《分布式系統(tǒng)》研究生教學(xué)課件

DistributedSystemsComputer&InformationCollege,HohaiUniversitySept.2013CourseIntroductionQuestions?PleasecompletesurveyquestionsWhataredistributedsystems?Examples?MultiplehostsAnetworkcloudHostscooperatetoprovideaunifiedserviceWhydistributedsystems?forease-of-useHandlegeographicseparationProvideusers(orapplications)withlocationtransparency:Web:accessinformationwithafew“clicks”Networkfilesystem:accessfilesonremoteserversasiftheyareonalocaldisk,sharefilesamongmultiplecomputersWhydistributedsystems?foravailabilityBuildareliablesystemoutofunreliablepartsHardwarecanfail:poweroutage,diskfailures,memorycorruption,networkswitchfailures…Softwarecanfail:bugs,mis-configuration,upgrade…Toachieve0.999999availability,replicatedata/computationonmanyhostswithautomaticfailoverWhydistributedsystems?

forscalablecapacityAggregateresourcesofmanycomputersCPU:Dryad,MapReduce,Gridcomputing,CloudComputingBandwidth:AkamaiCDN,BitTorrentDisk:Frangipani,Googlefilesystem,DataCenterChallengesSystemdesignWhatistherightinterfaceorabstraction?Howtopartitionfunctionsforscalability?ConsistencyHowtosharedataconsistentlyamongmultiplereaders/writers?FaultToleranceHowtokeepsystemavailabledespitenodeornetworkfailures?Challenges(continued)SecurityHowtoauthenticateclientsorservers?Howtodefendagainstorauditmisbehavingservers?ImplementationHowtomaximizeIOparallelism?Howtoreduceloadonthebottleneckresource?AwordofwarningEasytomakedistributedsystemsthatarelessreliableandworseperformancethancentralizedsystems! PerformancecanbesubtleGoal:sustainedperformanceunderhighloadToy“distributedsystem”:

2employeesrunStarbucksEmployee1:takeordersfromcustomers,callsouttoemployee2Employee2:Writedownorders(5secondsperorder)Makedrinks(10secondsperorder)Whatisstarbuck’sthroughputunderincreasingload?Starbucks’throughputWhatistheidealcurve?Whatdesignachievesit?Ordersperminute(offeredload)4812drinksperminute(tput)24ReliabilitycanbesubtletooAdistributedsystemisasysteminwhichIcan’tdomyworkbecausesomecomputerthatI’veneverevenheardofhasfailed.”--LeslieLamportTopicsinthiscourseDistributedsystemsarchitecturesCommunication–RPC,RMI,MessageQueue…Processes–client,serversandmigratingcodeNaming–namingandfindingthingsSynchronization–gettingeverybodyinpaceConsistencyandreplication–scalability,replicationandconsistencyFaulttolerance–survivingfailuresSecurity–ensuringprivacyCommonparadigms–SOA,P2P,CloudComputingWebInfrastructureThisclasswillteachyou…PresentaconceptualmodelofdistributedsystemsDescribekeycomponentsofadistributedsystemandevaluatethetradeoffsofalternativearchitecturalmodelsSuggestalgorithmsuitableforapplicationindistributedsystemsBuildprototypeimplementationsofdistributedsystemsDemonstrateanunderstandingofthechallengesfacedbyfuturedistributedsystemsCoursereadingsDistributedSystems:PrinciplesandParadigms,byAndrewS.Tanenbaum,MaartenvenSteen,Prentice-Hall,2007.DistributedSystems:ConceptsandDesign,byGeorgeCoulouris,JeanDollimore,TimKindberg,AddisonWesley,2005.ReliableDistributedSystems:Technologies,WebServices,andApplications,byKennethP.Birman,SpringerVerlag,2005.分布式系統(tǒng)原理與范型，辛春生，陳宗斌等譯，2008，清華大學(xué)出版社DistributedSystems:PrinciplesandParadigmsPrincipleadescriptivecomprehensiveandfundamentallaw,doctrine,orassumption;具有普遍意義的最基本的規(guī)律?？茖W(xué)的原理，由實(shí)踐確定其正確性，可作為其他規(guī)律的基礎(chǔ)。也指具有普遍意義的道理。ParadigmtheOxfordEnglishDictionarydefinesparadigmas"apatternormodel,anexemplar.“Howisanexperimenttobeconducted,andwhatequipmentisavailabletoconducttheexperiment.howdistributedapplicationsshouldbedeveloped每一個(gè)科學(xué)發(fā)展階段都有特殊的內(nèi)在結(jié)構(gòu)，而體現(xiàn)這種結(jié)構(gòu)的模型即“范式”。OrganizationofthebookPrinciplesofdistributedsystemsarediscussedinchapters2-902Architectures,03Processes,04Communication05Naming,06Synchronization,07ConsistencyandReplication08FaultTolerance,09SecurityWhereoverallapproachestohowdistributedapplicationsshouldbedeveloped(theparadigms)arediscussedinchapter10-1310DistributedObject-BasedSystems,11DistributedFileSystems,12DistributedWeb-BasedSystems13DistributedCoordination-BasedSystemsReferences

http://www.ece.ubc.ca/~matei/EECE411/

/~chiran/cs171/DistributedComputing,Peer-to-PeerandGRIDSCS244B,CS244C@StanfordFall2007:AdvancedandDistributedOperatingSystems@CMUDistributedComputerSystemsEngineering@MITcs425@UIUC

/~kig/CS333_SP97/References

GoogleCodeforEducatorsandRelatedCoursesClusterComputingandMapReduceMiniLectureSeriesIntroductiontoProblemSolvingonLargeScaleClustersUniv.ofWashington,CSE490h:Problem-solvingonlarge-scaleclusters:theoryandapplicationsUniv.ofMaryland’sJimmyLin:Web-ScaleInformationProcessingApplicationsMapReduceinaWeek/edu/parallel/index.html/edu/content/parallel.htmlCourseOrganizationCourseisorganizedasaseriesofLectures–asetoflecturesonthecorematerialReadings–additionalreadingsfrompapersandbookPresentation–paperdiscussionExam–finalreportortake-classfinalexamClassparticipationHowareyouevaluated?Classparticipation10%PaperorPresentation30%Exam60%Question?IntroductionofDistributedSystemsOutline1.0Motivation1.1DefinitionofADistributedSystem1.2GoalsMakingResourcesAccessibleDistributionTransparencyOpennessScalabilityPitfalls1.3TypesofDistributedSystemsDistributedComputingSystemsDistributedInformationSystemsDistributedPervasiveSystemsMotivationResourcesharing–bothphysicalresourcesandinformationComputationspeedup–tosolvelargeproblems,wewillneedmanycooperatingmachinesReliability-machinesfailfrequentlyCommunication–peoplecollaboratingfromremotesitesManyapplicationsarebytheirnaturedistributed(ATMs,airlineticketreservation,etc)TwoMainStimuliTechnologicalchangeUserneedsTechnologyadvancesNetworkingProcessorsMemoryStorageProtocolNetworkingJune1976:RobertMetcalfepresentstheconceptofEthernetattheNationalComputerConference1980:Ethernetintroducedasdefactostandard(DEC,Intel,Xerox)1985:thickEthernet:10Mbps,Bus-based1991:10BaseT-twistedpair:10Mbps1995:100MbpsEthernet1998:GigabitEthernet1999:802.11bstandard2001:10Gbpsintroduced2005:100Gbps(overopticallink)NetworkConnectivityThen:

largecompaniesanduniversitiesonInternetgatewaysbetweenothernetworksdial-upbulletinboards1985:1,961hostsontheInternetintheworldNow:OneInternet(mostly)2011:600millionhostsontheInternetinChina,2billionintheworldwidespreadconnectivity

High-speedWANconnectivity:1–>1GbpsSwitchedLANswirelessnetworkingcomputingpowercomputersgotsmallercheaperpowerefficientFastermicroprocessorsbecametechnologyleadersMemorymemoryhierarchiescacheshidelatencyofmainmemoryaccess,increaseaccessbandwidthmemorygetsdenser,processorsgetfasterlargercacheson-chipcache:1984:127bytes,today:multilevelcaches:firstintroduced~1986,today:cachingtechniquesreduceorhidemisslatenciescache-awareprogrammers/compliers/computersStoragecostreducedMainMemoryyear$/MBtypical1977$32,00016K1987$250640K-2MB1997$264MB-256MB2007$0.06512MB-2GB+2013$0.014GB-8GB+9,000xcheaper

4,000xmorecapacityStorage:disk131,000xcheaperin20years

30,000xmorecapacityRecordingdensityincreasedover60,000,000timesover50years1977:

310KBfloppydrive–$14801987:40MBdrivefor–$6792008:750GBdrivefor–$99,$0.13/GB2013：2TBdrivefor-$99,$0.05/GBProtocolsFasterCPUmoretimeforprotocolprocessingECC,checksums,parsing(e.g.XML)Image,audiocompressionfeasibleFasternetwork

biggerandbloatedprotocols(e.g.,SOAP/XML,H.232)transfermoredata(e.g.,music,movies,streamingdata)MorestoragestorerichmediaMediadeliveryandstorageAudioMPEG-3telephonequality:8kbpsMPEG-3FMquality:56-64kbps36hours/GBTelephoneaudio:64kbpsMPEG-3compressednear-CDaudio:96kbpsMPEG-3CDqualityaudio:112kbps20hours/GBCDqualityaudio:1.4MbpsHDTVaudio:3MbpsVideoMPEG-1compressedNTSCvideo:1.5Mbps1.5hours/GBJPEGcompressedNTSCvideo:3-7MbpsHDTVvideo:22-40Mbps4.5minutes/GBDigitalmoviesCompressed:45-65GB/moviesDecompressed:1.6TBStreamat1.5Gb/secDevelopmentofComputerTechnology1950s:serialprocessors1960s:batchprocessing1970s:time-sharing1980s:personalcomputing1990s:parallel,network,anddistributedprocessing2000s:wirelessnetworksandmobilecomputing2010s:cloudcomputingandsocialcomputingPeoplearedistributedOutline1.0Motivation1.1DefinitionofADistributedSystem

1.2GoalsMakingResourcesAccessibleDistributionTransparencyOpennessScalabilityPitfalls1.3TypesofDistributedSystemsDistributedComputingSystemsDistributedInformationSystemsDistributedPervasiveSystemsDistributedSystem:Definition(1)VerybroaddefinitionAcollectionofindependentcomputersthatappearstoitsuserasasinglecoherentsystem.Distributedsystemsare"seamless":theinterfacesamongfunctionalunitsonthenetworkareforthemostpartinvisibletotheuser.Twoaspects(1)independentcomputers(2)singlesystem=>middleware.DistributedSystem:Definition(2)DifferencesbetweenthevariouscomputersandthewaysinwhichtheycommunicatearemostlyhiddenfromusersUsersandapplicationscaninteractwithadistributedsysteminaconsistentanduniformway,regardlessofwhereandwheninteractiontakesplace.Adistributedsystemorganizedasmiddleware.Themiddlewarelayerextendsovermultiplemachines,andofferseachapplicationthesameinterface.GoalsofDistributedSystemsMakingresourcesavailableDistributiontransparencyOpennessScalabilityMakeResourcesAccessibleAccessresourcesandsharetheminacontrolledandefficientway.Printers,computers,storagefacilities,data,files,Webpages,andnetworks,…Connectingusersandresourcesalsomakesiteasiertocollaborateandexchangeinformation.Internetforexchangingfiles,mail,documents,audio,andvideoSecurityisbecomingincreasinglyimportantLittleprotectionagainsteavesdroppingorintrusiononcommunicationTrackingcommunicationtobuildupapreferenceprofileofaspecificuserDistributionTransparencyTransparency:hidethefactthatitsprocessesandresourcesarephysicallydistributedacrossmultiplecomputers.Access–What’sdatarepresentation?Connectingmachineswithdifferentarchitectureandfile-nameconventionsLocation–Where’stheresourcelocated?NamingiskeyMigration–Havetheresourcemoved?Replication–Istheresourcebeingmove?Concurrency–Isanybodyelseaccessingtheresourcenow?Failure–Hasitbeenworkingallalong?DistributionTransparencyNote:Distributiontransparencymaybesetasagoal,butachievingitisadifferentstory.DistributedSystem:DefinitionDuetoLesliLamportAdistributedsystemis“Youknowyouhaveonewhenthecrashofacomputeryou’veneverheardofstopsyoufromgettinganyworkdone.”Thisdescriptionputsthefingeronanotherimportantissueofdistributedsystemsdesign:dealingwithfailures.LesliLamportLamportisbestknownforhisseminalworkindistributedsystems

andastheinitialdeveloperofthedocumentpreparationsystemLaTeX.Lamport’sresearchcontributionshavelaidthefoundationsofthetheoryofdistributedsystems.Amonghismostnotablepapersare“Time,Clocks,andtheOrderingofEventsinaDistributedSystem”,whichreceivedthePODCInfluentialPaperAwardin2000“TheByzantineGeneralsProblem”“DistributedSnapshots:DeterminingGlobalStatesofaDistributedSystem”and“ThePart-TimeParliament”.Thesepapersrelatetosuchconceptsaslogicalclocks

(andthehappened-beforerelationship)andByzantinefailures.Theyareamongthemostcitedpapersinthefieldofcomputerscienceanddescribealgorithmstosolvemanyfundamentalproblemsindistributedsystems,including:thePaxosalgorithm

forconsensus,thebakeryalgorithmformutualexclusion

ofmultiplethreadsinacomputersystemthatrequirethesameresourcesatthesametimeandthesnapshotalgorithm

forthedeterminationofconsistentglobalstates.DegreeofTransparencyObservation:Aimingatfulldistributiontransparencymaybetoomuch:Usersmaybelocatedindifferentcontinents;distributionisapparentandnotsomethingyouwanttohideCompletelyhidingfailuresofnetworksandnodesis(theoreticallyandpractically)impossibleYoucannotdistinguishaslowcomputerfromafailingoneYoucanneverbesurethataserveractuallyperformedanoperationbeforeacrashFulltransparencywillcostperformance,exposingdistributionofthesystemKeepingWebcachesexactly

up-to-datewiththemastercopyImmediatelyflushingwriteoperationstodiskforfaulttoleranceDegreeofTransparencyDowereally

wanttransparency?Impossible–remotecontrollingaspaceshipAbadidea–creatingfalseexpectationsAgainstapplication’sgoals–pervasivecomputingandlocationawarenessScaleinDistributedSystemsObservation:Manydevelopersofmoderndistributedsystemeasilyusetheadjective“scalable”withoutmakingclearwhy

theirsystemactuallyscales.Scalability:Atleastthreecomponents:Numberofusersand/orprocesses(sizescalability)Maximumdistancebetweennodes(geographicalscalability)Numberofadministrativedomains(administrativescalability)ScalabilityProblems@sizeDecentralizedalgorithms:Nomachinehascompleteinformationaboutthesystemstate.Machinesmakedecisionsbasedonlyonlocalinformation.FailureofonemachinedoesnotruinthealgorithmThereisnoimplicitassumptionthataglobalclockexistsScalabilityProblems@geographySynchronouscommunicationApartyrequestingservice,generallyreferredtoasaclient,blocksuntilareplyissentback.WANsisunreliableandPoint-to-pointLANsprovidereliablecommunicationfacilitiesbasedonbroadcasting.Geographicalscalabilityisstronglyrelatedtotheproblemsofcentralizedsolutionsthathindersizescalability.Inaddition,centralizedcomponentsnowleadtoawasteofnetworkresources.ScalabilityProblems@administrationItisadifficultandinmanycasesopenquestionConflictingpoliceswithrespecttoresourceusage(andpayment),management,andsecurity.E.g.,Residewithinasingledomaincanoftenbetrustedbyusersthatoperatewithinthatsamedomain.DownloadingprogramssuchasappletsinWebbrowsers.TechniquesforScalingHidecommunicationlatencies:

Avoidwaitingforresponses;dosomethingelse:MakeuseofasynchronouscommunicationHaveseparatehandlerforincomingresponseProblem:noteveryapplicationfitsthismodelMovecomputationstoclients(Javaapplets)Distribution:

Partitiondataandcomputationsacrossmultiplemachines:Decentralizednamingservices(DNS)Decentralizedinformationsystems(WWW)Replication/caching:

Makecopiesofdataavailableatdifferentmachines:ReplicatedfileserversanddatabasesMirroredWebsitesWebcaches(inbrowsersandproxies)Filecaching(atserverandclient)ScalingTechniquesExample(1)Technique:OffloadworktoclientsScalingTechniquesExample(2)Technique:Dividetheproblemspace.

example:thewayDNSdividesthenamespaceintozones.Scaling–TheProblemObservation:Applyingscalingtechniquesiseasy,exceptforonething:Havingmultiplecopies(cachedorreplicated),leadstoinconsistencies:modifyingonecopymakesthatcopydifferentfromtherest.Alwayskeepingcopiesconsistentandinageneralwayrequiresglobalsynchronization

oneachmodification.Globalsynchronizationprecludeslarge-scalesolutions.Observation:Ifwecantolerateinconsistencies,wemayreducetheneedforglobalsynchronization.Observation:Toleratinginconsistenciesisapplicationdependent.OpennessGoal:Opendistributedsystem--abletointeractwithservicesfromotheropensystems,irrespectiveoftheunderlyingenvironment:Standardrules(protocols/interfaces)todescribeservices/componentsInterfaceddefinitionsshouldbe:Complete&VendorneutralThesehelpmakingsystem/servicesshouldinteroperable&portableFlexibility–abilitytointegratemultiplecomponentsAchievingopenness:Atleastmakethedistributedsystemindependentfromheterogeneity

oftheunderlyingenvironment:HardwarePlatformsLanguagesSeparatingpolicyandmechanismToachieveflexibility:

splitthesystemsinsmallercomponents.Componentsrequiressupportfordifferentpoliciesspecifiedbyapplicationsandusers:Example–webbrowsercaching;Mechanism:cachinginfrastructurePolicy:whattocache,howlargethecacheis,cachereplacementalgorithms,OtherexamplesWhichoperationsdoweallowdownloadedcodetoperform?WhichQoSrequirementsdoweadjustinthefaceofvaryingbandwidth?Whatlevelofsecrecydowerequireforcommunication?DevelopingDistributedSystems:PitfallsObservation:Manydistributedsystemsareneedlesslycomplexcausedbymistakesthatrequiredpatchinglateron.Manypossiblefalseassumptions:ThenetworkisreliableThenetworkissecureThenetworkishomogeneousThetopologydoesnotchangeLatencyiszeroBandwidthisinfiniteTransportcostiszeroThereisoneadministratorOutline1.0Motivation1.1DefinitionofADistributedSystem1.2GoalsMakingResourcesAccessibleDistributionTransparencyOpennessScalabilityPitfalls1.3TypesofDistributedSystemsDistributedComputingSystemsDistributedInformationSystemsDistributedPervasiveSystemsTypesofDistributedSystemsDistributedcomputingsystemsCommonlyusedinhigh-performancecomputingClustersGridsDistributedinformationsystemsDistributedtransactionsystemsEnterpriseapplicationintegrationDistributedpervasivesystemsHomesystemsHealthcareSensornetworksDistributedComputingSystems(1/2)Observation:ManydistributedsystemsareconfiguredforHigh-PerformanceComputingClusterComputing:Essentiallyagroupofhigh-endsystemsconnectedthroughaLAN:Homogeneous:sameOS,near-identicalhardwareSinglemanagingnodeBeowulfclusterconfigurationMasternodeprovidesinterfacetouserandhandlesjoballocationsDistributedComputingSystems(2/2)GridComputing:lotsofnodesfromeverywhere:HeterogeneousDispersedacrossseveralorganizationsCaneasilyspanawide-areanetworkKeyissue–sharingresourcesacrossorganizationsThus,muchpaingoesintostandardsandinterfacesNote:Toallowforcollaborations,gridsgenerallyusevirtualorganizations.Inessence,thisisagroupingofusers(orbetter:theirIDs)thatwillallowforauthorizationonresourceallocation.DistributedComputingSystems(2/2)AnearlyexamplearchitectureforgridsFabric–interfacestolocalresourcesConnectivity–communicationprotocolsforsupportingtransactionsusingmultipleresourcesResource–managementofasingleresourceCollective–handle

accesstomultipleresourcesAlayeredarchitectureforgridcomputingsystems.DistributedInformationSystemsObservation:organizationsthatwereconfrontedwithawealthofnetworkedapplications,butforwhichinteroperabilityturnedouttobeapainfulexperience.Manyoftheexistingmiddlewaresolutionsaretheresultofworkingwithaninfrastructureinwhichitwaseasiertointegrateapplicationsintoanenterprise-wideinformationsystemWecandistinguishseverallevelsatwhichintegrationtookplace.TransactionProcessingSystemsInmanycases,anetworkedapplicationsimplyconsistedofaserverrunningthatapplication(oftenincludingadatabase)andmakingitavailabletoremoteprograms,calledclients.EnterpriseApplicationIntegration(EAI)Asapplicationsbecamemoresophisticatedandweregraduallyseparatedintoindependentcomponents(notablydistinguishingdatabasecomponentsfromprocessingcomponents),itbecameclearthatintegrationshouldalsotakeplacebylettingapplicationscommunicatedirectlywitheachother.DistributedinformationsystemsOrganizationshavemultiplenetworkedapplications–howtointegratethem?Fordatabase-orientedapplication&atthelowestlevelTransaction–setofoperationwithACIDpropertiesAtomic–allornothingatallConsistent–ifconsistentbefore,consistentafterIsolated–concurrenttransactionsdon’tinterferewitheachotherDurable–onceit’sdone,it’spermanentNestedtransactionsfordistributedsystemsPermanent?Onlyforthetop-leveltransactionTointegrateapplicationindependentfromtheirdatabasesDifferentcommunicationmodels:RPC,RMI,andMOM…DistributedInformationSystemsObservation:Thevastamountofdistributedsystemsinusetodayareformsoftraditionalinformationsystems,thatnowintegratelegacysystems.Example:Transactionprocessingsystems.BEGINTRANSACTION(server,transaction);READ(transaction,file-1,data);WRITE(transaction,file-2,data);newData:=MODIFIED(data);IFWRONG(newData)THEN ABORTTRANSACTION(transaction);ELSE WRITE(transaction,file-2,newData); ENDTRANSACTION(transaction);ENDIF;Essential:AllREADandWRITEoperationsareexecuted,i.e.theireffectsaremadepermanentattheexecutionofENDTRANSACTION.Observation:Transactionsformanatomic

operation.AnestedtransactionsIsconstructedfromanumberofsubtransactionsGainperformanceorsimplifyprogramming.TransactionProcessingMonitorObservation:Inmanycases,thedatainvolvedinatransactionisdistributedacrossseveralservers.ATPMonitor

isresponsibleforcoordinatingtheexecutionofatransaction:DistributedInformationSystems:

EnterpriseApplicationIntegrationProblem:ATPmonitorworksfinefordatabaseapplications,butinmanycases,theappsneededtobeseparatedfromthedatabasestheywereactingon.Instead,whatwasneededwerefacilitiesfordirectcommunicationbetweenapplications:RemoteProcedureCall(RPC)Message-OrientedMiddleware(MOM)DistributedPervasiveSystemsObservation:Thereisanext-generationofdistributedsystemsemerginginwhichthenodesaresmall,mobile,andoftenembeddedaspartofalargersystem.Somerequirements:Contextualchange:Thesystemispartofanenvironmentinwhichchangesshouldbeimmediatelyaccountedfor.Adhoccomposition:Eachnodemaybeusedinaverydifferentwaysbydifferentusers.Requiresease-of-configuration.Sharingisthedefault:Nodescomeandgo,providingsharableservicesandinformation.Callsagainforsimplicity.Observation:Pervasivenessanddistributiontransparencymaynotalwaysformagoodmatch.PervasiveSystems:ExamplesHomeSystems:Shouldbecompletelyself-organizing:ThereshouldbenosystemadministratorProvideapersonalspace

foreachofitsusersSimplestsolution:acentralizedhomebox?Electronichealthsystems:Devicesarephysicallyclosetoaperson:Whereandhowshouldmonitoreddatabestored?Howcanwepreventlossofcrucialdata?Whatinfrastructureisneededtogenerateandpropagatealerts?Howcansecuritybeenforced?Howcanphysiciansprovideonlinefeedback?SensornetworksCharacteristics:Thenodestowhichsensorsareattachedare:Many(10s-1000s)Simple(i.e.,hardlyanymemory,CPUpower,orcommunicationfacilities)Oftenbattery-powered(orevenbattery-less)Sensornetworksasdistributedsystems:considerthemfromadatabaseperspective:Summary(1/2)Distributedsystemsconsistofautonomouscomputersthatworktogethertogivetheappearanceofasinglecoherentsystem.Oneimportantadvantageisthattheymakeiteasiertointegratedifferentapplicationsrunningondifferentcomputersintoasinglesystem.

Anotheradvantageisthatwhenproperlydesigned,distributedsystemsscalewellwithrespecttothesizeoftheunderlyingnetwork.Distributedsystemsoftenaimathidingmanyoftheintricaciesrelatedtothedistributionofprocesses,data,andcontrol.However,thisdistributiontransparencynotonlycomesataperformanceprice,butinpracticalsituationsitcanneverbefullyachieved.Thefactthattrade-offsneedtobemadebetweenachievingvariousformsofdistributiontransparencyandcaneasilycomplicatetheirunderstanding.Summary(2/2)Mattersarefurthercomplicatedbythefactthatmanydevelopersinitiallymakeassumptionsabouttheunderlyingnetworkthatarefundamentallywrong.Later,whenassumptionsaredropped,itmayturnouttobedifficulttomaskunwantedbehavior.Otherpitfallsincludeassumingthatthenetworkisreliable,static,secure,andhomogeneous.Differenttypesofdistributedsystemsexistwhichcanbeclassifiedasbeingorientedtowardsupportingcomputations,informationprocessing,andpervasiveness.Distributedcomputingsystemsaretypicallydeployedforhigh-performanceapplicationsoftenoriginatingfromthefieldofparallelcomputing.Ahugeclassofdistributedcanbefoundintraditionalofficeenvironmentswhereweseedatabasesplayinganimportantrole.Typically,transactionprocessingsystemsaredeployedintheseenvironments.Finally,anemergingclassofdistributedsystemsiswherecomponentsaresmallandthesystemiscomposedinanadhocfashion,butmostofallisnolongermanagedthroughasystemadministrator.DistributedSystems

ArchitecturesYingchiMaoOutlineArchitecturalstylesSystemarchitecturesArchitecturesversusmiddlewareSelf-managementindistributedsystemsWhatisaDistributedSystem?Adistributedsystemis:acollectionofindependentcomputersthatappearstoitsusersasasinglecoherentsystemDefinitionofaDistributedSystem(II)IndependenthardwareinstallationsUniformsoftwarelayer(middleware)Note:themiddlewarelayerextendsovermultiplemachinesMiddlewareGeneralstructureofadistributedsystemasmiddleware.MiddlewareandInteroperabilityInteroperabilityprovidedby:ProtocolsusedbyeachmiddlewarelayerInterfacesofferedtoapplicationsIndependent

hardwareinstallationsUniformsoftwarelayer(middle