WPMC 2003 Yokosuka, Kanagawa (Japan) 21-22 October 2003 Department of Information Engineering...

WPMC 2003 Yokosuka, Kanagawa (Japan) 21-22 October 2003

Department of Information EngineeringUniversity of Padova, ITALY

On Providing Soft-QoS in On Providing Soft-QoS in

Wireless Ad-Hoc NetworksWireless Ad-Hoc Networks

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On Providing Soft-QoS in On Providing Soft-QoS in

Wireless Ad-Hoc NetworksWireless Ad-Hoc Networks

{andrea.zanella, daniele.miorandi, silvano.pupolin}@dei.unipd.it

Andrea Zanella, Daniele Miorandi, Silvano Pupolin, Paolo Raimondi

WPMC 2003, 21-22 October 2003

Special Interest Group on NEtworking & Telecommunications


Motivations

Ad-hoc networks are a valuable solution to

Extend in a multi-hop fashion the radio access to wired networks

Interconnect wireless nodes without any fixed network structure

In these contexts, providing QoS is a key issue

audio/video streaming

interactive games

multimedia

A possible QoS support method

QoS-routing & Call-Admission-Control (CAC) mechanisms

Constrained Shortest Path Routing Problem (NP-complete)

MAC-layer Resource Reservation (MRR) and scheduling strategies


Hard & Soft QoS

Widely used in wired

networks

Integrated Services: flow

based (RSVP)

Differentiated Services:

class based

Suitable for wireless

networks

Applications may work even

if, for short periods of time,

QoS requirements are not

satisfied

Deals with limited bandwidth

and radio channel

Hard-QoS Soft-QoS


Aim of the study Reference network scenario

Low-profileLow-profile multi-hop wireless networks Intermediate nodes capable of basic functionalities

• Routing – Link monitoring – Basic computation

Border nodes capable of rather complex functionalities

• Call Admission Control (CAC) – MAC layer Resource Reservation (MRR)

Goal Providing Soft-QoSSoft-QoS support over low-profile multi-hop networks

Define Soft QoSSoft QoS parameters

Define distributed statistical CACdistributed statistical CAC

Define statistical MAC-layer Resource Reservation (MRR) mechanismstatistical MAC-layer Resource Reservation (MRR) mechanism

Modify AODVAODV in order to support Soft-QoS routing


What’s Soft-QoS?

Soft-QoS definitionSoft-QoS definition


QoS parameters required per link

Minimum peak band: Br

End-to-End Delay: Dr

Soft QoS parameter: Target Satisfaction indexTarget Satisfaction index

r = percentage of pcks expected to satisfy QoS

constrains

r = 1 hard QoS (or “wealthywealthy” clients)

r = 0 pure best-effort (or “poorpoor” clients)

Soft-QoS parameters


Call Admission Control

Distributed CAC Distributed CAC mechanism mechanism


Path Service Levels

Path: P = (p1,…, pN) Service levels:

Path Bandwidth: minimum available bandwidth along the path

Path Delay: total delay introduced by the path

Bandwidth bpj and delay dpj of each link are assumed to be

(independent) random variables BP & Dp are random

variables!

}{minj

jp

PpP bB

Pp

pP

j

jdD


Call Admission Control Path is feasible if

Bandwidth constrained requests

Delay constrained requests

However, this would require the collection of the complete statistics of link bandwidth and link delay…

rrP BB Pr

rrP DD Pr


Gaussian approx But when statistics are tough to be determined… we may (always?) resort

to the Gaussian approximation!Gaussian approximation!

Statistics are univocally determined by mean and standard deviation values of

link delay and available bandwidth

Such values can be easily determined by each intermediate node

QoS routing algorithm collects and delivers such statistics to the destination node

Destination node performs CAC in a straightforward manner:

Bandwidth constrained requests

Delay constrained requests

rPp b

br

j jp

jpmB

Q

rD

Dr

P

PmD

Q

1


MRR

Statistical MAC-layer Statistical MAC-layer Resource ReservationResource Reservation


Once a connection is accepted, resources should be reserved…

To avoid complex static reservation mechanisms and flow

differentiation we resort to statistical resource reservation:

Each node processes all the packets in the same way

Packets of different flows get the same service from the same link

For each link, nodes compute the Resource Bounds, i.e., the minimal

residual resources that should be guaranteed to preserve QoS levels of

accepted connections that go through that link

Resource Bounds


Example of Bandwidth bound

Bandwidth B

P(b

j > B

)

Target Satisfaction Index r

Required Path Bandwidth Br

Actual Sat. Index

Bandwidth Bound


r

jp

Pp b

br

b

brb

k

k kp

kp

j

j

j

mBQ

mBQm

ˆ such that ˆ

j

j

jjb

brrbrb

mBQQBm

ˆ

ˆ 1

Bandwidth Bounds

Bandwidth-constrained requests


Delay Bounds

Delay-constrained requests

Extra-delay margin is computed for the entire path

Each link along the path is assigned a fraction of the extra delay time inversely proportional to the average link delay

ˆ1ˆ 1 QDmPP DrD

jj

k

j

jj DD

Pkd

ddd mm

m

mmm

ˆ1

1ˆ

rD

DrD

P

P

P

mDQm

ˆ1 such that ˆ


Maximum Sustainable traffic

The tightest resource margins of the links along the path

are made available at the source

The source derives the maximum sustainable traffic rate,

i.e., the maximum traffic that may be injected into the

network without violating the QoS agreements of the

connections already established


How to create a path

Soft-QoS routing Soft-QoS routing algorithmalgorithm


Path creation & maintenance Soft-QoS routing is largely inspired to AODV

Each Route Request (RREQ) packet gathers statistical information on the minimum bandwidth and maximum delay along that portion of the path

RREQ is propagated only whether bandwidth request is satisfied

The destination node back propagates a Route Reply (RREP) packet along the selected path

RREP acquaints intermediate nodes with new resource bounds and updates maximum sustainable traffic rate limit

Source node is required to respect the maximum sustainable traffic rate limit or to refuse the connection


Simulation Results

Simulation of Soft-QoS Simulation of Soft-QoS routing algorithmrouting algorithm


Simulation Scenario

Bluetooth Scatternet Round Robin Polling

Gateways spend 50 slots in each piconet

Poisson packets arrival process Mixed packet formats with average length of 1500 bits

Delay-constrained requests


Gaussian Approximation Local slave-to-slave connections

in each piconet Data rate=9.6 Kbit/s 1 hop

6 hops

Gaussian approx is fairly closefairly close to empirical delay CDF

Gap increases for long-distance and high traffic connection


Simulation setup Target connection c1

Dr = 50 ms

r = 0.2 r = 20 kbit/s

Target connection c2

Dr = 200 ms

r = 0.9 r = 30 kbit/s

Target connection c3

Dr = 200 ms

r = 0.9 r = 20 kbit/s

Target connection c4 Dr = 50 ms r = 0.2 r = 60 kbit/s

Transversal connections Starting after 20 s, last for 10 s On average 1 request/s Random source, destination & QoS

requests Rate: 520 kbit/s


Satisfaction & Delay dynamics Satisfaction Delay


Conclusions We have proposed a basic Soft QoS routing algorithm for low-profile

ad hoc networks

Provides Soft-QoS guarantees

Requires

basic nodes’ functionalities

statistical link state monitoring (mean and standard deviation)

Does not require

service differentiation

static resource reservation

Drawbacks

Lower resource utilization

Higher rate of connection request rejection



On Providing Soft-QoS in Wireless Ad-Hoc NetworksOn Providing Soft-QoS in Wireless Ad-Hoc NetworksAndrea Zanella, Daniele Miorandi, Silvano Pupolin, Paolo Raimondi

Questions?


Extra Slides…

Spare SlidesSpare Slides


Statistical Resource Reservation

Bandwidth-constrained

Delay-constrained Extra-delay margin given to

each link along the path is inversely proportional to the mean link delay

Resource bounds Minimal residual resources that should be guaranteed

to preserve QoS levels of accepted connections

j

j

jjb

brrbrb

mBQQBm

ˆ

ˆ 1

ˆ1ˆ 1 QDmPP DrD

jj

k

j

jj DD

Pkd

ddd mm

m

mmm

ˆ1

1ˆ

Actual SatisfactionResource bounds

WPMC 2003 Yokosuka, Kanagawa (Japan) 21-22 October 2003 Department of Information Engineering...

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