Better-than-best-effort: QoS, IntServ, DiffServ, RSVP, RTP: BRIEF VERSION

Transcription

1 Better-than-best-effort: QoS, IntServ, DiffServ, RSVP, RTP: BRIEF VERSION Based in part on slides of Ion Stoica, Jim Kurose, Srini Seshan, Srini Keshav 1

2 Overview Why better-than-best-effort (QoS-enabled) Internet? Quality of Service (QoS) building blocks End-to-end protocols: RTP, H.323 Network protocols: Integrated Services(IntServ), RSVP. Scalable differentiated services: DiffServ Control plane: QoS routing, traffic engineering, policy management, pricing models 2

3 Why Better-than-Best-Effort (QoS)? To support a wider range of applications Real-time, Multimedia, etc To develop sustainable economic models and new private networking services Current flat priced models, and best-effort services do not cut it for businesses 3

4 Quality of Service: What is it? Multimedia applications: network audio and video QoS network provides application with level of performance needed for application to function. 4

5 What is QoS? Better performance as described by a set of parameters or measured by a set of metrics. Generic parameters: Bandwidth Delay, Delay-jitter Packet loss rate (or loss probability) Transport/Application-specific parameters: Timeouts Percentage of important packets lost 5

6 What is QoS (contd)? These parameters can be measured at several granularities: micro flow, aggregate flow, population. QoS considered better if a) more parameters can be specified b) QoS can be specified at a fine-granularity. QoS spectrum: Best Effort Leased Line 6

7 Fundamental Problems FIFO Scheduling Discipline B B In a FIFO service discipline, the performance assigned to one flow is convoluted with the arrivals of packets from all other flows! Cant get QoS with a free-for-all Need to use new scheduling disciplines which provide isolation of performance from arrival rates of background traffic 7

8 Fundamental Problems Conservation Law (Kleinrock): Σρ(i)W q (i) = K Irrespective of scheduling discipline chosen: Average backlog (delay) is constant Average bandwidth is constant Zero-sum game => need to set-aside resources for premium services 8

9 QoS Big Picture: Control/Data Planes Control Plane: Signaling + Admission Control or SLA (Contracting) + Provisioning/Traffic Engineering Router Workstation Router Internetwork or WAN Router Workstation Data Plane: Traffic conditioning (shaping, policing, marking etc) + Traffic Classification + Scheduling, Buffer management 9

10 QoS Components QoS => set aside resources for premium services QoS components: a) Specification of premium services: (service/service level agreement design) b) How much resources to set aside? (admission control/provisioning) c) How to ensure network resource utilization, do load balancing, flexibly manage traffic aggregates and paths? (QoS routing, traffic engineering) 10

11 QoS Components (Continued) d) How to actually set aside these resources in a distributed manner? (signaling, provisioning, policy) e) How to deliver the service when the traffic actually comes in (claim/police resources)? (traffic shaping, classification, scheduling) f) How to monitor quality, account and price these services? (network mgmt, accounting, billing, pricing) 11

12 How to upgrade the Internet for QoS? Approach: de-couple end-system evolution from network evolution End-to-end protocols: RTP, H.323 etc to spur the growth of adaptive multimedia applications Assume best-effort or better-than-best-effort clouds Network protocols: IntServ, DiffServ, RSVP, MPLS, COPS To support better-than-best-effort capabilities at the network (IP) level 12

13 QOS SPECIFICATION, TRAFFIC, SERVICE CHARACTERIZATION, BASIC MECHANISMS 13

14 Service Specification Loss: probability that a flow s packet is lost Delay: time it takes a packet s flow to get from source to destination Delay jitter: maximum difference between the delays experienced by two packets of the flow Bandwidth: maximum rate at which the soource can send traffic QoS spectrum: Best Effort Leased Line 14

15 Traffic and Service Characterization To quantify a service one has two know Flow s traffic arrival Service provided by the router, i.e., resources reserved at each router Examples: Traffic characterization: token bucket Service provided by router: fix rate and fix buffer space Characterized by a service model (service curve framework) 15

16 Token Bucket Characterized by three parameters (b, r, R) b token depth r average arrival rate R maximum arrival rate (e.g., R link capacity) A bit is transmitted only when there is an available token When a bit is transmitted exactly one token is consumed r tokens per second bits b tokens b*r/(r-r) slope R slope r <= R bps regulator 16 time

17 Characterizing a Source by Token Bucket Arrival curve maximum amount of bits transmitted by time t Use token bucket to bound the arrival curve bps bits Arrival curve time time 17

18 Example Arrival curve maximum amount of bits transmitted by time t Use token bucket to bound the arrival curve bits (b=1,r=1,r=2) Arrival curve bps time size of time interval

19 Per-hop Reservation Given b,r,r and per-hop delay d Allocate bandwidth r a and buffer space B a such that to guarantee d slope r a bits slope r Arrival curve b d B a 19

20 What is a Service Model? external process offered traffic Network element (connection oriented) delivered traffic The QoS measures (delay,throughput, loss, cost) depend on offered traffic, and possibly other external processes. A service model attempts to characterize the relationship between offered traffic, delivered traffic, and possibly other external processes. 20

21 Arrival and Departure Process R in Network Element R out bits R in (t) = arrival process = amount of data arriving up to time t delay buffer R out (t) = departure process = amount of data departing up to time t t 21

22 Traffic Envelope (Arrival Curve) Maximum amount of service that a flow can send during an interval of time t b(t) = Envelope slope = max average rate Burstiness Constraint slope = peak rate 22 Shivkumar t Kalyanaraman

23 Service Curve Assume a flow that is idle at time s and it is backlogged during the interval (s, t) Service curve: the minimum service received by the flow during the interval (s, t) 23

24 Big Picture bits bits Service curve R in (t) slope = C bits t t R out (t) 24 t

25 Delay and Buffer Bounds bits E(t) = Envelope Maximum delay Maximum buffer S (t) = service curve 25 t

26 Mechanisms: Traffic Shaping/Policing Token bucket: limits input to specified Burst Size (b) and Average Rate (r). Traffic sent over any time T <= r*t + b a.k.a Linear bounded arrival process (LBAP) Excess traffic may be queued, marked BLUE, or simply dropped 26

27 Mechanisms: Queuing/Scheduling Traffic Sources $$$$$$ $$$ Traffic Classes Class A Class B $ Class C Use a few bits in header to indicate which queue (class) a packet goes into (also branded as CoS) High $$ users classified into high priority queues, which also may be less populated => lower delay and low likelihood of packet drop Ideas: priority, round-robin, classification, aggregation,... 27

28 Mechanisms: Buffer Mgmt/Priority Drop Drop RED and BLUE packets Drop only BLUE packets Ideas: packet marking, queue thresholds, differential dropping, buffer assignments 28

29 SCHEDULING 29

30 Packet Scheduling Decide when and what packet to send on output link Usually implemented at output interface flow 1 1 Classifier flow 2 Scheduler 2 flow n Buffer management 30

31 Focus: Scheduling Policies Priority Queuing: classes have different priorities; class may depend on explicit marking or other header info, eg IP source or destination, TCP Port numbers, etc. Transmit a packet from the highest priority class with a non-empty queue Preemptive and non-preemptive versions 31

32 Scheduling Policies (more) Round Robin: scan class queues serving one from each class that has a non-empty queue 32

33 Round-Robin Discussion Advantages: protection among flows Misbehaving flows will not affect the performance of well-behaving flows Misbehaving flow a flow that does not implement any congestion control FIFO does not have such a property Disadvantages: More complex than FIFO: per flow queue/state Biased toward large packets a flow receives service proportional to the number of packets 33

34 Generalized Processor Sharing(GPS) Assume a fluid model of traffic Visit each non-empty queue in turn (RR) Serve infinitesimal from each Leads to max-min fairness GPS is un-implementable! We cannot serve infinitesimals, only packets 34

35 Generalized Processor Sharing A work conserving GPS is defined as Wi ( t, t + w i dt) = W ( t, t + j B( t) dt) w j i B( t) where w i weight of flow i W i (t 1, t 2 ) total service received by flow i during [t 1, t 2 ) W(t 1, t 2 ) total service allocated to all flows during [t 1, t 2 ) B(t) number of flows backlogged 35

36 Fair Rate Computation in GPS Associate a weight w i with each flow i If link congested, compute f such that max( ri, f wi ) = i C (w 1 = 3) 8 (w 2 = 1) 6 (w 3 = 1) f = 2: min(8, 2*3) = 6 min(6, 2*1) = 2 min(2, 2*1) = 2 36

37 Bit-by-bit Round Robin Single flow: clock ticks when a bit is transmitted. For packet i: P i = length, A i = arrival time, S i = begin transmit time, F i = finish transmit time F i = S i +P i = max (F i-1, A i ) + P i Multiple flows: clock ticks when a bit from all active flows is transmitted round number Can calculate F i for each packet if number of flows is known at all times This can be complicated 37

38 Packet Approximation of Fluid Standard techniques of approximating fluid GPS Select packet that finishes first in GPS assuming that there are no future arrivals Important properties of GPS Finishing order of packets currently in system independent of future arrivals Implementation based on virtual time Assign virtual finish time to each packet upon arrival Packets served in increasing order of virtual times System 38

39 Fair Queuing (FQ) Idea: serve packets in the order in which they would have finished transmission in the fluid flow system Mapping bit-by-bit schedule onto packet transmission schedule Transmit packet with the lowest F i at any given time Variation: Weighted Fair Queuing (WFQ) 39

40 Approximating GPS with WFQ Fluid GPS system service order Weighted Fair Queueing select the first packet that finishes in GPS 40

41 FQ Advantages FQ protect well-behaved flows from ill-behaved flows Example: 1 UDP (10 Mbps) and 31 TCP s sharing a 10 Mbps link Throughput(Mbps) RED Throughput(Mbps) FQ Flow Number Flow Number 41

42 Modeling: System Virtual Time: V(t) Measure service, instead of time V(t) slope rate at which every active flow receives service C link capacity N(t) number of active flows in fluid system at time t V(t) V ( t) t = C N ( t) time Service in fluid flow system time

43 Big Picture FQ does not eliminate congestion it just manages the congestion You need both end-host congestion control and router support for congestion control end-host congestion control to adapt router congestion control to protect/isolate Don t forget buffer management: you still need to drop in case of congestion. Which packet s would you drop in FQ? one possibility: packet from the longest queue 43

44 QoS ARCHITECTURES 44

45 Parekh-Gallager theorem Let a connection be allocated weights at each WFQ scheduler along its path, so that the least bandwidth it is allocated is g Let it be leaky-bucket regulated such that # bits sent in time [t 1, t 2 ] <= g(t 2 -t 1 ) + σ Let the connection pass through K schedulers, where the kth scheduler has a rate r(k) Let the largest packet size in the network be P end _ to _ end _ delay σ / g + K 1 P / g + K k = 1 k = 1 P / r ( k ) 45

46 Significance P-G Theorem shows that WFQ scheduling can provide end-to-end delay bounds in a network of multiplexed bottlenecks WFQ provides both bandwidth and delay guarantees Bound holds regardless of cross traffic behavior (isolation) Needs shapers at the entrance of the network Can be generalized for networks where schedulers are variants of WFQ, and the link service rate changes over time 46

47 Stateless vs. Stateful QoS Solutions Stateless solutions routers maintain no fine grained state about traffic scalable, robust weak services Stateful solutions routers maintain per-flow state powerful services guaranteed services + high resource utilization fine grained differentiation protection much less scalable and robust 47

48 Existing Solutions QoS Network support for congestion control Stateful Tenet [Ferrari & Verma 89] IntServ [Clark et al 91] ATM [late 80s] Round Robin [Nagle 85] Fair Queueing [Demers et al 89] Flow Random Early Drop (FRED) [Lin & Morris 97] 48 DiffServ - [Clark & Stateless Wroclawski 97] - [Nichols et al 97] DecBit [Ramkrishnan & Jain 88] Random Early Detection (RED) [Floyd & Jacobson 93] BLUE [Feng et al 99] REM [Low at al 00]

49 Integrated Services (IntServ) An architecture for providing QOS guarantees in IP networks for individual application sessions Relies on resource reservation, and routers need to maintain state information of allocated resources (eg: g) and respond to new Call setup requests 49

50 Signaling semantics Classic scheme: sender initiated SETUP, SETUP_ACK, SETUP_RESPONSE Admission control Tentative resource reservation and confirmation Simplex and duplex setup; no multicast support 50

51 RSVP: Internet Signaling Creates and maintains distributed reservation state De-coupled from routing: Multicast trees setup by routing protocols, not RSVP (unlike ATM or telephony signaling) Receiver-initiated: scales for multicast Soft-state: reservation times out unless refreshed Latest paths discovered through PATH messages (forward direction) and used by RESV mesgs (reverse direction). 51

52 Call Admission Session must first declare its QOS requirement and characterize the traffic it will send through the network R-spec: defines the QOS being requested T-spec: defines the traffic characteristics A signaling protocol is needed to carry the R- spec and T-spec to the routers where reservation is required; RSVP is a leading candidate for such signaling protocol 52

53 Call Admission Call Admission: routers will admit calls based on their R-spec and T-spec and base on the current resource allocated at the routers to other calls. 53

54 Stateful Solution: Guaranteed Services Achieve per-flow bandwidth and delay guarantees Example: guarantee 1MBps and < 100 ms delay to a flow Sender Receiver 54

55 Stateful Solution: Guaranteed Services Allocate resources - perform per-flow admission control Sender Receiver 55

56 Stateful Solution: Guaranteed Install per-flow state Services Sender Receiver 56

57 Stateful Solution: Guaranteed Services Challenge: maintain per-flow state consistent Sender Receiver 57

58 Stateful Solution: Guaranteed Per-flow classification Services Sender Receiver 58

59 Stateful Solution: Guaranteed Services Per-flow buffer management Sender Receiver 59

60 Stateful Solution: Guaranteed Services Per-flow scheduling Sender Receiver 60

61 Stateful Solution Complexity Data path Per-flow classification Per-flow buffer management Per-flow scheduling Control path install and maintain per-flow state for data and control paths Classifier Per-flow State flow 1 flow 2 flow n Buffer management Scheduler 61 output interface

62 Stateless vs. Stateful Stateless solutions are more scalable robust Stateful solutions provide more powerful and flexible services guaranteed services + high resource utilization fine grained differentiation protection 62

63 Question Can we achieve the best of two worlds, i.e., provide services implemented by stateful networks while maintaining advantages of stateless architectures? Yes, in some interesting cases. DPS, CSFQ. Can we provide reduced state services, I.e., maintain state only for larger granular flows rather than end-to-end flows? Yes: Diff-serv 63

64 Differentiated Services (DiffServ) Intended to address the following difficulties with Intserv and RSVP; Scalability: maintaining states by routers in high speed networks is difficult sue to the very large number of flows Flexible Service Models: Intserv has only two classes, want to provide more qualitative service classes; want to provide relative service distinction (Platinum, Gold, Silver, ) Simpler signaling: (than RSVP) many applications and users may only w ant to specify a more qualitative notion of service 64

65 Differentiated Services Model Ingress Edge Router Interior Router Egress Edge Router Edge routers: traffic conditioning (policing, marking, dropping), SLA negotiation Set values in DS-byte in IP header based upon negotiated service and observed traffic. Interior routers: traffic classification and forwarding (near stateless core!) Use DS-byte as index into forwarding table 65

66 Diffserv Architecture Edge router: - per-flow traffic management - marks packets as inprofile and out-profile Core router: - per class TM - buffering and scheduling b r marking scheduling... based on marking at edge - preference given to in-profile packets - Assured Forwarding 66

67 Packet format support Packet is marked in the Type of Service (TOS) in IPv4, and Traffic Class in IPv6: renamed as DS 6 bits used for Differentiated Service Code Point (DSCP) and determine PHB that the packet will receive 2 bits are currently unused 67

68 Traffic Conditioning It may be desirable to limit traffic injection rate of some class; user declares traffic profile (eg, rate and burst size); traffic is metered and shaped if non-conforming 68

69 Per-hop Behavior (PHB) PHB: name for interior router data-plane functions Includes scheduling, buff. mgmt, shaping etc Logical spec: PHB does not specify mechanisms to use to ensure performance behavior Examples: Class A gets x% of outgoing link bandwidth over time intervals of a specified length Class A packets leave first before packets from class B 69

70 PHB (contd) PHBs under consideration: Expedited Forwarding: departure rate of packets from a class equals or exceeds a specified rate (logical link with a minimum guaranteed rate) Emulates leased-line behavior Assured Forwarding: 4 classes, each guaranteed a minimum amount of bandwidth and buffering; each with three drop preference partitions Emulates frame-relay behavior 70

71 Question Can we achieve the best of two worlds, i.e., provide services implemented by stateful networks while maintaining advantages of stateless architectures? Yes, in some interesting cases. DPS, CSFQ. Can we provide reduced state services, I.e., maintain state only for larger granular flows rather than end-to-end flows? Yes: Diff-serv 71

72 Scalable Core (SCORE) A trusted and contiguous region of network in which edge nodes perform per flow management core nodes do not perform per flow management edge nodes core nodes edge nodes 72

73 The DPS Approach 1. Define a reference stateful network that implements the desired service 2. Emulate the functionality of the reference network in a SCORE network Reference Stateful Network 73 SCORE Network

74 The DPS Idea Instead of having core routers maintaining perflow state have packets carry per-flow state Reference Stateful Network 74 SCORE Network

75 Dynamic Packet State (DPS) Ingress node: compute and insert flow state in packet s header 75

76 Dynamic Packet State (DPS) Ingress node: compute and insert flow state in packet s header 76

77 Dynamic Packet State (DPS) Core node: process packet based on state it carries and node s state update both packet and node s state 77

78 Dynamic Packet State (DPS) Egress node: remove state from packet s header 78

79 Example: DPS-Guaranteed Services Goal: provide per-flow delay and bandwidth guarantees How: emulate ideal model in which each flow traverses dedicated links of capacity r flow (reservation = r ) r r r Per-hop packet service time = (packet length) / r 79

80 Reality: End-to-end Adaptive Applications Video Coding, Error Concealment, Unequal Error Protection (UEP) Packetization, Marking, Source Buffer Management Congestion control Internet Video Coding, Error Concealment, Unequal Error Protection (UEP) Packetization, Marking, playout Buffer Management Congestion control End-to-end Closed-loop control 80

81 End-to-end: Real-Time Protocol (RTP) Provides standard packet format for real-time application Typically runs over UDP Specifies header fields below Payload Type: 7 bits, providing 128 possible different types of encoding; eg PCM, MPEG2 video, etc. Sequence Number: 16 bits; used to detect packet loss 81

82 Real-Time Protocol (RTP) Timestamp: 32 bytes; gives the sampling instant of the first audio/video byte in the packet; used to remove jitter introduced by the network Synchronization Source identifier (SSRC): 32 bits; an id for the source of a stream; assigned randomly by the source 82

83 RTP Control Protocol (RTCP) Protocol specifies report packets exchanged between sources and destinations of multimedia information Three reports are defined: Receiver reception, Sender, and Source description Reports contain statistics such as the number of packets sent, number of packets lost, inter-arrival jitter Used to modify sender transmission rates and for diagnostics purposes 83

84 Eg: Streaming & RTSP User interactive control is provided, e.g. the public protocol Real Time Streaming Protocol (RTSP) Helper Application: displays content, which is typically requested via a Web browser; e.g. RealPlayer; typical functions: Decompression Jitter removal Error correction: use redundant packets to be used for reconstruction of original stream GUI for user control 84

85 Using a Streaming Server Web browser requests and receives a Meta File (a file describing the object) Browser launches the appropriate Player and passes it the Meta File; Player contacts a streaming server, may use a choice of UDP vs. TCP to get the stream 85

86 Receiver Adaptation Options If UDP: Server sends at a rate appropriate for client; to reduce jitter, Player buffers initially for 2-5 seconds, then starts display If TCP: sender sends at maximum possible rate; retransmit when error is encountered; Player uses a much large buffer to smooth delivery rate of TCP 86

87 H.323 H.323 is an ITU standard for multimedia communications over best-effort LANs. Part of larger set of standards (H.32X) for videoconferencing over data networks. H.323 includes both stand-alone devices and embedded personal computer technology as well as point-to-point and multipoint conferences. H.323 addresses call control, multimedia management, and bandwidth management as well as interfaces between LANs and other networks. 87

88 H.323 Architecture 88

89 Inter-domain QoS: Challenge Provide high quality service across ISPs Problem: intermediate ISPs don t have incentive to provide good service e.g., hot-potato policy? ISP 2 ISP 3 ISP 1 89

90 Approach: Virtual ISP (V-ISP) Avoid crossing ISP boundaries Each ISP will provide good service; V-ISP can easily verify it Allocate/buy service across each ISP and compose them GPoP (core) GPoP (core) Proxy (edge) ISP 1 ISP 2 ISP 3 Proxy (edge) 90

91 Composition Tools for QoS Dynamic Packet State (DPS): Proxy (edge): maintain per flow state; label packets Giga PoPs (core): maintain no per flow state; process packets based on their labels Closed-loop building blocks: No core upgrades, smaller QoS service spectrum I Logical FIFO E I B E I 91 E

92 Closed-Loop Building Blocks for QoS International Link or International Link or 92

93 Closed-loop QoS Building Blocks Priority/WFQ FIFO B B Scheduler: differentiates service on a packet-bypacket basis Loops: differentiate service on an RTT-by-RTT basis using purely edge-based policy configuration. 93

94 Recall: Accln-based Control Policy 1 j j+1 J f i µ Λ ij Λ i,j+1 µ i i control objective : keep if if a i ( t ) = bandwidth; control algorithm : if a ( t ) < ε rec a i i : a ( t ) i ( t, 0 > t ) d j 94 a i ( t ) ε > = i, no way to probe increase of available ε i i = then then [ λ ( t i d λ λ f i i i, t ) 0 µ ( t, i t )] t 94

95 Closed-Loop Service Differentiation: Loss-based or Accumulation-based? 95 95

96 Closed-Loop QoS: Bandwidth Assurances Flow 1 with 4 Mbps assured + 3 Mbps best effort Flow 2 with 3 Mbps best effort 96

97 QoS: an application-level approach sophisticated services in application architecturally above network core simple, fast, diffserv network 97

98 QoS: an application-level approach Application-level infrastructure accommodate network-level service additional tailoring of user services 98

99 Content Delivery Motivation: congestion Browsers Networks Routers 99 Web Servers

100 Content Delivery: idea Reduces load on server Avoids network congestion Browsers Replicated content Content Sink Router Content Source 100 Web Server

101 Client 6 Surrogate CDN: Architectural Layout Request Routing(RR) Distribution System Publisher informs RR of Content Availability. Content Pushed to Distribution System. 2 1 Origin Client Requests Content, Requested redirected to RR. RR finds the most suitable Surrogate Surrogate services client request. 101

102 Summary QoS big picture, building blocks Integrated services: RSVP, 2 services, scheduling, admission control etc Diff-serv: edge-routers, core routers; DS byte marking and PHBs Real-time transport/middleware: RTP, H.323 New problems: inter-domain QoS, Application-level QoS, Content delivery/web caching 102