Architecture & Protocols for Supporting Routing & QoS in MANET

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Architecture & Protocols for Supporting Routing &

QoS in MANET

Navid NIKAEIN

http://www.eurecom.fr/~nikaeinn

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Outline Introduction Motivation Topology Management Route Determination Quality of Service Support Architecture Conclusion and Open Issues

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Issues in MANET

Mobile ad hoc networks: Wireless broadcasting collision Mobility time-varying resources link Failure Lack of infrastructure fully-distributed

Complex Small devices limited resources multihop

routing

Topology Management, Routing, and QoS

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Topology of MANET

B

A

S E

F

H

J

D

C

G

IK

Z

Y

Represents a node that has received packet P

Represents that connected nodes are within each other’s transmission range

M

N

L

5

Motivation

B

A

S E

F

H

J

D

C

G

IK

Represents a node that receives packet P forthe first time

Represents transmission of packet P

Z

YBroadcast transmission

M

N

L

6

Motivation

B

A

S E

F

H

J

D

C

G

IK

Z

Y

M

N

L

7

Motivation

B

A

S E

F

H

J

D

C

G

IK

Generate redundant and unnecessary information

Z

Y

M

N

L

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Motivation

B

A

S E

F

H

J

D

C

G

IK

Z

Y

M

Transmissions may collide Packet P may not be delivered to node D at all, despite the use of flooding

N

L

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Motivation

B

A

S E

F

H

J

D

C

G

IK

Z

Y

M

N

L

Flooding generates:• Redundant and unnecessary information• Collision

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Related Work-Topology Management

Topology Management

Power Control Clustering

Non-deterministic Deterministic

Pb. Minimum dominating setNP-hard

• Core-extraction &• Spanning-tree algorithms

• DDR• TEMPOe.g. Lowest ID, Max Degree

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Topology Management DDR- Distributed Dynamic Routing

Algorithm [2,3] Intuition Preferred neighbor election Forest Construction Zone Partitioning

Simulation Model Performance Results Summary

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Intuition

Network Topology

Forest

TREE TREE …. TREE

ZONE ZONE …. ZONETime

BEACON

BEACON

Criteria

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Preferred Neighbor Election

Each node selects a neighbor, called preferred neighbor, that has the maximum degree of connectivity

If identical degrees, select the one with the higher ID

a

b

e

f

c

dg

h

2

4

2

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5

3

1

PNx={y | yNx label(y) = Max(deg(Nx) | NID) }

a

b

e

f

c

dg

h4

2

43

5

3

1

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Forest Construction

Theorem: Connecting each node to its preferred neighbor yields to a forest [2]

Mechanism: Beaconing

a

b

e

f

c

dg

h

Forest limits the number of forwarding nodes, which reduces the redundant and unnecessary information as well as the probability of collision

a

b

e

f

c

dg

h

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Zone PartitioningZone TreeMaintained Proactively

a

b

f

c

s

y

k

d

t

x

g

v

w

z

h

u

ei n

a

b

f

c

s

y

kd

t

x

g

v

w

z

h

u

ei n

DDR

z1

z2

z3 Zones : Improves delay performance Contributes in protocol scalability

Connected Dominating Set

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Criteria for FC [4]:Quality of Connectivity (QoC) Buffer level b unallocated buffer

Stability level s ||

||)(

10

10

tt

tt

NN

NNxs

QoC = b + s

PNx={y | yNx label(y) = Max(QoC(Nx) | NID) }

The PNs belong to the set of high quality nodes

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Protocol Model To study the effect of the proposed

topology management on routing performance ?

Hybrid Ad Hoc Routing Protocol (HARP) [5] Discover the shortest path Establish forward and reverse path

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Simulation Model [Johansson, Perkins, Broach]

Traffic model: CBR 512 byte/packet 4 packets/second Source 10, 20, 30

Performance Metrics: Packet delivery fraction Avg. E2E delay Routing overhead

Movement model: Random way point [Yoon] 50 nodes 1500mx300m 0-20 m/s (or 1-20m/s) 900 simulated seconds Pause time=0, 30, 60, 150, 300,

600, 900 10 scenarios for each pause time

Beaconing: 10 s QoC = 2 s + b

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Packet Delivery Fraction

10 sources 20 sources 30 sources

Simple routing has a slightly better PDF in low traffic load Routing+TM outperforms simple routing up to 20% as the traffic

load increases

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Avg. E2E Delay Routing +TM significantly improves the delay performance up to 200ms

as the network conditions become stressful Shortest path is not enough


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Routing Overhead (pkt)

Simple Routing outperforms Routing+TM in low/medium traffic load Most of the packets produced by Routing+TM are the beacons


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Routing Overhead (bytes)


Simple Routing outperforms Routing+TM in low/medium traffic load

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Summary

Overall Performance

Low traffic load

Medium traffic load

High traffic load

Low MobilityFlat Routing

SimilarRouting +TM

Medium Mobility

Flat Routing

Routing +TM

Routing +TM

High Mobility Similar

Routing +TM

Routing +TM

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Motivation for Route Selection

The effect of mobility rate and traffic load on DELAY Issue: load balancing Adjusting the weight of QoC solves the problem of load balancing

within a zone


Load Balancing

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Routing Issues

Dilemma at a node:“Do I keep track of routes to all destinations, or

instead keep track of only those that are of immediate interest?”

Three strategies: Proactive: keep track of all routes. Reactive: only those routes of immediate interest. Hybrid: partial proactive / partial reactive.

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Related Work-RoutingAd Hoc Routing

Topology-based Position-based

Proactive Reactive Hybrid

OLSRTBRPFDSDVWRPCGSRFSH-HSRLANMAR

Proactive Reactive Hybrid

DSRAODVRDMARABRSSRTORA

ZHLSZRPCBRPHARP

DREAM LAR TerminodesGLSALM

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Route Determination [5,6] HARP- Hybrid Ad Hoc Routing Protocol [5,6]

Intra-zone and Inter-zone routing Relative distance estimation [Aggelou,

Tafazolli] Quality of service support

Performance Results [Osafune] Summary

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HARP: Hybrid Routing

a

b

f

c

s

y

kd

t

x

g

v

w

z

h

u

ei n

z1

z2

z3

Zone abstraction Z1

Z3

Z2

Intra-zone RoutingInter-zone Routing

mr

z4

Z4

src zone

dst zone

Shortcut intra-zone routing

- Zone level routing

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Mechanisms to Achieve Load Balancing Inter-zone routing: route selection is done at the

destination Load balancing requires:

A set of route candidates A set of route metrics

Issues: Congestion Single route metric

Proposed mechanisms : Relative distance estimation Quality of service metrics

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Relative Distance Estimation

SRC DST

SrcOffset

DstOffset

RD_Offset

d x R

…

Offset= mobility x elapsed time

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Relative Distance Estimation

SRC DST

SrcOffset

Path_offset

RD_Offset

d x R

…

Offset= mobility x elapsed time

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Query Localization Technique

dst

d=1

d=2

d=3

d=k

src

x

x

if (rd(x,dst)>rd(src,d))Drop PREQ;

else if (rd(x,dst)<TTL)TTL=rd(x,dst);

…

PREQPREQ

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Quality of Service Support [7]

2nd Class

3rd Class

Delay

Throughput

QoSService

Best-Effort

1st Class h.(r-b)/c

QoC

c/(2h.(r-b))

1/s

Legend

h : hop count

r : buffer size

b : buffer occupancy

c : nodes’ throughput

s : stability

Application QoS Network QoC

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Simulation Model [Johansson, Perkins, Broach]

Traffic model: CBR 512 byte/packet 4 packets/second Source 10, 20, 30

Performance Metrics: Packet delivery

fraction Avg. E2E delay Routing overhead

Movement model: Random way point [Yoon] 50 nodes 1500mx300m 0-20 m/s (or 1-20m/s) 900 simulated seconds Pause time=0, 30, 60, 150,

300, 600, 900 10 scenarios for each pause

time

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The effect of mobility and traffic load is not uniform Congestion stems from the lack of load balancing in the protocols

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Avg. E2E Delay


The effect of traffic load and mobility on the delay performance is non-uniform Load balancing :

weight of QoCRelative distance estimation

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Avg. E2E Delay


Delay performance has significant improved QoS metrics is the key factor for load balancing effect

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QoS metrics has no significant effect on PDF Route discovery and route maintenance are the key factors for improving PDF Deal with Traffic load/pattern and mobility model/rate

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Summary

Overall Performance

Low traffic load

Medium traffic load

High traffic load

Low MobilityHARP +TM

HARP +TM

HARP +TM

Medium Mobility

HARP +TM

SimilarHARP +TM

High Mobility

HARP +TM

SimilarHARP +TM

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Architecture

Application

HARP

DDR

Network

Topology Management

With respect to Quality of Network

Route Determination

With respect to Application requirements

AN ARCHITECTURE THAT SEPARATES [1]:

QoS Classes

QoS:Delay TPut BE

Network QualityQoC:

Power, bufferStability

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Conclusion

Topology management improves routingLoad balancing HARP QoS metrics and RDE DDR QoC metrics

Control flooding overhead Forest redundancy & collision Relative distance estimation scope

Scalability and delay performance zone abstraction

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ConclusionRouting requires: Adaptive topology management Load balancing Congestion avoidance mechanisms Neighboring information

Factors affecting routing performance Network size, mobility rate and model, traffic

load and pattern, network density

Traffic locality vs. network size

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Future Work

Optimal criteria of forest Construction Introduce an adaptive routing mechanisms Effect of the factors affecting routing

performance

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Publications[1] N. Nikaein and C. Bonnet, “An Architecture for Improving

Routing and Network Performance in Mobile Ad Hoc Network”, Kluwer/ACM MONET, 2003.

[2] N. Nikaein, H. Labiod, and C. Bonnet, “DDR-- Distributed Dunamic Routing Algorithm for Mobile Ad Hoc Networks”, MobiHoc, 2000.

[3] N. Nikaein, S. Wu, C. Bonnet and H. Labiod, “Designing Routing Protocol for Mobile Ad Hoc Networks”, DNAC, 2000.

[4] N. Nikaein and C. Bonnet, “ Improving Routing and Network Performance in MANET using Quality of Nodes”, WiOpt, 2003

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Publications[5] Navid Nikaein, C. Bonnet and Neda Nikaein, “HARP- Hybrid

Ad Hoc Routing Protocol ”, IST, 2001.[6] Navid Nikaein, C. Bonnet, N. Akhtar and R. Tafazolli, “HARP-

v2 Hybrid Ad Hoc Routing Protocol ”, To be submitted, 2003.[7] N. Nikaein and C. Bonnet, “A Glance at Quality of Service

models in Mobile Ad Hoc Networks”,DNAC, 2002.[8] N. Nikaein, C. Bonnet, Y. Moret and I. A. Rai, “LQoS- Layered

Quality of Service Model for Routing in Mobile Ad Hoc Networks”, SCI, 2002.

[9] N. Nikaein and C. Bonnet, “ALM-- Adaptive Location Management Model Incorporating Fuzzy Logic For Mobile Ad Hoc Networks ”, Med-Hoc-Net, 2002.

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References[Wu] DDR-Based Multicast Protocol with Dynamic

Core (DMPDC), PFHSN 2002, Eurecom Institut.[Osafune] Performance Comparison of Ad Hoc

Network Routing Protocol, IEICE 2002, Hitachi Co.[Rastogi] LQoS support for reactive ad hoc routing

protocol, Tech. Report, Indian institute of Technology.

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The effect of mobility rate and traffic load on PDF Fluctuation Congestion

CongestionFluctuation Fluctuation

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Routing Overhead (pkt)


Reaction to mobility (main cause of link failure) Caching (DSR), route request (AODV), periodical link state (OLSR), and

beaconing and PREQ (HARP+TM)

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Routing Overhead (bytes)


Reaction to mobility (main cause of link failure) Caching (DSR), route request (AODV), beaconing and PREQ (HARP+TM)

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Forest Construction A forest is constructed by connecting each node

to its preferred neighbor and vice versa.

Node k:

PN = f then B = (ZID, k, 4, 1, f)

Node f:

PN = y then B = (ZID, f, 5, 1, y)

Periodical Beacon

INTRA-ZONE TABLE OF NODES k AND f

NID Learned_PN

f

NID Learned_PN

y

k

a

b

f

c

s

y

k

d

t

xc

g

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Intra-Zone Clustering

Node k:

Learned_PN = c: d

B = (ZID, k, 4, 0, Learned_PN )

Learned_PN = a: b: q: y B = (ZID, k, 4, 0, Learned_PN )

Node f: Learned_PN = a: b: q: y: k

B = (ZID, f, 5, 0, Learned_PN )

Learned_PN = c: d: x: t

B = (ZID, f, 5, 0, Learned_PN )

NID Learned_PN

f a, b, q, y, t, x

c -

d -

NID Learned_PN

y x, t

k c, d

b, a, q -

INTRA-ZONE TABLE OF NODES k AND f

a

b

f

c

s

y

k

d

t

xc

g

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Inter-Zone Clustering Either a node can succeed to add some

nodes to its intra-zone table. Otherwise, it puts the remaining nodes in

its inter-zone table.

NID NZID Z_Stability

r z4 ++

g z5 ++

INTER-ZONE TABLE OF NODE d

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Zone Naming Select q highest ID # in intra-zone table, where

Compute a hash function on each selected ID #

separately. Concatenate all the hashed ID #.

Node k (for n=12 & d=3) :

q = 4 selected nodes: y, x, t, q

h(y)|h(x)|h(t)|h(q)

Z2= y’x’t’q’

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Correctness Theorem: For any graph G (i.e. networks

topology), let G’ be the graph obtained by connecting each node to its PN. Then G’ is a forest.

Label(x) = Max {deg(w)|NID} wPNx

deg(xi-2) deg(xi), then xi PNxi-1 .

deg(xi-2) = deg(xi) &

NID(xi-2) NID(xi) .

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Problem Definition ?

Trade-off between routing overhead and delay while maximizing network utilization

Trade-off between load balancing and resource conservation

Separation between topology management and route determination

What are the design elements of routing and how they must interact ?

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Zone Behaviors

As the number of zone increases, the overhead within a zone decreases but the overhead between zones increases

Whatever the network density is, the zone diameter is bounded to 8 What is the optimal number of zones to achieve the minimum overall

overhead ? Mopt<N

Number of Zones Size of Zones

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Zone Behaviors

Whatever the network density is, the zone diameter is bounded to 8

The average ratio of tree-path to shortest path is no longer than 2 Low Complexity O(N)

Zone Diameter Tree Path / Shortest Path

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Stability Level Node mobility a basic characteristic of ad

hoc networks. A point of difference from wired networks. Critical to capture this node mobility in the

routing protocol in order to determine stable, reliable routes.

We propose:

||

||)(

10

10

tt

tt

NN

NNxstab

Nto: neighbors at time to.

Nt1: neighbors at time t1.

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Stability Level

0 stab(x) 1 stab (x) = 1 high stability, stab (x) = 0 low stability

Numerator: nodes that have remained in the neighborhood of x.

High stability if none (few) of its neighbors change, low stability if many (all) of its neighbors change.

||

||)(

10

10

tt

tt

NN

NNxstab

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Stability Example:

Stability also reflects connectivity. A large degree node, in general, more stable.

t0 t1

3/4

0

1/2

1

1

1

1

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A path of lower hop count has higher delay, because of high buffering delays.

The other path of a possibly higher hop count, but lower delay. (also load balancing).

Example

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Service differentiation

Outgoing traffic

Class I

Class II

Class III

60%

30%

10%

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Status Concept A node broadcasts is QoS state itself. This QoS state reflects node’s ability to

act as a router. If selfish, then ceases to act as a router, doesn’t take part in routing protocol.

Since propagated by the node itself, the possibility of lying. (malicious behavior) pretend to be in selfish mode, to avoid being

chosen for forwarding.

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Status Concept A selfish node does not serve the network

(does not route), hence, fair that it receives poor services from the network.

Status: the fraction of time a node has been in unselfish mode to the network.

The status of node y at node x:

][

][][

yN

yNyR u Nu [y] : number of y’s beacons in unselfish mode.

N [y] : total number of y’s beacons received.

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Status Concept How to prevent malicious behavior? Give a status to each node, and give

incentive to a node to act as a router. If a node acts as a router, then it is not in

selfish mode. Prefer packets generated by unselfish

nodes while routing. Hence, a node that has remained selfish,

receives poor services from the network.

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Quality of Service Definition To provide a set of service requirements

to the applications while Routing through the network, e.g. end-to-end delay.

Even Internet today, with high-speed high-quality fixed communication links, is unable to deliver guaranteed end-to-end services.

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QoS Routing Issues

State of communication path should be considered in QoS routing: Resource availability and its stability

Cause longer path than shortest path

Trade-off between shortest path and optimal path

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Assumption Fully symmetric environment

All nodes have identical capabilities Capabilities:

Transmission range, Battery life, processing capacity, buffer

capacity Each node periodically sends a Beacon All nodes participate in protocol operation

and packet forwarding [Michardi, Molva, Crowcroft]

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Motivation

The low-capacity time-varying resources make maintaining accurate link state and topology information very difficult

Even Internet today, with high-speed high-quality fixed communication links, is unable to deliver guaranteed end-to-end service

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Quality of Service Definition To provide a set of service requirements

to the applications while Routing through the network e.g. end-to-end delay

Even Internet today, with high-speed high-quality fixed communication links, is unable to deliver guaranteed end-to-end services.

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Related Work- Quality of Service

Two examples in the wired Network: IntServ: per-flow end-to-end guarantee DiffServ: Per-class service differentiation

An example in Manet: FQMM: Flexible QoS Model for Manet

IntServ is used for high priority classes DiffServ is used for low priority classes

They require accurate link state and topology information

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DiffServ & IntServ & FQMM

Require accurate link state and topology information

The low-capacity time-varying resources make maintaining accurate link state and topology information very difficult

Quality of service that an application requires depends strictly to the quality of network

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Network Metrics

Hop count resource conservation

Buffer Level Stability Level

Load balancing

Trade-off between load balancing & resource conservation Compute during path discovery using concave function Reflect the quality of the communication paths Map this quality to application metrics

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Conclusion-Architecture

Routing

Topology management Route determination

Quality of connectivity (QoC) Quality of Service (QoS)

Pro-Network Pro-Application

Documents

Architecture & Protocols for Supporting Routing & QoS in MANET