC2000 Web Server User s Manual RCI P/N: FP-SER-ETH-SERVR1

RC2000 Web Server User s Manual RCI P/N: FP-SER-ETH-SERVR1 RC2000 Web Server User s Manual RCI P/N: FP-SER-ETH-SERVR1 v 1.1 Content Subject to Change 13 September 2012 9501 Dice Lane Lenexa, Kansas USA TEL: (913) 422-0210, FAX: (913) 422-0211 Website: WWW.ResearchConcepts.COM

More information