quality-of-service - computer sciencecs757/slidespdf/757-15-qosintro.pdf · what is...

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© Jörg Liebeherr, 2000-2003 CS757

Quality-of-Service


Quality of Service

What is Quality-of-Service?• QoS refers to traffic control mechanisms that seek to either

differentiate performance based on application or network-operator requirements, or provide predictable or guaranteed performance to applications, sessions, or traffic aggregates.

Why is this an issue?• The default service in many packet networks is to give all

applications the same service, and not consider any service requirements to the networkThis is called a best-effort service.

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Quality of Service

Who needs Quality-of-Service?– Video and audio conferencing bounded delay and loss rate– Video and audio streaming bounded packet loss rate– Time-critical applications (real-time control) bounded delays– “valuable applications” better service than less valuable applications

How are Quality-of-Service requirements specified?• QoS parameters are

– Delay– Delay Variation (Jitter)– Throughput– Error Rate


Quality of Service

What is the granularity of QoS?– Per-flow QoS

Guarantees are specified and enforced for single end-to-end data flow

– Class-based QoSGuarantees are specified and enforced for groups of

flows

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Granularity of QoS

• Per-flow guarantees– Require per-flow reservations in the network– Require per-flow classification at routers


Granularity of QoS

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• Per-class guarantees– Bundle traffic flows with similar service requirements into “classes”– No per-flow reservations– Per-class guarantees do not immediately translate into per-flow

guarantees

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Levels of QoS guarantees

Absolute QoS guarantees• Assumes per-flow guarantees• The QoS of a flow is independent of QoS of other

flows• Objective of service: “Isolation”• Guarantees can be deterministic or statistical• Needs resource reservation mechanism


Levels of QoS guarantees

Adaptive QoS guarantees

– Adapts QoS to load conditions in the network; potentially with upper and lower bounds.

– Objective of Service: “Fairness”– Does not need resource reservation

– Needs adaptive feedback mechanism

No QoS guarantees (Best Effort)

- Objective of Service: “Sharing”

- Always works

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Components of QoS in a Network

QoSU

tilit y

Application can adapt utility--> adaptive QoS

QoS

Util

ity

Application needs

--> absolute QoS

QoS

Util

ity

Application toler-ates QoS variations--> best effort


Types of QoS guarantees

• Deterministic QoS– Service guarantees are enforced for all traffic– For example, deterministic delay guarantees have the form:

Delay of a packet from flow X < D(D is called a delay bound)

• Statistical QoS– Allows a certain fraction of traffic to violate the service

guaranteesProb [ Delay of a packet from flow X < D ] > 1 - ε

– Where ε is a small number (e.g., ε = 10-6)

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Quality of Service Network

• Traffic description: 1 Mbps throughput, 100 kB max. burst • Quality of Service parameters: 10-5 loss rate, 50 msec delay

Sender ReceiverPolicingand Shaping

Switch

AdmissionControl


Traffic Contract

• An application submits to network a reservation request for a new flow with a traffic specification and desired QoS

• Network performs admission control functions which determines if sufficient resources are available to

(a) satisfy the desired QoS of new flow(b) without violating QoS of existing flows

• If sufficient resources are available, network reserves resources for flow; Otherwise, it rejects the flow

• Network performs policing and shaping at the network entrance to ensure that application adheres to its specification

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Why is QoS Hard ?

• QoS is easy to achieve if the network over allocates resources for each flow

• Allocating bandwidth at the peak rate, yields deterministic QoS, but is very inefficient

• Challenge of QoS Networking:– Build a network that can provide QoS with the least

amount of resourcesUsing better algorithms has the same effect as adding bandwidth (or other resources)

– Problem: Complexity and scalability of QoS techniques


Multiplexing GainMultiplexing Gain

⋅<<

flow 1 for guarantees

support toneeded Resources

N

flows N for guarantees

support to needed Resources

Sources of multiplexing gain:• Traffic Conditioning (“Smoothing”)• Scheduling• Statistical Multiplexing Gain

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Why is it hard to get multiplexing gain?Why is it hard to get multiplexing gain?

MPEG-Compressed Video Trace

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0 200 400 600 800 1000

Frame number

T r a

f f I

c (

i n

5 0 b

y t

e ce l l

s)

1. Burstiness of traffic2. Stringent service guarantees

Peak rate

Mean rate


Traffic ConditioningTraffic Conditioning


0

50

100

150

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0 200 400 600 800 1000

Frame number

Traf

fic (i

n 50

byt

e ce

lls)

Traffic Conditioning

• Traffic conditioning is typically done at the network edge


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0 200 400 600 800 1000Frame number

Traf

fic (i

n 50

byt

e ce

lls)

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SchedulingScheduling

• Scheduling algorithm determines the order in which traffic is transmitted


Deterministicworst-case

Expected case Probable worst-

case

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Designing Networks for Multiplexing GainDesigning Networks for Multiplexing Gain

Peak Rate

Multiple Buckets

FCFS

Static Priority

Earliest-Deadline-First

GPS

Average Rate

Peak Rate AllocationDeterministic service

Statistical service

Scheduling

Service /Admission Control

Token Bucket

TrafficCharacterization/ Conditioning


Token BucketMultiple BucketsDeterministic service

Statistical service

Static Priority


GPS

Average Rate

Peak Rate

FCFS

Peak Rate Allocation

TrafficCharacterization/ ConditioningService /

Admission Control

Scheduling


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Peak RateToken Bucket

Peak Rate Allocation

Statistical service

FCFS

Static Priority

GPS

Average Rate

By now: The design space for determi-nistic guarantees is well understood.

Multiple BucketsDeterministic service


TrafficCharacterization/ ConditioningService /

Admission Control

Scheduling



Peak RateToken Bucket

Peak Rate AllocationDeterministic service

FCFS

Static Priority


GPS

Average Rate

Still open:Is there an elegant framework to reason about statistical guarantees?

Statistical Network Calculus

Statistical serviceMultiple Buckets

TrafficCharacterization/ Conditioning

Scheduling

Service /Admission Control


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Components of a QoS Network(with absolute per-flow guarantees)

1. At routers: Packet Classification, Packet Scheduling

2. At network entrance: Traffic conditioning

3. At routers or somewhere in the network: Admission Control

4. Between hosts and routers: Signaling


Classification and Scheduling

Routers need to be able to

1. classify arriving packets according to their QoSrequirements

Packet Classification

2. isolate traffic flows and provide requested QoS

Packet Scheduling

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Action

--------

---- ----

--------

Predicate ActionClassifier (Policy Database)


Forwarding Engine

Incoming Packet

HEADER

Packet classification is done before routing table lookup


Packet Scheduling

• Packet scheduling algorithm determines the order in which backlogged packets are transmitted on an output link

scheduler

Allocating output bandwidthControlling packet delay

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Scheduling Algorithms

• First-Come-First-Served (FCFS or FIFO)– Cannot support different QoS

• Static Priority (a.k.a. Head-of-line priority)– Mechanism: Has one FCFS queue for each priority level; always

serves the backlogged FCFS queue with highest priority– Can support delay differentiation, but tends to starve low priority traffic

• Earliest-Deadline-First – Mechanism: Assigns each packet a deadline (deadline = arrival time +

delay guarantee of flow)– Requires to maintain a sorted queue


Scheduling Algorithms

• Fair Queueing– Attempts to implement a scheduler that serves all flows

with a backlog at the same rate– Emulates a bitwise Round Robin scheduling algorithm– Not completely trivial to implement Fair Queuing in a

packet network

FIFO

Fair Queueing

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ArrivalsFlow 1Flow 2Flow 3

Time

Suppose we have QoS constraints on delay:• Flow 1: • Flow 2: • Flow 3:

Ba c

k lo g

Flow 1

Flow 2

Flow 3

Multiplexing Gain: ExampleMultiplexing Gain: Example


QoS constraints on delay:• Flow 1: • Flow 2: • Flow 3:

Flow 1

ArrivalsFlow 2Flow 3

Time

Bac

klog

Multiplexing Gain via SchedulingMultiplexing Gain via Scheduling

• Here: fixed priority scheduling

Flow 1

Flow 2

Flow 3

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• Traffic conditioning mechanisms at the network boundary need to enforce that traffic from a flow adheres to its specification

PolicingDrop traffic that violates the specificationShapingBuffer traffic at network entrance that violates specificationMarkingMark packets with a lower priority or as best effort, if the traffic specification is violated



• The most popular traffic conditioning algorithm is the leaky bucket

Token pool (Bucket) has depth b

r token/sec are added (no tokens are added if there are b tokens)

Network

A shaper buffers packets until a token becomes available A policer drops a packet if no token is available

Each packet removes a token from the pool.If pool is empty, packet cannot enter

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• Leaky bucket with peak rate enforcement has two buckets:• Size b, rate r: controls average rate• Size 1, rate P (with P > r): controls peak rate

Size = b

Network

Size = 1

r token/secP token/sec

This type of leaky bucket is used in ATM QoS and Internet QoS



• Maximum traffic that is admitted by leaky bucket over any time interval

Pack

ets

Time interval

b

Slope r

Leaky Bucket

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• Maximum traffic that is admitted by dual leaky bucket over any time interval

Pack

ets

Time interval

Slope r

Leaky Bucket

Slope P

rPb−


Admission Control

• Admission Control Conditions determine if the network can support the QoS requirements for a given set of flows

• Example: End-to-end delay must be less than delays at all nodes

1 23

d1,j d2,j d3,j

Dj = d1,j + d2,j + d3,j

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• Example: End-to-end delay must be less than a delay bound D

• Calculate smallest possible delay bound at each node: d*1,d*2 ,d*3 and reserve resources

• At receiver: – If D < d*1+d*2+d*3 , reject flow, send reject message to sender and release

resources – If D > d*1+d*2+d*3 , accept flow, commit resource reservation and notify sender

Distributed Admission Control

1 23

D < d1+d2+d3Reject

S

RDD,d1 D,d1,d2

D,d1,d2,d3

Reject

D > d1+d2+d3Accept

Accept


• Example: End-to-end delay must be less than a delay bound D

• Calculate smallest possible delay bound at each node: d*1,d*2 ,d*3 and reserve resources

• At receiver: – If D < d*1+d*2+d*3 , send reject message to sender– If D > d*1+d*2+d*3 , accept flow and reserve resources

Centralized Admission Control

1 23

D < d1+d2+d3Reject

S

RD

D > d1+d2+d3AcceptAccept

server

Reject

Reserve

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Signaling for QoS

• A network with resource reservations needs to have a control protocol which relays the reservation request:

– ATM Networks: Q.2931– IP Networks: Reservation protocol (RSVP)


RSVP Functional Diagram

Application

RSVPD

AdmissionsControl

PacketClassifier

PacketScheduler

PolicyControlD

ATA

DATA

RSVPD

PolicyControl

AdmissionsControl

PacketClassifier

PacketScheduler

DATA

RoutingProcess

Host Router

Source: Gordon Chaffee, UC Berkeley

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Resource Reservation

• Senders advertise using PATH message• Receivers reserve using RESV message

– Flowspec + filterspec + policy data– Travels upstream in reverse direction of Path message

• Merging of reservations• Sender/receiver notified of changes

Source: Gordon Chaffee, UC Berkeley

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