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CS 268: Packet Scheduling Ion Stoica March 18/20, 2003

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istoica@cs.berkeley.edu2 Packet Scheduling Decide when and what packet to send on output link -Usually implemented at output interface 1 2 Scheduler flow 1 flow 2 flow n Classifier Buffer management

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istoica@cs.berkeley.edu3 Why Packet Scheduling? Can provide per flow or per aggregate protection Can provide absolute and relative differentiation in terms of -Delay -Bandwidth -Loss

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istoica@cs.berkeley.edu4 Fair Queueing In a fluid flow system it reduces to bit-by-bit round robin among flows -Each flow receives min ( r i, f ), where r i – flow arrival rate f – link fair rate (see next slide) Weighted Fair Queueing (WFQ) – associate a weight with each flow [Demers, Keshav & Shenker 89] -In a fluid flow system it reduces to bit-by-bit round robin WFQ in a fluid flow system Generalized Processor Sharing (GPS) [Parekh & Gallager 92]

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istoica@cs.berkeley.edu5 Fair Rate Computation If link congested, compute f such that 8 6 2 4 4 2 f = 4 : min(8, 4) = 4 min(6, 4) = 4 min(2, 4) = 2 10

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istoica@cs.berkeley.edu6 Fair Rate Computation in GPS Associate a weight w i with each flow i If link congested, compute f such that 8 6 2 4 4 2 f = 2 : min(8, 2*3) = 6 min(6, 2*1) = 2 min(2, 2*1) = 2 10 ( w 1 = 3) ( w 2 = 1) ( w 3 = 1)

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istoica@cs.berkeley.edu7 Generalized Processor Sharing 015210468 511111 Red session has packets backlogged between time 0 and 10 Other sessions have packets continuously backlogged flows link

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istoica@cs.berkeley.edu8 Generalized Processor Sharing A work conserving GPS is defined as 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 al flows during [ t 1, t 2 ) -B(t) – number of backlogged flows

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9 Properties of GPS End-to-end delay bounds for guaranteed service [Parekh and Gallager 93] Fair allocation of bandwidth for best effort service [Demers et al. 89, Parekh and Gallager 92] Work-conserving for high link utilization

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istoica@cs.berkeley.edu10 Packet vs. Fluid System GPS is defined in an idealized fluid flow model -Multiple queues can be serviced simultaneously Real system are packet systems -One queue is served at any given time -Packet transmission cannot be preempted Goal -Define packet algorithms approximating the fluid system -Maintain most of the important properties

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istoica@cs.berkeley.edu11 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 Packet Approximation of Fluid System

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istoica@cs.berkeley.edu12 System Virtual Time Virtual time ( V GPS ) – service that backlogged flow with weight = 1 would receive in GPS

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istoica@cs.berkeley.edu13 Service Allocation in GPS The service received by flow i during an interval [ t 1,t 2 ), while it is backlogged is

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istoica@cs.berkeley.edu14 Virtual Time Implementation of Weighted Fair Queueing if session j backlogged in general a j k – arrival time of packet k of flow j S j k – virtual starting time of packet k of flow j F j k – virtual finishing time of packet k of flow j L j k – length of packet k of flow j

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istoica@cs.berkeley.edu15 Virtual Time Implementation of Weighted Fair Queueing Need to keep per flow instead of per packet virtual start, finish time only System virtual time is used to reset a flows virtual start time when a flow becomes backlogged again after being idle

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istoica@cs.berkeley.edu16 System Virtual Time in GPS 0412816 1/2 1/8 2*C C

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istoica@cs.berkeley.edu17 Virtual Start and Finish Times Utilize the time the packets would start S i k and finish F i k in a fluid system 0412816

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istoica@cs.berkeley.edu18 Goals in Designing Packet Fair Queueing Algorithms Improve worst-case fairness (see next): -Use Smallest Eligible virtual Finish time First (SEFF) policy -Examples: WF 2 Q, WF 2 Q+ Reduce complexity -Use simpler virtual time functions -Examples: SCFQ, SFQ, DRR, FBFQ, leap-forward Virtual Clock, WF 2 Q+ Improve resource allocation flexibility -Service Curve

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istoica@cs.berkeley.edu19 Worst-case Fair Index (WFI) Maximum discrepancy between the service received by a flow in the fluid flow system and in the packet system In WFQ, WFI = O( n ), where n is total number of backlogged flows In WF2Q, WFI = 1

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istoica@cs.berkeley.edu20 WFI example Fluid-Flow (GPS) WFQ (smallest finish time first): WFI = 2.5 WF2Q (earliest finish time first); WFI = 1

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istoica@cs.berkeley.edu21 Hierarchical Resource Sharing Resource contention/sharing at different levels Resource management policies should be set at different levels, by different entities -Resource owner -Service providers -Organizations -Applications Link Provider 1 seminar video Stat Stanford.Berkeley Provider 2 WEB 155 Mbps 50 Mbps 10 Mbps 20 Mbps 100 Mbps 55 Mbps Campus seminar audio EECS

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istoica@cs.berkeley.edu22 Hierarchical-GPS Example 41 1 111 Red session has packets backlogged at time 5 Other sessions have packets continuously backlogged 5 0 10 20 10 1 First red packet arrives at 5…and it is served at 7.5

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istoica@cs.berkeley.edu23 Packet Approximation of H-GPS Idea 1 -Select packet finishing first in H-GPS assuming there are no future arrivals -Problem: Finish order in system dependent on future arrivals Virtual time implementation wont work Idea 2 -Use a hierarchy of PFQ to approximate H-GPS 64 3 2 1 GPS 10 Packetized H-GPS H-GPS 64 3 2 1 GPS 10

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istoica@cs.berkeley.edu24 Problems with Idea 1 The order of the 4 th blue packet finish time and of the 1 st green packet finish time changes as a result of a red packet arrival Make decision here 41 1 111 5 10 1 Blue packet finish first Green packet finish first

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istoica@cs.berkeley.edu25 Hierarchical-WFQ Example A packet on the second level can miss its deadline (finish time) by an amount of time that in the worst case is proportional to WFI 41 1 111 5 10 1 First red packet arrives at 5 …but it is served at 11 ! First level packet schedule Second level packet schedule

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istoica@cs.berkeley.edu26 Hierarchical-WF2Q Example In WF2Q, all packets meet their deadlines modulo time to transmit a packet (at the line speed) at each level 41 1 111 5 10 1 First red packet arrives at 5..and it is served at 7 First level packet schedule Second level packet schedule

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istoica@cs.berkeley.edu27 WF 2 Q+ WFQ and WF 2 Q -Need to emulate fluid GPS system -High complexity WF 2 Q+ -Provide same delay bound and WFI as WF 2 Q -Lower complexity Key difference: virtual time computation - - sequence number of the packet at the head of the queue of flow i - - virtual starting time of the packet at the head of queue i -B(t) - set of packets backlogged at time t in the packet system

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istoica@cs.berkeley.edu28 Example Hierarchy

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istoica@cs.berkeley.edu29 Uncorrelated Cross Traffic Delay under H-WFQ Delay under H-WF 2 Q+ Delay under H-SFQ Delay under H-SCFQ 20ms 60ms 40ms 20ms 60ms 40ms

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istoica@cs.berkeley.edu30 Correlated Cross Traffic Delay under H-WFQ Delay under H-WF 2 Q+ Delay under H-SFQ Delay under H-SCFQ 20ms 60ms 40ms 20ms 60ms 40ms

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istoica@cs.berkeley.edu31 Why Service Curve? WFQ, WF2Q, H-WF2Q+ -Guarantee a minimum rate: N – total number of flows -A packet is served no later than its finish time in GPS (H-GPS) modulo the sum of the maximum packet transmission time at each level For better resource utilization we need to specify more sophisticated services (example to follow shortly) Solution: QoS Service curve model

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istoica@cs.berkeley.edu32 What is a Service Model? 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. external process Network element offered traffic delivered traffic (connection oriented)

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istoica@cs.berkeley.edu33 Arrival and Departure Process Network Element R in R out R in (t) = arrival process = amount of data arriving up to time t R out (t) = departure process = amount of data departing up to time t bits t delay buffer

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istoica@cs.berkeley.edu34 Traffic Envelope (Arrival Curve) Maximum amount of service that a flow can send during an interval of time t slope = max average rate b(t) = Envelope slope = peak rate t Burstiness Constraint

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istoica@cs.berkeley.edu35 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 )

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istoica@cs.berkeley.edu36 Big Picture t t slope = C t R in (t) Service curve bits R out (t)

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istoica@cs.berkeley.edu37 Delay and Buffer Bounds t S (t) = service curve E(t) = Envelope Maximum delay Maximum buffer bits

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istoica@cs.berkeley.edu38 Service Curve-based Earliest Deadline (SCED) Packet deadline – time at which the packet would be served assuming that the flow receives no more than its service curve Serve packets in the increasing order of their deadlines Properties -If sum of all service curves <= C*t -All packets will meet their deadlines modulo the transmission time of the packet of maximum length, i.e., L max /C bits Deadline of 4-th packet 1 2 3 4 t

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istoica@cs.berkeley.edu39 Linear Service Curves: Example t bits t t Arrival curves t bits tt Service curves Arrival process Deadline computation Video FTP t Video packets have to wait after ftp packets

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istoica@cs.berkeley.edu40 Non-Linear Service Curves: Example t bits t t Arrival curves t bits tt Service curves Arrival process Deadline computation t Video FTP Video packets transmitted as soon as they arrive

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istoica@cs.berkeley.edu41 Summary WF2Q+ guarantees that each packet is served no later than its finish time in GPS modulo transmission time of maximum length packet -Support hierarchical link sharing SCED guarantees that each packet meets its deadline modulo transmission time of maximum length packet -Decouple bandwidth and delay allocations Question: does SCED support hierarchical link sharing? -No (why not?) Hierarchical Fair Service Curve (H-FSC) [Stoica, Zhang & Ng 97] -Support nonlinear service curves -Support hierarchical link sharing

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Generalized Processing Sharing (GPS) Is work conserving Is a fluid model Service Guarantee –GPS discipline can provide an end-to-end bounded- delay service.

Generalized Processing Sharing (GPS) Is work conserving Is a fluid model Service Guarantee –GPS discipline can provide an end-to-end bounded- delay service.

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