ITTC Communication Networks The University of Kansas EECS 780 Traffic Management and QoS

Transcription

1 Communication Networks The University of Kansas EECS 780 Traffic Management and QoS James P.G. Sterbenz Department of Electrical Engineering & Computer Science Information Technology & Telecommunications Research Center The University of Kansas 04 December 2017 rev James P.G. Sterbenz

2 Traffic Management and QoS TQ.1 Functions and Services TQ.1 Traffic management functions and services TQ.2 Traffic characteristics and service models TQ.3 Basic queueing analysis TQ.4 Congestion control and avoidance TQ.5 Packet scheduling disciplines TQ.6 QoS and Internet service models TQ.6.1 Guaranteed service and ATM TQ.6.2 IntServ and RSVP TQ.6.3 DiffServ TQ.6.4 MPLS traffic engineering 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-2

3 L8 L7 L5 L4 L3 L2.5 L2 L1.5 L1 Network Layer Control Hybrid Layer/Plane Cube data plane management plane control plane social application session transport network virtual link link MAC physical Layer 3: traffic management in control plane significant interaction with management plane Layer 4: interacts with L3 traffic mgt 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-3

4 Network Layer Service and Interfaces Network layer 3 is above link layer 2 addressing : network layer identifier for end systems (hosts) forwarding : transfers packets hop-by-hop using link layer services network layer responsible for determining which next hop routing : determination of path to forward packets signalling : messages to control network layer behaviour traffic management : actions to manage E2E service quality Network layer service to transport layer (L4) deliver TPDUs to destination transport entity 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-4

5 Switches Functions: Routing and Signalling Traffic management routing and signalling signalling topology DB routing network management traffic management transfer control filter classify forwarding table fabric control cong control link sched data manipulation input processing link decaps switch fabric output processing link encaps 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-5

6 Network Layer Service Model and Traffic Management Service model describes service the network provides for end-to-end data transfer Traffic management actions the network takes to manage this service Conflicting goals sufficient resources to deliver required service to users minimise network resource use to keep costs low Components congestion control and avoidance resource provisioning and (perhaps) QoS 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-6

7 Traffic Management and QoS TQ.2 Traffic Characteristics & Service Models TQ.1 Traffic management functions and services TQ.2 Traffic characteristics and service models TQ.3 Basic queueing analysis TQ.4 Congestion control and avoidance TQ.5 Packet scheduling disciplines TQ.5 QoS and Internet service models 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-7

8 Traffic Characteristics Service Models Networks provide a service model to applications Best effort no service guarantees to application Probabilistic guarantees statistical guarantees of performance parameters Absolute guarantees guarantees of performance parameters 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-8

9 Best effort Traffic Characteristics Service Models: Best Effort no service guarantees to application only best effort attempt to eventually deliver packets Resource allocation over provisioning to provide reasonable service no resource allocation to individual flows may schedule among flows for fairness 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-9

10 Traffic Characteristics Service Models: Probabilistic Guarantees Probabilistic guarantees statistical guarantees of performance parameters Resource allocation allocation of resources to meet probabilistic service bounds assumes benefits from statistical multiplexing average rate + burstiness allocation degree of over provisioning helps meet service guarantees 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-10

11 Traffic Characteristics Service Models: Absolute Guarantees Absolute guarantees hard guarantees of performance parameters Resource allocation allocation of resources to meet absolute service bounds worst case allocation of resources peak rate circuit emulation 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-11

12 Traffic Characteristics Traffic Parameters Traffic parameters? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-12

13 Throughput or rate Delay Jitter: delay variance Reliability Delivery order Traffic Characteristics Traffic Parameters 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-13

14 Traffic Characteristics Throughput or Rate r p r a uniform bursty time Main parameters peak rate r p average rate r a burstiness (peak to average ratio or max burst size) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-14

15 Traffic Characteristics Delay Delay [s] is the sum of components: speed-of-light path delay through transmission media through circuits in nodes object transmission delay queueing delay in network nodes due to blocking in a switch fabric (try to avoid) due to contention for an output link todo: fig 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-15

16 1delay distribution ITTC Traffic Characteristics Jitter no jitter low jitter high jitter 0 delay d d d min d Jitter: delay variance around mean delay d min is the minimum path delay additional delay due to variable queueing and processing 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-16

17 Reliability packet loss rate Traffic Characteristics Reliability maximum burst error size 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-17

18 Delivery order Traffic Characteristics Delivery Order whether packets must be delivered in order may be required by E2E protocol or application 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-18

19 Traffic Characteristics Traffic Classes The traffic class specifies the characteristics of a flow constant bit rate (CBR) specified as a single rate variable bit rate specified as (peak rate, average rate, burstiness) best effort a desired minimum rate may be specified Mechanisms to support traffic classes over-provisioning QoS mechanisms 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-19

20 Traffic Characteristics Traffic Matrix Traffic can be characterised by a traffic matrix matrix that describes traffic from every input output pair element i, j is traffic parameter from i to j engineered capacity [b/s or Erlangs] load [b/s or Erlangs] typically over some time interval delay loss rate 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-20

21 Traffic Characteristics Traffic Matrix Example traffic matrix: load [Mb/s] traffic load from i j and j i (typically asymmetric) e.g. requires measurements by service provider r KCK ZÜR = 3.4 r ZÜR KCK = 6.1 BOS KCK LAN MKE SAN STL ZÜR BOS KCK LAN MKE SAN STL ZÜR December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-21

22 Traffic Management and QoS TQ.3 Basic Queueing Analysis TQ.1 Traffic management functions and services TQ.2 Traffic characteristics and service models TQ.3 Basic queueing analysis TQ.4 Congestion control and avoidance TQ.5 Packet scheduling disciplines TQ.6 QoS and Internet service models 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-22

23 Queueing Analysis Basic Model arrival rate utilisation queue server Packets arrive in a queue at rate [1/s] Packets are served at a rate [1/s] service time of s [s] System utilisation is = / [Erlangs] ([1] = [s/s]) expressed as number in (0 1) or % 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-23

24 N = T Variables Queueing Analysis Little s Theorem N average number of customers in system arrival rate [1/s] T average time spent in system [s] Holds for all distributions Intuition as service time increases, so do number in system as arrival rate increases, so do number in system 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-24

25 Queueing Analysis Distributions Arrival and service rates determine performance average rates matter, but Distribution of rates are critical uniform: all interarrival or service times equal simple but unrealistic for most systems exponential or Poisson Pr[k arrivals in interval T] = bursty: arrivals clumped into groups self-similar: distribution similar at different granularities evidence of self-similar traffic in Internet challenges benefits of statistical multiplexing k! k T T e todo: fig 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-25

26 A/S/N Queueing Analysis Notation A and S: distribution of arrivals and service times G general independent M exponential (Poisson) D deterministic or uniform N: number of servers Examples M/M/1: exponential arrival, exponential service, single server 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-26

27 M/M/1 Queueing Analysis Basic Results Utilization = / delay arrival rate / service rate Average time in queue note what happens as 1 Average time in system W T 1 / 1/ 1 delay dmin offered load December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-27

28 M/M/1 Queueing Analysis Discussion M/M/1 equations very simple so they are frequently used in closed-form analysis reflects independent arrivals e.g. Web transactions, PSTN call arrivals does not accurately represent traffic in network bursty traffic correlated traffic G/G/1 equations very complex! requires integration of a function difficult to analyse networks of generalised queues 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-28

29 Analysis Techniques Analytical Analytical queueing analysis mathematical analysis of system useful for small simple system exact behaviour of complex system difficult or impossible not possible to precisely analyse large network of real traffic critical problem: simplifying assumptions must be made for complex systems usefulness of results depends on these assumptions! Simulation Emulation Measurement 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-29

30 Queueing analysis Simulation Analysis Techniques Simulation build software simulation model of system generally more complex models possible than analytical critical problem: real system must be abstracted to software model abstractions usually contain simplifying assumptions usefulness of results depends on abstraction and model! Emulation Measurement 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-30

31 Queueing analysis Simulation Emulation Analysis Techniques Emulation hardware component designed to behave like real system e.g. link emulator allows control of behaviour not possible in real system critical problem emulator usually simplification of real system usefulness of results depends on simplification! emulator frequently a component of simulation or testbed Measurement 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-31

32 Queueing analysis Simulation Emulation Measurement Analysis Techniques Measurement measurement of actual system may be a testbed usually a small replica of real network critical problem: testbed may not reflect scale of real network access to measurement data difficult due to scale of real network due to administrative concerns, including privacy 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-32

33 Analysis Techniques Verification Combination of techniques each technique has strengths and weaknesses should be combined as necessary Verification of models compare results of two techniques to verify model example: compare queueing and simulation model of simple system gives confidence of simulation model for more complex system 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-33

34 Analysis Techniques Design Cycle Use each technique as appropriate in design cycle Design cycle mathematical analysis and/or simulation iterate on design parameters until desired behaviour gives insight on how to build prototype system construct prototype and measure in testbed analysis in small scale iterate design; modify simulation model if necessary build real system on large scale measure to confirm design and modify future deployments 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-34

35 Traffic Management and QoS TQ.4 Congestion Control and Avoidance TQ.1 Traffic management functions and services TQ.2 Traffic characteristics and service models TQ.3 Basic queueing analysis TQ.4 Congestion control and avoidance TQ.5 Packet scheduling disciplines TQ.6 QoS and Internet service models 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-35

36 Flow control Congestion Control Definitions control transmission to avoid overwhelming receiver this is a exclusively a transport layer function lecture TL Congestion control control transmission to avoid overwhelming network paths this is a network layer function that may interact with the transport or application layers 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-36

37 Congestion Control Ideal Network throughput ideal delay carried load delay ideal Ideal network: offered load offered load 1.0 throughput: carried load = offered load (45 line) zero delay (flat line) Why isn t this possible? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-37

38 Congestion Control Real Network Delay can t be zero: speed-of-light delay through network channels delay along paths in network nodes Throughput can t be infinite channel capacity limits bandwidth switching rate of components limits bit rate 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-38

39 Congestion Control Desired Real Network Behaviour 1.0 throughput ideal delay knee carried load delay knee d min offered load 1.0 offered load 1.0 Desired network: carried load = offered load up to share of capacity what happens to delay? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-39

40 Congestion Control Causes of Congestion Congestion when offered load link capacity Best effort occurs whenever load is high Probabilistic guarantees occurs when load exceeds resource reservations Absolute guarantees can t happen (in theory) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-40

41 Congestion Control Infinite Buffers / No Retransmission Congestion when offered load link capacity Infinite buffers queue length builds to infinity d todo: figures 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-41

42 Congestion Control Finite Buffers with Retransmission Finite buffers cause packet loss retransmissions contribute to offered load assuming reliable protocol throughput curve levels off 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-42

43 Multiple hops Congestion Control Multihop Network downstream packet loss upstream transmission wasted 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-43

44 Delay increases Congestion Control Consequences of Congestion due to packet queuing in network nodes due to retransmissions when packets overflow buffers finite buffers must drop packets when full Throughput levels off gradually (with real traffic) then decreases due to retransmissions when packets dropped particularly over multiple hops congestion collapse cliff of the throughput curve 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-44

45 Congestion Control Congestion Control 1.0 throughput ideal delay knee cliff CC cliff carried load delay knee CC d min ideal offered load 1.0 offered load 1.0 Congestion control reacts to congestion operates at the cliff of the curve to prevent collapse What should congestion control do? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-45

46 Congestion Control Local Action Local action at point of congestion Drops packets: discard policy tail drop simplest: drop packets that overflow buffers more intelligent policies possible need flow or connection state in switches discriminate which flows are causing congestion and penalise 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-46

47 Congestion Control End-to-End Action End-to-end action: throttle source reduce transmission rates prevent unnecessary retransmissions Explicit congestion control (ECN) message to signal source to throttle Implicit (TCP) sender assumes that loss is due to congestion source throttles with tail drop of a packet More later 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-47

48 Congestion Control Congestion Control 1.0 throughput ideal delay knee cliff CC cliff carried load delay knee CC d min ideal offered load 1.0 offered load 1.0 Should we be operating just to the left of the cliff? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-48

49 Congestion Control Congestion Control 1.0 throughput ideal delay knee cliff CC cliff carried load delay knee CC d min ideal offered load 1.0 offered load 1.0 Just before the cliff little or not gain in throughput at high delay Where should we operate? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-49

50 Congestion Control Preventing Congestion Collapse Congestion control reacts to congestion occurring may be too late to avoid large-scale congestion collapse Can we do better? consider how a network node could detect congestion 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-50

51 Congestion Control Congestion Avoidance Congestion control reacts to congestion occurring may be too late to avoid large-scale congestion collapse Congestion avoidance attempts to prevent measure impending congestion detection of increasing queue occupancy Important with high bandwidth- -delay product response to an event happens after more bits transferred it may be too late to react all bits causing problem may already be transmitted other cause of problem may have gone away 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-51

52 Congestion Avoidance Congestion Avoidance 1.0 throughput ideal delay knee cliff CC cliff carried load delay knee CA CA CC d min ideal offered load 1.0 offered load 1.0 Congestion avoidance predicts congestion operates at the knee of the curve What should congestion avoidance do? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-52

53 Congestion Avoidance Goals Congestion avoidance prevent congestion from occurring Keep delay low buffer occupancy 0 in steady state buffering needed for transient conditions traffic bursts avoid buffer bloat TCP will use all the buffer provided higher delay for all flows 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-53

54 Congestion Avoidance Mechanisms Queue threshold detects impending congestion less than buffer size (before tail drop) Action to take? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-54

55 Congestion Avoidance Mechanisms Queue threshold detects impending congestion less than buffer size (before tail drop) Implicit congestion avoidance drop causes TCP to throttle when ACK not received 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-55

56 Congestion Avoidance Mechanisms Queue threshold detects impending congestion less than buffer size (before tail drop) Implicit congestion avoidance drop causes TCP to throttle when ACK not received Explicit congestion avoidance signal source to throttle or adjust rate 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-56

57 Congestion Avoidance Mechanisms Queue threshold detects impending congestion less than buffer size (before tail drop) Implicit congestion avoidance drop causes TCP to throttle when ACK not received Explicit congestion avoidance signal source to throttle or adjust rate Fragment discard should cause entire PDU discard PPD/EPD (partial/early packet discard) in ATM network IP fragment discard possible, but better avoid fragmentation 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-57

58 Congestion Avoidance & Control Implicit Sender assume loss is congestion and throttles assumes that all losses are due to congestion End-to-end error and congestion control combined missing ACK assumed to be congestion causes throttling and then retransmission TCP does this Lecture TL reasonable when all losses are due to congestion fiber optic channels connected by reliable switches performs poorly when significant losses in channel mobile wireless links [Krishnan 2004] under-provisioned CDMA (including optical CDMA) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-58

59 Congestion Control & Avoidance Closed-Loop End-to-End Congestion Control congestion control congestion window flow control receive window SS / AIMD transmission Closed loop congestion control feedback from network necessary if no hard reservations 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-59

60 Congestion Control & Avoidance Closed-Loop End-to-End Congestion Control congestion control congestion window flow control receive window SS / AIMD transmission Closed loop congestion control feedback from network necessary if no hard reservations loss (data resulting in no ACK or ACK) throttles source tail drop when router queue is full 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-60

61 Implicit Congestion Avoidance AQM: Random Early Detection RED (random early detection) [Floyd 1993] drop packets Compute average queue length over an interval EWMA: exponentially weighted moving average q = instantaneous queue length q (1 ) q q = weighting factor Drop packets if threshold exceeded q min min q max q q max if do nothing if drop with probability proportional to if drop every packet 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-61

62 Congestion Control & Avoidance Active Queue Management congestion control congestion window flow control receive window SS / AIMD transmission AQM Closed loop congestion avoidance feedback from network necessary if no hard reservations loss (data resulting in no ACK or ACK) throttles source AQM forces loss earlier than tail drop shifts toward knee to keep delay lower 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-62

63 Implicit Congestion Avoidance AQM: Random Early Detection drop probability 1 p max min max q Drop packets if threshold exceeded q min min q max q q max if do nothing if drop with probability proportional to if drop every packet 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-63

64 Implicit Congestion Avoidance AQM: Random Early Detection RED advantages causes TCP sources to throttle to relieve congestion RED disadvantages random drops don t necessarily penalise offending source UDP and non-tcp friendly transport ignores RED drops at the cost of TCP flows RED deployment AQM recommended by [RFC 2309] (1998) RED default recommendation updated by [RFC 7567] (2015) not possible to directly measure deployment E2E 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-64

65 Congestion Control & Avoidance Explicit Congested node signals sender to throttle ECN: explicit congestion notification Explicit signalling message BECN or FECN (backward or forward ECN) example: BECN/FECN in ATM networks example: ICMP source quench requires ability to address signalling message to source Congestion marking of headers in packets example: ECN in IP networks 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-65

66 Congestion Control & Avoidance FECN Performance Forward notification requires full RTT may necessary if no signalling back-channel alternative? FECN CONGESTION C=1 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-66

67 Congestion Control & Avoidance BECN Performance Backward signaling reduces control loop delay half on average important in high bandwidth- -delay networks (why? ) FECN CONGESTION C=1 BECN CONGESTION 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-67

68 Congestion Control & Avoidance Internet ECN Explicit congestion notification in the Internet BECN (backward ECN) ICMP source quench (never deployed) FECN (forward ECN) ECN (explicit congestion notification) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-68

69 ICMP Source Quench Overview ICMP Source quench type = 4 code = 0 payload is congesting datagram + 64B of its payload Congested router signals source TCP throttles Never widely deployed in spite of [RFC 1122] 04 hl TOS length fragment id flag TTL 0 1 header checksum source address destination address checksum unused frag offset 04 hl TOS length fragment id flag TTL protocol header checksum source address destination address frag offset 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-69

70 Congestion Control & Avoidance Explicit Congestion Notification congestion control congestion window flow control receive window SS / AIMD transmission ECN Closed loop congestion avoidance feedback from network necessary if no hard reservations ECN marks packet rather than dropping early E2E congestion signal returned to sender to throttle implicit congestion control still operates in response to loss 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-70

71 Internet ECN Signalling Message Sequence Capability to support ECN signalled by source ECT (ECN capable transport) bit in IP header IP router marks packet when congestion impending CE (congestion experienced) bit in IP header FECN since packets marked; receiver must reply to source Receiver turns around congestion notification ECE (ECN echo) flag in TCP header for ACKs until Sender acknowledges ECE received CWR (congestion window reduced) bit in TCP header 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-71 0

72 ECN fields DSCP replaces part of IPv4 TOS b 6 b 6 DSCP b 6 : ECT ECN capable transport b 7 : CE congestion experienced Internet ECN IP Packet Fields E C T C E DSC 04 hl length P EC fragment id flag frag offset TTL protocol header checksum source address destination address options (= hl 20B) payload (= length hl 20B) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-72

73 C W R E C E U R G A C K Internet ECN TCP Segment Flags Control flags (1 bit each) CWR cong. win. reduced ECE ECN echo URG urgent data ACK acknowledgement PSH push data RST reset connection SYN connection setup FIN connection teardown P S H R S T S Y N F I N 32 bits source port # dest port # sequence number ack number HL CEUAPRSF receive window checksum urg data pointer options (variable length) application payload (variable length) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-73

74 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=0 CWR=0 Capability to support ECN signalled by source ECT (ECN capable transport) bit in IP header set to 1 IP router marks packet when congestion impending Receiver turns around congestion notification Sender acknowledges ECE received 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-74 1

75 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=0 CWR=0 Capability to support ECN signalled by source IP router passes packet unmarked if no congestion CE (congestion experienced) bit in IP header left at 0 Receiver turns around congestion notification Sender acknowledges ECE received 2 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-75

76 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=1 TCP:ECE=0 CWR=0 Capability to support ECN signalled by source IP router marks packet when congestion impending CE (congestion experienced) bit in IP header set to 1 Receiver turns around congestion notification Sender acknowledges ECE received 3 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-76

77 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=1 CWR=0 Capability to support ECN signalled by source IP router marks packet when congestion impending Receiver turns around congestion notification ECE (ECN echo) flag in TCP ACK header set to 1 Sender acknowledges ECE received 4 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-77

78 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=1 CWR=0 Capability to support ECN signalled by source IP router marks packet when congestion impending Receiver turns around congestion notification ECE flag continues to be set in case ACKs dropped until Sender acknowledges ECE received 5 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-78

79 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=0 CWR=1 Capability to support ECN signalled by source IP router marks packet when congestion impending Receiver turns around congestion notification Sender acknowledges ECE received CWR (congestion window reduced) TCP flag set to December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-79

80 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=0 CWR=1 Capability to support ECN signalled by source IP router marks packet when congestion impending Receiver turns around congestion notification Sender acknowledges ECE received note that if CWR packet lost it will be retransmitted 7 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-80

81 Internet ECN Signalling Message Sequence IP IP IP:ECT=1 CE=0 TCP:ECE=0 CWR=0 Capability to support ECN signalled by source IP router marks packet when congestion impending Receiver turns around congestion notification Sender acknowledges ECE received on receipt receiver resets ECE to 0 in subsequent ACKs 8 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-81

82 Congestion Control & Avoidance Open-Loop End-to-End Rate Control admission control network receiver negotiation rate scheduling rate policing conforming traffic excess traffic Initial negotiation of traffic contract admission control limits traffic to available net resources receiver negotiates what it can accept (flow control) Steady state policing enforces traffic contract from transmitter excess traffic may be marked and passed if capacity available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-82

83 Congestion Control & Avoidance Open-Loop End-to-End Rate Control SETUP CONNECT admission control receiver negotiation Initial negotiation of rate specification Lecture NL signalling: forward SETUP / reverse CONNECT or REJECT Mechanism admission control limits traffic to available net resources network accepts connections with CONNECT receiver negotiates what it can accept with CONNECT 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-83

84 Congestion Control & Avoidance Open-Loop End-to-End Rate Control SETUP REJECT admission control receiver negotiation Initial negotiation of rate specification signalling: forward SETUP / reverse CONNECT or REJECT Mechanism admission control limits traffic to available net resources network REJECTs connections that can not be reserved receiver REJECTs connections if not willing or able 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-84

85 Congestion Control & Avoidance Open-Loop End-to-End Rate Control admission control receiver negotiation transmission scheduling rate policing drop conforming traffic Initial negotiation signalling: forward SETUP / reverse CONNECT or REJECT Steady state traffic contract based on negotiated rate policing enforces traffic contract excess traffic in violation of contract dropped sufficient for only guaranteed service with no overbooking 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-85

86 Congestion Control & Avoidance Open-Loop End-to-End Rate Control admission control receiver negotiation transmission scheduling rate policing conforming traffic excess traffic Initial negotiation signalling: forward SETUP / reverse CONNECT or REJECT Steady state traffic contract based on negotiated rate policing enforces traffic contract; drops excess excess traffic may be marked and passed if capacity available sufficient for only guaranteed service with no overbooking 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-86

87 Congestion Control & Avoidance Hybrid End-to-End Rate/Congestion Control admission control receiver negotiation transmission scheduling BECN rate policing drop congestion control Open loop rate control for statistical guarantees Overbooking of resources requires congestion control dynamic rate adjustments signaled to sender as BECN 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-87

88 Traffic Management and QoS TQ.5 Packet Scheduling Disciplines TQ.1 Traffic management functions and services TQ.2 Traffic characteristics and service models TQ.3 Basic queueing analysis TQ.4 Congestion control and avoidance TQ.5 Packet scheduling disciplines TQ.6 QoS and Internet service models 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-88

89 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) operation? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-92 0

90 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-93 1

91 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-94 2

92 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-95 3

93 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-96 4

94 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-97 5

95 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-98 6

96 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-99 7

97 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-100 8

98 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-101 9

99 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

100 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

101 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

102 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

103 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

104 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

105 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

106 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available What happens when the queue fills? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

107 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available Discard policy: when full queue tail drop: drop arriving packet 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

108 Packet Scheduling FIFO Queueing scheduling queue server (link) FIFO (first in first out) send in order of arrival to queue when link available Discard policy: when full queue tail drop: drop arriving packet alternatives? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ

109 Packet Scheduling FIFO Queueing server (link) FIFO (first in first out) send in order of arrival to queue when link available Discard policy: when full queue tail drop: drop arriving packet priority: drop/remove on priority basis random: drop/remove randomly why? December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-112

110 Packet Scheduling FIFO Queueing server (link) FIFO (first in first out) send in order of arrival to queue when link available Discard policy: when full queue tail drop: drop arriving packet priority: drop/remove on priority basis random: drop/remove randomly: RED congestion avoidance December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-113

111 Packet Scheduling FIFO Queueing Advantages and Disadvantages? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-114

112 FIFO is simplest discipline Packet Scheduling FIFO Advantages very simple software management very simple hardware shift register is a series of flip-flops 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-115

113 FIFO is simplest discipline Packet Scheduling FIFO Disadvantages very simple software management very simple hardware shift register is a series of flip-flops All packets treated equally implications? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-116

114 FIFO is simplest discipline Packet Scheduling FIFO Disadvantages All packets treated equally flows not necessarily treated fairly important for best effort service flows not discriminated by service class e.g. gold vs. silver vs. bronze variable packet size not accounted for small packets wait behind large packets (recall message switching) 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-117

115 FIFO is simplest discipline Packet Scheduling FIFO Disadvantages All packets treated equally flows not necessarily treated fairly important for best effort service flows not discriminated by service class e.g. gold vs. silver vs. bronze variable packet size not accounted for small packets wait behind large packets (recall message switching) Alternatives? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-118

116 Priority queueing Packet Scheduling Priority Queueing separate traffic classes by priority serve highest priority first provides relative service differentiation Implementation? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-119

117 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class Packet classifier sorts into proper queues e.g. source address, port, or QoS field 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-120 0

118 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class Packet classifier sorts into proper queues e.g. source address, port, or QoS field 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-121 1

119 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class Packet classifier sorts into proper queues e.g. source address, port, or QoS field 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-122 2

120 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class Packet classifier sorts into proper queues e.g. source address, port, or QoS field 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-123 3

121 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class Packet classifier sorts into proper queues e.g. source address, port, or QoS field 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-124 4

122 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class Packet classifier sorts into proper queues e.g. source address, port, or QoS field 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-125 5

123 Packet Scheduling Priority Queueing Priority queueing FIFO queue for each traffic class queues served in priority order Packet classifier sorts into proper queues e.g. source address, port, or QoS field Higher priority traffic classes receive better service 6 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-126

124 Packet Scheduling Priority Queueing Advantages and Disadvantages? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-127

125 Packet Scheduling Priority Queueing Priority queuing advantages relatively simple discipline priority queues multiple physical FIFO queues memory and pointer management to partition between queues 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-128

126 Packet Scheduling Priority Queueing Priority queueing advantages relatively simple discipline Priority queueing disadvantages provides service differentiation but lower priorities may get no service: starvation no mechanism for proportional service alternatives? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-129

127 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Implementation? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-130 0

128 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-131 0

129 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 1 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-132

130 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 2 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-133

131 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 3 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-134

132 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 4 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-135

133 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 5 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-136

134 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 6 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-137

135 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 7 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-138

136 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns 8 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-139

137 Packet Scheduling Round Robin Queueing Round robin FIFO queue for each class or flow attempt to provide fair service among best-effort flows Packet classifier sorts into proper queues by flow id Packets are served round-robin cyclically taking turns; skip if empty 9 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-140

138 Packet Scheduling Round Robin Queueing Advantages and Disadvantages? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-141

139 Packet Scheduling Round Robin Advantages Round robin is simple discipline very simple software management very simple hardware round robin is a counter the points to a particular queue in per flow round-robin senders are treated equally in terms of number of packets served 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-142

140 Packet Scheduling Round Robin Disadvantages Round robin is simple discipline All classes or flows treated equally implications? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-143

141 Packet Scheduling Round Robin Disadvantages Round robin is simple discipline All classes or flows treated equally senders not necessarily treated fairly variable packet size not accounted for small packets wait behind large packets (recall message switching) senders not discriminated by service class e.g. gold vs. silver vs. bronze 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-144

142 Packet Scheduling Round Robin Disadvantages Round robin is simple discipline All classes or flows treated equally senders not necessarily treated fairly variable packet size not accounted for small packets wait behind large packets (recall message switching) senders not discriminated by service class e.g. gold vs. silver vs. bronze Alternatives? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-145

143 Packet Scheduling Round Robin Disadvantages Round robin is simple discipline All classes or flows treated equally senders not necessarily treated fairly variable packet size not accounted for small packets wait behind large packets (recall message switching) senders not discriminated by service class e.g. gold vs. silver vs. bronze Alternatives : combine priority and round robin? 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-146

144 Packet Scheduling Weighted Round Robin Queueing Weighted round robin FIFO queue for each flow or class (flow aggregates) Packet classifier sorts into proper queues by flow id or traffic class Packets are served cyclically: round-robin weights determine relative service: benefits of priority and RR 0 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-147

145 Motivation Packet Scheduling Fair Queueing fairness among best effort flows GPS: generalised processor sharing ideal fluid model of sharing among flows Bit-by-bit round robin would serve a bit at a time from each queue fair regardless of packet sizes not practical to implement directly 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-148

146 Packet Scheduling Weighted Fair Queueing WFQ (weighted fair queueing) FIFO queue flow or flow class Simulates bit-by-bit round robin schedules packets based on simulated departure time relatively complex to implement 0 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-149

147 Packet Scheduling Deficit Round Robin Fair Queueing Deficit round robin: simple hardware implementation FIFO queue for each class or flow each flow given a quantum of service Packets are served round-robin as long as packet can be served within quantum + deficit unused service (with packet waiting) added to deficit provides long term fairness 0 04 December 2017 KU EECS 780 Comm Nets Traffic Management & QOS NET-TQ-150