cs 43: computer networkschaganti/cs43/f18/... · – choice of transport protocol (tcp, udp, icmp,...
TRANSCRIPT
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CS 43: Computer Networks
08:NetworkServicesandDistributedSystems
19September
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Reading Quiz
Lecture8-Slide2
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Last class
• Inter-processcommunicationusingmessagepassing• Howsendandrecvbufferswork• Concurrency
– Multi-threadingvs.multipleprocesses– select()systemcall
Lecture8-Slide3
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Today
• Distributednetworkapplications• Pros/Consof:
– Client-Server– Peer-to-peerarchitecture
• Sourcesofcomplexity
Lecture8-Slide4
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• Cooperatingprocessesinacomputernetwork• Varyingdegreesofintegration
– Loose:email,webbrowsing– Medium:chat,Skype,remoteexecution,remotefilesystems
– Tight:processmigration,distributedfilesystems Lecture8-Slide5
What is a distributed application?
Computer
Network
`processes
messages
Computer
Computer
Computer
Computer
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Inter-process Communication (IPC)
• Inordertocooperate,needtocommunicate• AchievedviaIPC:inter-processcommunication
– abilityforaprocesstocommunicatewithanother
Lecture8-Slide6
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Inter-process Communication (IPC)
• Inordertocooperate,needtocommunicate• AchievedviaIPC:inter-processcommunication
– abilityforaprocesstocommunicatewithanother
• Onasinglemachine:– Sharedmemory
Text
Data
Stack
Text
Data
StackP1 P2
Lecture8-Slide7
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Inter-process Communication (IPC)
• Inordertocooperate,needtocommunicate• AchievedviaIPC:interprocesscommunication
– abilityforaprocesstocommunicatewithanother
• Onasinglemachine:– Sharedmemory
Text
Data
StackP1 P2
Text
Data
Stack
SharedSegment
Lecture8-Slide8
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SharedSegment
Inter-process Communication (IPC)
• Inordertocooperate,needtocommunicate• AchievedviaIPC:interprocesscommunication
– abilityforaprocesstocommunicatewithanother
• Onasinglemachine:– Sharedmemory
• Acrossmachines:– Weneedotherabstractions(messagepassing)
Text
Data
Stack
Text
Data
StackP1 P2
Lecture8-Slide9
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Sockets
• Processsends/receivesmessagesto/fromitssocket• Applicationhasafewoptions,operatingsystemhandlesthedetails
– Choiceoftransportprotocol(TCP,UDP,ICMP,SCTP,etc.)– Transportoptions(TCP:maximumsegmentsize,delayedsends)
Internet
controlledbyOS
controlledbyappdeveloper
transport
application
physical
link
network
process
transport
application
physical
link
network
processsocket
Lecture8-Slide10
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Sockets
• Processsends/receivesmessagesto/fromitssocket• Applicationhasafewoptions,operatingsystemhandlesthedetails
– Choiceoftransportprotocol(TCP,UDP,ICMP,SCTP,etc.)– Transportoptions(TCP:maximumsegmentsize,delayedsends)
• Mustidentifywhichsocketwe’readdressing
Internet
controlledbyOS
controlledbyappdeveloper
transport
application
physical
link
network
process
transport
application
physical
link
network
processsocket
Lecture8-Slide11
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App
TCP
IP
Ethernet interface
App
TCP
IP
Ethernet interface
IP IP
Ethernet interface
Ethernet interface
SONET interface
SONET interface
host host
router router
Addressing Sockets
• IPaddressidentifiesdeviceinterface
Lecture8-Slide12
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App
TCP
IP
Ethernet interface
App
TCP
IP
Ethernet interface
IP IP
Ethernet interface
Ethernet interface
SONET interface
SONET interface
host host
router router
Addressing Sockets
• IPaddressidentifiesdeviceinterface
• Needanotheridentifier:port– 16-bit,unsignedintegervalue– Differentiatessockets
Lecture8-Slide13
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§ TCPsocketidentifiedby4-tuple:• sourceIPaddress• sourceportnumber• destIPaddress• destportnumber
§ Receiverusesallfourvaluestodirectsegmenttoappropriatesocket
§ serverhostmaysupportmanysimultaneousTCPsockets:• eachsocketidentifiedbyitsown4-tuple
§ webservershavedifferentsocketsforeachconnectingclient• non-persistentHTTPwillhavedifferentsocketforeachrequest
Connection-oriented: example
Lecture8-Slide14
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Connection-oriented: example
transport
application
physical
link
network
P3 transport
application
physical
link
P4
transport
application
physical
link
network
P2
source IP,port: A,9157 dest IP, port: B,80
source IP,port: B,80 dest IP,port: A,9157
host: IP address A
host: IP address C
network
P6 P5 P3
source IP,port: C,5775 dest IP,port: B,80
source IP,port: C,9157 dest IP,port: B,80
three segments, all destined to IP address: B, dest port: 80 are demultiplexed to different sockets
server: IP address B
Lecture8-Slide15
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Connection-oriented: example
transport
application
physical
link
network
P3 transport
application
physical
link
transport
application
physical
link
network
P2
source IP,port: A,9157 dest IP, port: B,80
source IP,port: B,80 dest IP,port: A,9157
host: IP address A
host: IP address C
server: IP address B
network
P3
source IP,port: C,5775 dest IP,port: B,80
source IP,port: C,9157 dest IP,port: B,80
P4
threaded server
Lecture8-Slide16
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Client/Server Model
• Client– Short-livedprocessthatmakesrequests– “User-side”ofapplication– Initiatesthecommunication(oftenviaconnect())
• Server– Exportswell-definedrequests/responseinterface– Long-livedprocessthatwaitsforrequests– Uponreceivingrequest,carriesitout(mayspawnprocesses)
Client ServerInternet
Lecture8-Slide17
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Server:• always-onhost• permanent(IP)address(rendezvouslocation)• staticportconventions(http:80,email:25,ssh:22)• datacentersforscaling• maycommunicatewithotherserverstorespond
Clients:• maybeintermittentlyconnected• mayhavedynamic(IP)addresses• donotcommunicatedirectlywitheachother
Lecture8-Slide18
Client vs. Server
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• noalways-onserver• arbitraryendsystemsdirectly
communicate• peersrequestservicefrom
otherpeers,provideserviceinreturntootherpeers– selfscalability–newpeersbringnewservicecapacity,aswellasnewservicedemands
• peersareintermittentlyconnectedandchangeIPaddresses– complexmanagement
peer-peer
Lecture8-Slide19
Peer-to-Peer
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Peer-to-Peer
• Apeertalksdirectlywithanotherpeer– Symmetricresponsibility(unlikeclient/server)
• Oftenusedfor:– Filesharing(Napster,BitTorrent)– Games– “NoSQL”dataretrieval– Ingeneral:“distributedsystems”
Peer Peer
Lecture8-Slide20
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In a peer-to-peer architecture, are there clients and servers?
A. Yes
B. No
Lecture8-Slide21
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Peer-to-Peer
• (+)Peersrequestservicefromotherpeers,provideserviceinreturntootherpeers– selfscalability–newpeersbringnewservicecapacity,aswellasnewservicedemands
• (-)Complexmanagement,difficultproblems
Peer Peer
Lecture8-Slide22
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Advantages
• Speed:parallelism,lesscontention• Reliability:redundancy,faulttolerance• Scalability:incrementalgrowth,economyofscale• Geographicdistribution:lowlatency,reliability
Lecture8-Slide23
Network
`processes
messages
Computer
Computer
Computer
Computer
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If one machine can process requests at a rate of X per second, how quickly can two machines process requests?
A. Slowerthanonemachine(<X)B. Thesamespeed(X)C. Fasterthanonemachine,butnotdouble(X-2X)D. Twiceasfast(2X)E. Morethantwiceasfast(>2X)
Lecture8-Slide24
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Disadvantages
• Fundamentalproblemsofdecentralizedcontrol– Stateuncertainty:nosharedmemoryorclock– Actionuncertainty:mutuallyconflictingdecisions
• Distributedalgorithmsarecomplex
Lecture8-Slide25
Network
`processes
messages
Computer
Computer
Computer
Computer
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On a single system…
• Youhaveanumberofcomponents– CPU– Memory– Disk– Powersupply
• Ifanyofthesegowrong,you’re(usually)toast.
Lecture8-Slide26
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On multiple systems…
• Newclassesoffailures(partialfailures).– Alinkmightfail
– One(ofmany)processesmightfail
– Thenetworkmightbepartitioned
Lecture8-Slide27
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On multiple systems…
• Newclassesoffailures(partialfailures).– Alinkmightfail
– One(ofmany)processesmightfail
– Thenetworkmightbepartitioned
Introducesmajorcomplexity! Lecture8-Slide28
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If a process sends a message, can it tell the difference between a slow link and a delivery failure?
Lecture8-Slide29
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If a process sends a message, can it tell the difference between a slow link and a delivery failure?
A. Yes
B. No
Lecture8-Slide30
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What should we do to handle a partial failure? Under what circumstances, or what types of distributed applications?
A. Ifoneprocessfailsorbecomesunreachable,switchtoaspare.
B. Pauseorshutdowntheapplicationuntilallconnectivityandprocessesareavailable.
C. Allowtheapplicationtokeeprunning,evenifnotallprocessescancommunicate.
D. Handlethefailureinsomeotherway.
Lecture8-Slide31
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Desirable Properties
• Consistency– Nodesagreeonthedistributedsystem’sstate
• Availability– Thesystemisableandwillingtoprocessrequests
• Partitiontolerance– Thesystemisrobusttonetwork(dis)connectivity
Lecture8-Slide32
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The CAP Theorem • Consistency
– Nodesagreeonthedistributedsystem’sstate• Availability
– Thesystemisableandwillingtoprocessrequests• Partitiontolerance
– Thesystemisrobusttonetwork(dis)connectivity
• ChooseTwo• “CAPprohibitsonlyatinypartofthedesignspace:perfect
availabilityandconsistencyinthepresenceofpartitions,whicharerare.”*
*Brewer,Eric."CAPtwelveyearslater:Howthe"rules"havechanged."Computer45.2(2012):23-29. Lecture8-Slide33
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Event Ordering
• It’sveryusefulifallnodescanagreeontheorderofeventsinadistributedsystem
• Forexample:Twouserstryingtoupdateasharedfileacrosstworeplicas
Lecture8-Slide34
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If two events occur (digitally or in the “real world”), can we always tell which happened first?
A. Yes
B. No
“Relativityofsimultaneity”• Example:observingcarcrashes• Exception:causalrelationship
Lecture8-Slide35
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If two events occur (digitally or in the “real world”), can we always tell which happened first?
A. Yes
B. No
“Relativityofsimultaneity”• Example:observingcarcrashes• Exception:causalrelationship
Lecture8-Slide36
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Event Ordering
• It’sveryusefulifallnodescanagreeontheorderofeventsinadistributedsystem
• Forexample:Twouserstryingtoupdateasharedfileacrosstworeplicas
• “Time,Clocks,andtheOrderingofEventsinaDistributedSystem”byLeslieLamport(1978)– Establishescausalorderings– Cited>8000times
Lecture8-Slide37
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Causal Consistency Example
• Supposewehavethefollowingscenario:– SallypoststoFacebook,“Billyismissing!”– (Billyisatafriend’shouse,seesmessage,callsmom)– Sallypostsnewmessage,“Falsealarm,he’sfine”– Sally’sfriendJamesposts,“Whatarelief!”
• NOTcausallyconsistent:– Thirduser,Henry,seesonly:
Lecture8-Slide38
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Causal Consistency Example
• Supposewehavethefollowingscenario:– SallypoststoFacebook,“Billyismissing!”– (Billyisatafriend’shouse,seesmessage,callsmom)– Sallypostsnewmessage,“Falsealarm,he’sfine”– Sally’sfriendJamesposts,“Whatarelief!”
• NOTcausallyconsistent:– Thirduser,Henry,seesonly:
Lecture8-Slide39
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Causal Consistency Example
• Supposewehavethefollowingscenario:– SallypoststoFacebook,“Billyismissing!”– (Billyisatafriend’shouse,seesmessage,callsmom)– Sallypostsnewmessage,“Falsealarm,he’sfine”– Sally’sfriendJamesposts,“Whatarelief!”
• Causallyconsistentversion:– Thirduser,Henry,seesonly:
BecauseJameshadseenSally’ssecondpost(whichcausedhisresponse),HenrymustalsoseeitpriortoseeingJames’s.
Lecture8-Slide40
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Summary
• Client-servervs.peer-to-peermodels
• Distributedsystemsarehardtobuild!– Partialfailures– Orderingofevents
• TakeCS87formoredetails!
Lecture8-Slide41