Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 1 Better-than-best-effort: QoS, IntServ, DiffServ, RSVP, RTP Shivkumar Kalyanaraman Rensselaer

Shivkumar KalyanaramanRensselaer Polytechnic Institute

1

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

Shivkumar Kalyanaraman

Rensselaer Polytechnic Institute

[email protected]

http://www.ecse.rpi.edu/Homepages/shivkuma

Based in part on slides of Ion Stoica, Jim Kurose, Srini Seshan, Srini Keshav


2

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

Overview


3

Why Better-than-Best-Effort (QoS)?

To support a wider range of applicationsReal-time, Multimedia, etc

To develop sustainable economic models and new private networking servicesCurrent flat priced models, and best-effort

services do not cut it for businesses


4

Quality of Service: What is it?

Multimedia applications: network audio and video

network provides application with level of performance needed for application to function.

QoS


5

What is QoS? “Better performance” as described by a set of

parameters or measured by a set of metrics.

Generic parameters: BandwidthDelay, Delay-jitterPacket loss rate (or loss probability)

Transport/Application-specific parameters:TimeoutsPercentage of “important” packets lost


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


7

Fundamental Problems

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

B

Scheduling DisciplineFIFO

B


8

Fundamental Problems Conservation Law

(Kleinrock): (i)Wq(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


9

QoS Big Picture: Control/Data Planes

Internetw ork or W ANW orkstationRouter

Router

RouterW orkstation

Control Plane: Signaling + Admission Control orSLA (Contracting) + Provisioning/Traffic Engineering

Data Plane: Traffic conditioning (shaping, policing, markingetc) + Traffic Classification + Scheduling, Buffer management


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)


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)


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 applicationsAssume 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


13

QOS SPECIFICATION, TRAFFIC, SERVICE

CHARACTERIZATION, BASIC MECHANISMS


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


15

Hard Real Time: Guaranteed Services

Service contractNetwork to client: guarantee a deterministic

upper bound on delay for each packet in a session

Client to network: the session does not send more than it specifies

Algorithm supportAdmission control based on worst-case

analysisPer flow classification/scheduling at routers


16

Soft Real Time: Controlled Load Service

Service contract:Network to client: similar performance as an

unloaded best-effort networkClient to network: the session does not send

more than it specifies Algorithm Support

Admission control based on measurement of aggregates

Scheduling for aggregate possible


17

Traffic and Service Characterization

To quantify a service one has two knowFlow’s traffic arrivalService provided by the router, i.e., resources

reserved at each router Examples:

Traffic characterization: token bucketService provided by router: fix rate and fix

buffer space Characterized by a service model (service

curve framework)


18

Token Bucket Characterized by three parameters (b, r, R)

b – token depthr – average arrival rateR – maximum arrival rate (e.g., R link capacity)

A bit is transmitted only when there is an available tokenWhen a bit is transmitted exactly one token is consumed

r tokens per second

b tokens

<= R bps

regulatortime

bits

b*R/(R-r)

slope R

slope r


19

Characterizing a Source by Token Bucket

Arrival curve – maximum amount of bits transmitted by time t Use token bucket to bound the arrival curve

time

bits

Arrival curve

time

bps


20

Example Arrival curve – maximum amount of bits transmitted by time t Use token bucket to bound the arrival curve

size of timeinterval

bitsArrival curve

time

bps

0 1 2 3 4 5

1

2

1 2 3 4 5

1

2

3

4

(b=1,r=1,R=2)


21

Per-hop Reservation Given b,r,R and per-hop delay d Allocate bandwidth ra and buffer space Ba such that to

guarantee d

bits

b

slope rArrival curve

d

Ba

slope ra


22

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 elementoffered traffic

delivered traffic

(connection oriented)


23

Arrival and Departure Process

Network ElementRin Rout

Rin(t) = arrival process = amount of data arriving up to time t

Rout(t) = departure process = amount of data departing up to time t

bits

t

delay

buffer


24

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”


25

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)


26

Big Picture

t t

slope = C

t

Rin(t)

Service curvebits bits

bits

Rout(t)


27

Delay and Buffer Bounds

t

S (t) = service curve

E(t) = Envelope

Maximum delay

Maximum buffer

bits


28

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


29

Mechanisms: Queuing/Scheduling

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, ...

Class C

Class B

Class A

Traffic Classes

Traffic Sources

$$$$$$

$$$

$


30

Mechanisms: Buffer Mgmt/Priority Drop

Ideas: packet marking, queue thresholds, differential dropping, buffer assignments

Drop RED and BLUE packets

Drop only BLUE packets


31

SCHEDULING


32

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


33

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


34

Scheduling Policies (more) Round Robin: scan class queues serving one from each class

that has a non-empty queue


35

Round-Robin Discussion

Advantages: protection among flows Misbehaving flows will not affect the performance

of well-behaving flowsMisbehaving 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


36

Generalized Processor Sharing(GPS) Assume a fluid model of traffic

Visit each non-empty queue in turn (RR)Serve infinitesimal from eachLeads to “max-min” fairness

GPS is un-implementable!We cannot serve infinitesimals, only packets


37

Generalized Processor Sharing A work conserving GPS is defined as

where wi – weight of flow i Wi(t1, t2) – total service received by flow i during [t1, t2) W(t1, t2) – total service allocated to all flows during [t1, t2) B(t) – number of flows backlogged

)(),(),(

)(

tBiw

dtttW

w

dtttW

tBj ji

i


38

Fair Rate Computation in GPS

Associate a weight wi with each flow i If link congested, compute f such that

Cwfr ii

i ),max(

8

6

244

2

f = 2: min(8, 2*3) = 6 min(6, 2*1) = 2 min(2, 2*1) = 2

10(w1 = 3)

(w2 = 1)

(w3 = 1)


39

Bit-by-bit Round Robin

Single flow: clock ticks when a bit is transmitted. For packet i:Pi = length, Ai = arrival time, Si = begin

transmit time, Fi = finish transmit timeFi = Si+Pi = max (Fi-1, Ai) + Pi

Multiple flows: clock ticks when a bit from all active flows is transmitted round numberCan calculate Fi for each packet if number of

flows is known at all timesThis can be complicated


40

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


41

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 Fi at any given time Variation: Weighted Fair Queuing (WFQ)


42

Approximating GPS with WFQ

Fluid GPS system service order

0 2 104 6 8

Weighted Fair Queueing select the first packet that finishes in GPS


43

FQ Example

F=10

Flow 1(arriving)

Flow 2transmitting Output

F=2

F=5

F=8

Flow 1 Flow 2 Output

F=10

Cannot preempt packetcurrently being transmitted


44

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

FQ

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

1 4 7 10 13 16 19 22 25 28 31Flow Number

Thro

ughp

ut(M

bps)

RED

0

1

2

3

4

5

6

7

8

9

10

1 4 7 10 13 16 19 22 25 28 31Flow Number

Thro

ughp

ut(M

bps)


45

System Virtual Time: V(t) Measure service, instead of time V(t) slope – rate at which every active flow receives service

C – link capacityN(t) – number of active flows in fluid system at time t

1 23

1 24

3 45

5 6Servicein fluid flow

systemtime

time

V(t)

)(

)(

tN

C

t

tV


46

System Virtual Time Virtual time (VGPS) – service that backlogged

flow with weight = 1 would receive in GPS

)(),(

),()(

tBiw

dtttWwdtttW

tBj jii

t

W

wt

V

tBj j

GPS

)(

1)()(

tBit

W

w

w

t

W

tBj j

ii

)(1

),(2

1)(

21 tBidtt

W

wwttW

t

tttBj j

ii


47

Service Allocation in GPS

The service received by flow i during an interval [t1,t2), while it is backlogged is

)(),(2

121 tBidt

t

VwttW

t

tt

GPSii

)())()((),( 1221 tBitVtVwttW GPSGPSii


48

Virtual Time Implementation of Weighted Fair Queueing

w j

kj

jj

LSF

0)0( V GPS

))(,max( kjjj aVFS

if session j backlogged

if session j un-backlogged

ajk – arrival time of packet k of flow j

Sjk – virtual starting time of packet k of flow j

Fjk – virtual finishing time of packet k of flow j

Ljk – length of packet k of flow j

kj

kj FS


49

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 flow’s virtual start time when a flow becomes backlogged again after being idle


50

System Virtual Time in GPS

0 4 128 16

1/2

1/81/81/81/8

)(tVGPS

2*C

C2*C


51

Virtual Start and Finish Times Utilize the time the packets would start Si

k and finish Fik in

a fluid system

0 4 128 16

kiFkiS

i

kik

ik

i w

LSF

)(tVGPS


52

Big Picture FQ does not eliminate congestion it just

manages the congestion You need both end-host congestion control and

router support for congestion controlend-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


53

QoS ARCHITECTURES


54

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 [t1, t2] <= g(t2 - t1) +

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

1

1 1

)(///___K

k

K

k

krPgPgdelayendtoend


55

Significance P-G Theorem shows that WFQ scheduling can

provide end-to-end delay bounds in a network of multiplexed bottlenecksWFQ provides both bandwidth and delay

guaranteesBound 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


56

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 utilizationfine grained differentiationprotection

much less scalable and robust


57

Existing Solutions

Stateful Stateless

QoS

Tenet [Ferrari & Verma ’89] IntServ [Clark et al ’91] ATM [late ’80s]

DiffServ - [Clark & Wroclawski ‘97] - [Nichols et al ’97]

Network support for congestion control

Round Robin [Nagle ’85] Fair Queueing [Demers et al ’89] Flow Random Early Drop (FRED) [Lin & Morris ’97]

DecBit [Ramkrishnan & Jain ’88] Random Early Detection (RED) [Floyd & Jacobson ’93] BLUE [Feng et al ’99] REM [Low at al ’00]


58

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


59

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


60

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).


61

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


62

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.


63

Stateful Solution: Guaranteed Services

SenderReceiver

Achieve per-flow bandwidth and delay guarantees Example: guarantee 1MBps and < 100 ms delay to a flow


64


SenderReceiver

Allocate resources - perform per-flow admission control


65


SenderReceiver

Install per-flow state


66

SenderReceiver

Challenge: maintain per-flow state consistent



67


SenderReceiver

Per-flow classification


68


SenderReceiver

Per-flow buffer management


69


SenderReceiver

• Per-flow scheduling


70

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

Buffermanagement

Scheduler

flow 1

flow 2

flow n

output interface

…

Per-flow State


71

Stateless vs. Stateful

Stateless solutions are morescalable robust

Stateful solutions provide more powerful and flexible servicesguaranteed services + high resource utilization fine grained differentiationprotection


72

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


73

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


74

Differentiated Services Model

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

IngressEdge Router

EgressEdge Router

Interior Router


75

Diffserv ArchitectureEdge router:- per-flow traffic management

- marks packets as in-profile and out-profile

Core router:

- per class TM

- buffering and scheduling

based on marking at edge

- preference given to in-profile packets- Assured Forwarding

scheduling

...

r

b

marking


76

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


77

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


78

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 lengthClass A packets leave first before packets from

class B


79

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


80

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


81

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

core nodes edge nodesedge nodes


82

The DPS Approach1. Define a reference stateful network that

implements the desired service

Reference Stateful Network

SCORE Network

2. Emulate the functionality of the reference network in a SCORE network


83

The DPS Idea Instead of having core routers maintaining per-

flow state have packets carry per-flow state

Reference Stateful Network SCORE Network


84

Dynamic Packet State (DPS)

Ingress node: compute and insert flow state in packet’s header


85


Ingress node: compute and insert flow state in packet’s header


86


Core node: process packet based on state it carries

and node’s stateupdate both packet and node’s state


87


Egress node: remove state from packet’s header


88

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

Per-hop packet service time = (packet length) / r

r r rflow(reservation = r )


89

Guaranteed Services Define reference network to implement service

control path: per-flow admission control, reserve capacity r on each link

data path: enforce ideal model, by using Jitter Virtual Clock (Jitter-VC) scheduler

Reference Stateful Network

Jitter-VC Jitter-VC Jitter-VCJitter-VC

Jitter-VCJitter-VCJitter-VC


90

Guaranteed Services Use DPS to eliminate per-flow state in core

control path: emulate per-flow admission control data path: emulate Jitter-VC by Core-Jitter

Virtual Clock (CJVC)

Reference Stateful Network SCORE Network

Jitter-VC Jitter-VC Jitter-VCJitter-VC

Jitter-VCJitter-VCJitter-VC

CJVCCJVC

CJVC

CJVC

CJVC

CJVC


91

End-to-end Adaptive Applications

Internet

End-to-end Closed-loop control

Video Coding, Error Concealment, Unequal Error Protection (UEP) Packetization, Marking, SourceBuffer Management

Congestion control

Video Coding, Error Concealment, Unequal Error Protection (UEP) Packetization, Marking, playoutBuffer Management

Congestion control


92

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


93

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


94

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


95

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:DecompressionJitter removalError correction: use redundant packets to be

used for reconstruction of original streamGUI for user control


96

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


97

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


98

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.


99

H.323 Architecture


100

Inter-domain QoS: Challenge Provide high quality service across ISPs Problem: intermediate ISPs don’t have

incentive to provide “good” servicee.g., “hot-potato” policy

ISP 1

ISP 2

ISP 3?


101

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

ISP 1

ISP 2

ISP 3

Proxy(edge)

GPoP(core)

GPoP(core)

Proxy(edge)


102

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

I E

I

EI

E

Logical FIFO

B

Closed-loop building blocks: No core upgrades, smaller QoS service spectrum


103

Closed-Loop Building Blocks for QoS

International Linkor

International Linkor


104

Edge-based QoS building blocks

New: Closed-loop control !Policy/Bandwidth Broker

I E

I

EI

E

Logical FIFO

B


105

Closed-loop QoS Building Blocks

FIFO

B

Loops: differentiate service on an RTT-by-RTT basis using purely edge-based policy configuration.

B

Priority/WFQ

Scheduler: differentiates service on a packet-by-packet basis


106

Recall: Accumulation-based CC Schemes!

1 j j+1 J

μij Λi,j+1

dj

fi

Λiμi

… …

106time

)(1f

ii dtq )(

1

J

jkkij dtq

)(tqiJ

1 j j+1 J

jd 1Jd

),( tdtI fii

)(tai

)( ttai

),( ttOi

fid

t


107

Recall: Accumulation-based CC Schemes!

1 j j+1 J

μij Λi,j+1

dj

fi

Λiμi

… …

107time

)(1f

ii dtq )(

1

J

jkkij dtq

)(tqiJ

1 j j+1 J

jd 1Jd

),( tdtI fii

)(tai

)( ttai

),( ttOi

fid

t


108

Recall: Accln-based Control Policy

1 j j+1 J

μij Λi,j+1

dj

fi

Λiμi

0)( ii ta

108

control objective : keep if , no way to probe increase of available

bandwidth;0)( tai

ttttdtttarec

thentaif

thentaif

if

iii

iii

iii

)],(),([),(:

)(

)(

control algorithm :


109

Recall: “Monaco” CC Scheme

109

congestion estimation:out-of-band and in-band control packets

congestion response: if qm < α, cwnd(k+1) = cwnd(k) + 1;

if qm > β, cwnd(k+1) = cwnd(k) – 1; [ 1 = α < β = 3 ]


110

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

110


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Closed-Loop QoS: Bandwidth Assurances

Flow 1 with 4 Mbps assured + 3 Mbps best effort

Flow 2 with 3 Mbps best effort


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QoS: an application-level approach

sophisticated services in application• architecturally “above” network core• open services: let 1000 flowers bloom

simple, fast, diffserv network


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QoS: an application-level approach

Application-level infrastructure• accommodate network-level service• additional tailoring of user services


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BrowsersBrowsers

Web ServersWeb Servers

RoutersRouters

NetworksNetworks

Content Delivery Motivation: congestion


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• Reduces load on server• Avoids network congestion

BrowsersBrowsers

Web ServerWeb Server

ReplicatedReplicatedcontentcontent

RouterRouter Content SourceContent SourceContent SinkContent Sink

Content Delivery: idea


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Request Routing(RR)

Distribution System

Surrogate

Client

Origin

CDN: Architectural Layout

Publisher informs RR of Content Availability. Content Pushed to Distribution System. Client Requests Content, Requested redirected to RR. RR finds the most suitable Surrogate Surrogate services client request.

1

2

3

4

5

6


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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

Documents

Shivkumar Kalyanaraman Rensselaer Polytechnic Institute 1 Better-than-best-effort: QoS, IntServ, DiffServ, RSVP, RTP Shivkumar Kalyanaraman Rensselaer