Performance Evaluation of Complex Systems: Techniques and Tools

Thefastevolutionandtheincreasedpervasivenessofcomputersandcom- nicationnetworkshaveledtothedevelopmentofalargevarietyofcomplex applicationsandserviceswhichhavebecomeanintegralpartofourdailylives. Modernsocietywidelyreliesoninformationtechnologies. Hence,theQuality ofService,thatis,thee?ciency,availability,reliability,andsecurityofthese technologies,isanessentialrequirementfortheproperfunctioningofmodern society. Inthisscenario,performanceevaluationplaysacentralrole. Performance evaluationhastoassessandpredicttheperformanceofhardwareandsoftware systems,andtoidentifyandpreventtheircurrentandfutureperformancebo- lenecks. Inthepastthirtyyears,manyperformanceevaluationtechniquesandtools havebeendevelopedandsuccessfullyappliedinstudiesdealingwiththec- ?gurationandcapacityplanningofexistingsystemsandwiththedesignand developmentofnewsystems. Recently,performanceevaluationtechniqueshave evolvedtocopewiththeincreasedcomplexityofthecurrentsystemsandtheir workloads. Manyoftheclassicaltechniqueshavebeenrevisitedinlightofthe recenttechnologicaladvances,andnoveltechniques,methods,andtoolshave beendeveloped. Thisbookisorganizedaroundasetofsurveypaperswhichprovideac- prehensiveoverviewofthetheories,techniques,andtoolsforperformanceand reliabilityevaluationofcurrentandnewemergingtechnologies. Thepapers,by leadinginternationalexpertsinthe?eldofperformanceevaluation,arebasedon thetutorialspresentedattheIFIPWG7. 3InternationalSymposiumonCom- terModeling,Measurement,andEvaluation(Performance2002)heldinRome onSeptember23–27,2002. Thepapersaddressthestateoftheartofthetheoreticalandmethodological advancesintheareaofperformanceandreliabilityevaluationaswellasnew perspectivesinthemajorapplicationdomains. Abroadspectrumoftopicsis coveredinthisbook. Modelingandveri?cationformalisms,solutionmethods, workloadcharacterization,andbenchmarkingareaddressedfromametho- logicalpointofview. Applicationsofperformanceandreliabilitytechniquesto variousdomains,suchas,hardwareandsoftwarearchitectures,wiredand- relessnetworks,Gridenvironments,Webservices,real–timevoiceandvideo applications,arealsoexamined. Thisbookisintendedtoserveasareferenceforstudents,scientists,and- gineersworkingintheareasofperformanceandreliabilityevaluation,hardware andsoftwaredesign,andcapacityplanning. VI Preface Finally,aseditorsofthebook,wewouldliketothankallauthorsfortheir valuablecontributionsandtheire?ortandcooperationinthepreparationof theirmanuscripts. July2002 MariaCarlaCalzarossa SalvatoreTucci TableofContents G-Networks:MultipleClassesofPositiveCustomers,Signals,and ProductFormResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 ErolGelenbe SpectralExpansionSolutionsforMarkov-ModulatedQueues . . . . . . . . . . . . 17 IsiMitrani M/G/1-TypeMarkovProcesses:ATutorial . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 AlmaRiska,EvgeniaSmirni AnAlgorithmicApproachtoStochasticBounds . . . . . . . . . . . . . . . . . . . . . . . 64 J. M. Fourneau,N. Pekergin DynamicSchedulingviaPolymatroidOptimization. . . . . . . . . . . . . . . . . . . . . 89 DavidD. Yao WorkloadModelingforPerformanceEvaluation. . . . . . . . . . . . . . . . . . . . . . . . 114 DrorG. Feitelson CapacityPlanningforWebServices(TechniquesandMethodology) . . . . . . 142 VirgilioA. F. Almeida End-to-EndPerformanceofWebServices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 PaoloCremonesi,GiuseppeSerazzi Benchmarking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 ReinholdWeicker BenchmarkingModelsandToolsforDistributedWeb-ServerSystems. . . . . 208 MauroAndreolini,ValeriaCardellini,MicheleColajanni StochasticProcessAlgebra:FromanAlgebraicFormalismtoan ArchitecturalDescriptionLanguage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 MarcoBernardo,LorenzoDonatiello,PaoloCiancarini AutomatedPerformanceandDependabilityEvaluationUsingModel Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 ChristelBaier,BoudewijnHaverkort,HolgerHermanns, Joost-PieterKatoen Measurement-BasedAnalysisofSystemDependabilityUsingFault InjectionandFieldFailureData . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290 RavishankarK. Iyer,ZbigniewKalbarczyk VIII TableofContents SoftwareReliabilityandRejuvenation:ModelingandAnalysis. . . . . . . . . . . 318 KishorS. Trivedi,KalyanaramanVaidyanathan PerformanceValidationofMobileSoftwareArchitectures . . . . . . . . . . . . . . . 346 VincenzoGrassi,VittorioCortellessa,Ra?aelaMirandola PerformanceIssuesofMultimediaApplications . . . . . . . . . . . . . . . . . . . . . . . . 374 EdmundodeSouzaeSilva,RosaM. M. Le˜ao,BerthierRibeiro-Neto, S´ergioCampos MarkovianModelingofRealDataTra?c:HeuristicPhaseTypeand MAPFittingofHeavyTailedandFractalLikeSamples. . . . . . . . . . . . . . . . . 405 Andr´asHorv´ath,Mikl´osTelek OptimizationofBandwidthandEnergyConsumptioninWireless LocalAreaNetworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435 MarcoConti,EnricoGregori ServiceCentricComputing–NextGenerationInternetComputing. . . . . . . 463 JerryRolia,RichFriedrich,ChandrakantPatel EuropeanDataGridProject:ExperiencesofDeployingaLargeScale TestbedforE-scienceApplications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 FabrizioGagliardi,BobJones,MarioReale,StephenBurke AuthorIndex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 G-Networks: Multiple Classes of Positive Customers, Signals, and Product Form Results Erol Gelenbe SchoolofElectricalEngineeringandComputerScience UniversityofCentralFlorida Orlando,FL32816 erol@cs. ucf. edu Abstract. ThepurposeofthistutorialpresentationistointroduceG- Networks,orGelenbeNetworks,whichareproductformqueueingn- works which include normal or positive customers, as well as negative customers which destroy other customers, and triggers which displace othercustomersfromonequeuetoanother. Wederivethebalanceeq- tionsforthesemodelsinthecontextofmultiplecustomerclasses,show the product form results, and exhibit the tra?c equations which – in thiscase,contrarytoBCMPandJacksonnetworks-arenon-linear. This leadstointerestingissuesofexistenceanduniquenessofthesteady-state solution. GelenbeNetworkcanbeusedtomodellargescalecomputers- temsandnetworksinwhichsignalingfunctionsrepresentedbynegative customersandtriggersareusedtoachieve?owandcongestioncontrol. 1 Introduction In this survey and tutorial, we discuss a class of queueing networks, originally inspired by our work on neural networks, in which customers are either “signals” or positive customers.