Quality of Service for Flows in Ad-Hoc Networks: Overview

University of California at Berkeley

SmartNets Research Grouphttp://smartnets.eecs.berkeley.edu

Summary Distributed MAC protocols that achieve enhanced

throughput and fairness for multi-hop flows

Theoretical QoS Routing algorithms Graph model of interference

Practical QoS Routing mechanisms Suitable clustering decouples interference effects On-line measurements and distributed computation Improved admission ratios

Contributions Capacity Estimation

Clique-based Constraints Measurement Approximation

Scheduling Limitations of Local Scheduling Fair Scheduling (Impatient Backoff Algorithm) Multi-Channel MAC

Clustering Algorithms Routing

Ad-Hoc Shortest Widest Path (ASWP) Interference-aware QoS Routing (IQRouting) Measurement-based Routing

Approximating Maximal Cliques Number of maximal cliques

in CG may be exponential Want localized and

polynomial approximation

CG is an Unit Disk Graph Use geometric nature of

UDG

For each edge uv in CG Length of edge uv = duv

Output all cliques with edges duv

Football Fuv contains all cliques

Disk Duv forms a clique Curved Triangles T1uv &

T2uv form cliques

Fuv

Duv

u v

T1uv

duv

Clique-based Constraints Theorem: Assuming constant interference range, feasible

schedule exists if scaled clique constraints are satisfied on a conflict graph

Scale capacity of each link by

Used to determine the available capacity of a link

Variance in interference range Model interference range varying between [x,1] Then, need to scale the clique constraints by

Only pessimistic bounds for networks with obstructions

B a s i c A l g o r i t h m : B a n d s

i f d u v 1 / 3o u t p u t c l i q u e F u v ;

e l s e o u t p u t c l i q u e s D u v , T 1 u v , T 2 u v ; i f a l l n o d e s i n D u v , T 1 u v o r T 2 u v

w e a r e d o n e ;e l s e

o u t p u t { B u v } b y p o s i t i o n i n g b a n d a t e a c h n o d e i n F u v ;

T h e o r e m : A l l c l i q u e s i n F u vi n c l u d e d i n { B u v }

B a n d B u v m a y i n c l u d e e x t r a v e r t i c e s ( a p p r o x . p o l y . a l g o )

O r d e r o f a l g o r i t h m = O ( m 2 ) m = n u m b e r o f e d g e s i n C G = d e g r e e o f C G

N u m b e r o f c l i q u e s = O ( m )

u v

F u v

d u v

B u v

d u v u vh t = d u v

d u v

x

yB a n dB u v

> d u v

d u v

M o d i fi e d A l g o r i t h m

C o n s i d e r s h a p e s D 1u v , T 1 1

u v , T 2 1u v

o f d i m e n s i o n 1 i n s t e a d o f d u v

T h e s e f o r m c l i q u e s t h a t a r e s u p e r s e t s o f D u v , T 1 u v , T 2 u v

I f d u v 3 – 1 , e v e r y b a n d i s c o n t a i n e d i n e i t h e r T 1 1

u v o r T 2 1u v

W o r s t c a s e r u n n i n g t i m e s a m e , b u t i m p r o v e s a v e r a g e c a s e

1

d u v

T 1 u v1

D u v1 T 1 u v

1

o v e r l a p

T 2 u v1

D u v

M o d i fi c a t i o n s :i f d u v 3 - 1

c l i q u e s D 1u v , T 1 1

u v , T 2 1u v e n o u g h ;

e l s e i f a l l n o d e s i n D 1

u v , T 1 1u v , o r T 2 1

u v

w e a r e d o n e ;e l s e

u s e b a n d s { B u v } a s b e f o r e ;

Conflict Graph (CG)

QoS in ad-hoc networks In wired networks, all links

may be used simultaneously In Ad-Hoc networks,

neighboring links interfere Interference Range >

Transmission Range

Model as a Conflict Graph Link in graph is represented

by vertex in CG Edge in CG if the two links

interfere

2

31

45

A

CB

E

Dinterference

E

CD

B

A

Connectivity Graph Conflict Graph

`Cliques’ in CG Clique = Set of links that

interfere with each other Cliques are local structures Only one link in a clique may

be active at once

Prospective

Clustering

Routing

Interference-awareQoS Routing

Ad-HocShortestWidestPath

Measurement

BasedRouting

CapacityEstimation

Measurement

BasedCliqueBased

Media AccessControl/

Scheduling

802.11MultipleChannel

MAC

ImpatientBackoffAlgo.

IteratedLongestQ First

ClusterBased

Routing

OSPF

K-hop

Clustering