Traffic Models and QoS

Transcription

1 Traffic Models ad QoS TELE4642: Week9 Ackowledgemet: Some slides are adapted from Computer Networkig: A Top Dow Approach Featurig the Iteret, 2 d editio, J.F Kurose ad K.W. Ross All Rights Reserved, copyright

2 Outlie What is QoS? What does Iteret traffic look like? Is it Poisso? What are the implicatios for etwork performace? Approaches to providig QoS: Laissez faire approach No chage to etwork; Applicatio-level bag of tricks Structured approach Chage etwork to provide some performace guaratees QoS mechaisms: Packet classificatio ad markig Packet policig/shapig Packet schedulig Resource allocatio IETF ItServ ad DiffServ frameworks Network Performace 9-2

3 What is QoS? Applicatios: Existig: , ftp, web; delay isesitive, loss sesitive Emergig: VoIP, multimedia; delay sesitive, loss isesitive Streamig stored/live audio ad video Real-time iteractive audio ad video Itegrated etwork to support existig ad ew apps Best-effort model adeuate? QoS etwork provides applicatio with level of performace eeded for applicatio to fuctio. Network Performace 9-3

4 Iteret Traffic: Need a model All performace techiues must make some assumptios regardig traffic Aalytical models: arrival ad service time distributios Simulatio: traffic geerators Experimets: traffic traces or real traffic Aalysis of trace data A trace is captured from a live etwork Normally wat to statistically characterize the trace to build a model, but may be able to use the trace directly How do we kow our sample is typical or large eough? Network Performace 9-4

5 Markovia Models Poisso Process Appropriate if there is a large umber of idepedet users ad o source domiates? We kow ad love it! (good hadle o M/M/1 ueues) µ 01 rate l rate l 2 µ 10 Variatios: Markov Modulated Poisso Process (MMPP) A Poisso arrival process with time-varyig arrival rate l(t) Process modulatig the Poisso arrivals has a Markov chai Markov Modulated Fluid Process (MMFP) Embedded Markov models, Regressio models, Network Performace 9-5

6 Traffic Burstiess Variability i traffic rate / volume Why is burstiess importat? Peak traffic demads o buffer resources ca lead to overflow ad lost traffic Peak demads may create uality of service (QoS) problems i a etwork Need to characterize burstiess for traffic sources i a QoS eviromet Ca be characterized i may ways: Ratio of peak rate to mea rate Coefficiet of variatio of traffic load over differet itervals Idex of dispersio of itervals (IDI) Idex of dispersio of couts (IDC) Spectral (freuecy) characteristics Stochastic process etropy rate Network Performace 9-6

7 Traffic Modelig Pre-1990 s: Traffic modelig i the world of telephoy was the basis for iitial etwork models Assumed Poisso arrival process Assumed expoetial call duratio Well established ueuig literature based o these assumptios Eabled very successful egieerig of telephoe etworks I 1989, Lelad ad Wilso begi takig high resolutio traffic traces at Bellcore Etheret traffic from a large research lab 100 µsec time stamps Packet legth, status, 60 bytes of data Mostly IP traffic (a little NFS) Four data sets over three year period Over 100 millio packets i traces Traces cosidered represetative of ormal use Network Performace 9-7

8 Measured Traffic Network Performace 9-8

9 Poisso Traffic Network Performace 9-9

10 Geerated vs. Measured Traffic Network Performace 9-10

11 Fractals: Scalig property A Poisso process Whe observed o a fie time scale will appear bursty Whe aggregated o a coarse time scale will flatte (smooth) to white oise A Self-Similar (fractal) process A pheomeo that is self-similar looks or behaves the same whe viewed at differet degrees of magificatio or differet scales o a dimesio (time or space) Whe aggregated over wide rage of time scales will maitai its bursty characteristic Hurst parameter H (0.5 H 1) measures degree of self-similarity Network Performace 9-11

12 Geerated vs. Measured Traffic If etwork traffic is self-similar, there is sigificat amout of clusterig at all time scales Reuires more bufferig Leads to higher ueueig delays Mea waitig time Queue occupacy Network Performace 9-12

13 IP QoS History Iceptio: ToS byte i IP header 1986: TCP developed Early-1990s: QoS mechaisms for routers: Packet schedulig Packet droppig Traffic coditioig Resource allocatio Mid-1990s: ItServ framework firm guaratees ( cotract ) Late-1990s: DiffServ framework Classes that receive differetial service 2000s: MPLS ad Traffic Egieerig Network Performace 9-13

14 QoS i Today s Iteret TCP/UDP/IP: best-effort service o guaratees o delay, loss??????? But you said multimedia apps reuires QoS ad level of performace to be effective!???? Today s Iteret multimedia applicatios use applicatio-level techiues to mitigate (as best possible) effects of delay, loss Network Performace 9-14

15 Ad-hoc approach: Applicatio-level solutios Example: Iteret Phoe UDP: avoid TCP cogestio cotrol (delays) for timesesitive traffic Delay compesatio: adaptive play-out delay at cliet Loss compesatio: FEC, iterleavig, retrasmissios Badwidth estimatio: server side matches stream badwidth to available cliet-to-server path badwidth chose amog pre-ecoded stream rates dyamic server ecodig rate Network Performace 9-15

16 Structured approach: Priciples Example: 1Mbps IP phoe, FTP share 1.5 Mbps lik. bursts of FTP ca cogest router, cause audio loss wat to give priority to audio over FTP Priciple 1 packet classificatio ad markig eeded for router to distiguish traffic Network Performace 9-16

17 Priciples for QOS (cotd.) what if applicatios misbehave (audio seds higher tha declared rate) Policig/shapig: force source to adherece to badwidth allocatios Priciple 2 provide protectio (isolatio) for oe class from others Network Performace 9-17

18 Priciples for QOS (cotd.) Allocatig fixed (o-sharable) badwidth to flow: iefficiet use of badwidth if flow does t use its allocatio Priciple 3 While providig isolatio, it is desirable to use resources as efficietly as possible Network Performace 9-18

19 Priciples for QOS (cotd.) Basic fact of life: ca ot support traffic demads beyod lik capacity Priciple 4 Resource allocatio ad Call Admissio: etwork may block call (e.g., busy sigal) if it caot meet eeds Network Performace 9-19

20 Summary of QoS Priciples Let s ext look at mechaisms for achievig this. Network Performace 9-20

21 Packet Classificatio ad Markig Classificatio ca be based o: 9-tuple: <src-ip, dst-ip, proto, src-port, dst-port> Etheret MAC addresses Packet cotet: e.g. URL Markig doe i IP ToS byte, ow reamed the Diff-Serv Code Poit (DSCP) byte Core routers ca use markig, eed ot reclassify 9-21

22 Policig ad Shapig Goal: limit traffic to ot exceed declared parameters Three commo-used criteria: (Log term) Average Rate Peak Rate (Maximum) Burst Size Policig/Shapig Mechaism: Toke Bucket: limit iput to specified Burst Size ad Average Rate. bucket ca hold b tokes tokes geerated at r toke/sec uless bucket full over iterval of legth t: umber of packets/bytes admitted o more tha (r t + b). Network Performace 9-22

23 Packet Schedulig schedulig: choose ext packet to sed o lik FIFO (first i first out) schedulig: sed i order of arrival to ueue example: supermarket check-out Network Performace 9-23

24 Schedulig Policies (cotd.) Priority schedulig: trasmit highest priority ueued packet multiple classes, with differet priorities class may deped o markig or other header ifo, e.g. IP source/dest, port umbers, etc.. example: airlie check-i? Network Performace 9-24

25 Schedulig Policies (cotd.) Weighted Fair Queuig: geeralized Roud Robi each class gets weighted amout of service i each cycle real-world example? Network Performace 9-25

26 Resource Reservatio RSVP (ReSerVatio Protocol) call setup, sigalig traffic, QoS declaratio per-elemet admissio cotrol reuest/ reply Ø QoS-sesitive schedulig (e.g., WFQ) Network Performace 9-26

27 IETF Itegrated Services (ItServ) Objective: QOS guaratees for idividual applicatio sessios resource reservatio: routers maitai state ifo of allocated resources, QoS re s admit/dey ew call setup reuests: Questio: ca ewly arrivig flow be admitted with performace guaratees while ot violated QoS guaratees made to already admitted flows? Network Performace 9-27

28 ItServ Architecture arrivig traffic Policig/shapig: toke bucket Per-flow classificatio ad ueueig WFQ schedulig Resource reservatio / call admissio All the above combie to provide guarateed upper boud o delay, i.e., QoS guaratee! toke rate, r bucket size, b WFQ per-flow rate, R D = b/r max Network Performace 9-28

29 IETF Differetiated Services (DiffServ) Cocers with Itserv: Scalability: sigalig, maitaiig per-flow router state difficult with large umber of flows Flexible Service Models: Itserv has oly two classes. Also wat ualitative service classes behaves like a wire relative service distictio: Platium, Gold, Silver Diffserv approach: simple fuctios i etwork core, relatively complex fuctios at edge routers (or hosts) Do t defie defie service classes, provide fuctioal compoets to build service classes Network Performace 9-29

30 Diffserv Architecture Edge router: - per-flow traffic maagemet - marks packets as i-profile ad out-profile b markig r schedulig... Core router: - per class traffic maagemet - bufferig ad schedulig based o markig at edge - preferece give to i-profile packets Network Performace 9-30

31 How should the Iteret evolve to better support multimedia? Itegrated services philosophy: Fudametal chages i Iteret so that apps ca reserve ed-to-ed badwidth Reuires ew, complex software i hosts & routers Differetiated services philosophy: Fewer chages to Iteret ifrastructure, yet provide 1st ad 2d class service. Laissez-faire o major chages more badwidth whe eeded cotet distributio, applicatio-layer multicast applicatio layer What s your opiio? Network Performace 9-31