Efficient Geographic Routing in Multihop Wireless Networks

KAIST

Efficient Geographic Routing in Multihop Wireless Networks

Seungjoon Lee, Bobby Bhattacharjee, Suman Banerjee

MobiHoc, 2005

Jerry

22 / 21 / 21Efficient geographic routing in multihop wireless networks

Contents

Introduction

Overview of NADV

NADV

New link metric for geographic routing

Link cost types and estimation

Simulation and results

Conclusion


Introduction

Geographic routing

Location information for packet delivery

Next hop node selection based on neighborhood and destination information

No route establishment

Popular strategy for geographic routing

To the neighbor geographically closest to the destination

Route around ‘voids’ problem

No neighbor closer to the destination than the current node

wvd

y zx


Overview of NADV

NADV (normalized advance)

New link metric for geographic routing

Optimal trade-off between ‘proximity’ and ‘link cost’

Adaptive routing

General scheme for efficient routing

Support a variety of different cost types

Different routing strategies depending on system objectives, message priority or applications


New link metric for geographic routing(1/3)

ADV (advance) : background

Current node S greedily select the neighbor closest to destination T

Minimization the hop count between source and destination

Advance (ADV) of n

Amount of decrease in distance by a neighbor n

Demerit

No consideration of link cost

Use of poor quality links, unnecessarily high communication cost

)()()( nDSDnADV D(x) : distance from node x to T

Large advance Good link qualityvs



NADV (normalized advance)

Normalized advance of neighbor n

-> Expected advance per transmission

)()(

)(

)()(

nPnADV

nCost

nADVnNADV

succ

Psucc(n)

probability of success in transmitting data to n



Optimality of NADV in an idealized environment

Link costs along the found path by NADV is minimum

Assumptions

We can find a node at an arbitrary point

Link cost is an unknown increasing convex function of distance

Process

DIST : distance from source S and destination T (relatively large)

Optimal path : straight line between S and T

Sum of link costs : minimized when all links have the same distance

Optimal interval

x

x

x

ADV

CostDIST

ADV

DISTCost

HopCountLinkCostTotalCost

)()(

Cost

ADVNADV

S

T


Link cost types and estimation (1/7)

Wireless integration sublayer extension (WISE)

Three types of link cost

Packet error rate

Link delay

Energy consumption

For efficient link cost estimation

Additional control messages available

-> WISE extract relevant link cost info.

Otherwise

-> WISE exploits MAC-specific info.



Packet error rate (PER)

Four PER estimation methods for

Using probe messages

Using signal-to-noise ratio

Neighborhood monitoring

Self monitoring

)1(

)1/(1

PERADVC

ADVNADV

PERC

errorerror

error

errorNADV



PER estimation 1: Using probe messages

Link error probability

Probe message

Reception ratio from periodic message exchange

Adjusting PER depending on the data packet length

l-bit probe messages

Infer bit error rate from observed PER(l)

L-bit data frame

bp

lb

lb

lPERp

plPER/1))(1(1

)1(1)(

lLlPERLPER /))(1(1)(

[ Observed and estimated PERs for five experiments with varying distance ]



PER estimation 2: Using signal-to noise ratio (SNR)

Bit error rate – Assuming white gaussian noise and BPSK modulation

PER estimation 3: Neighborhood monitoring

Passive monitoring to infer link PERs

Node A monitor frames sent by neighbors

Using the MAC sequence number, A count frames missed from neighbor B

A infer PER of link from B to A

A needs to inform B of the PER estimation

)(5.0fN

Wperfcp

rb

function errorary complement:erfc

rate bit ontransmissi:f

power noise:N

bandwidth channel:W

power received:pr

)(P

log10rdB

NSNR



PER estimation 4: Self monitoring

Condition

Additional control messages : not possible

Modification of beacon message format : not possible

Technique

Node transmits a data frame to neighbor n

Mac-layer informs the WISE whether transmission was successful or not

F=1 (fail), F=0 (success)

PER of wireless link to neighbor n

FPERPER nn )1(



Delay

Two types of link delay

Medium time

Time spent in sending a packet over the link

WISE can easily retrieve the current value of transmission rate from the MAC layer and calculate the necessary medium time to the neighbor

Total delay

Time from the packet insertion into the interface queue until the notification of successful transmission

Queuing delay, backoff time out, contention period, retransmissions due to errors or collisions

delaydelay

C

ADVNADV



Power consumption

Assumptions

Control mechanism for transmission power adjustment to save battery

Appropriate transmission power level Ptx

WISE retrieve Ptx and calculate actual system power consumption Cpower

powerpower

C

ADVNADV


Simulation model (1/2)

EnvironmentNs-2 simulation

Node placementUniformly at random on a 1000m by 1000m square

Static source at (50, 500), destination at (50+D, 500)

Geographic routing : simulation code for GPSR

802.11 auto rate fallback ARF (1M, 2M, 5.5M, 11Mbps)

IEEE 802.11b standard for the underlying MAC layer protocol

Error modelRandom packet error model

Performance of NADV in the presence of randomness in packet errors

Error models obey SNR equations

Rivals: BlacklistingFixed threshold

Node excludes neighbors with low-quality link based on the threshold


Simulation model (2/2)

Power consumption model

Transmission power for successful reception at a receiver

Transmission power

Energy each packet forwarding consumes

C is hardware specific variable

minSd n d : distance, n: path loss exponent (2 - 6)

Smin: minimum required signal strength at receiver

txpower cpC 1

}1 ,:min{

},...,,{

min

21

LmpSdpP

pppP

mn

mtx

L

In simulation

n=4, }0.1,5.0,3.0,2.0,05.0,01.0{P


Simulation results (1/5)

Experiments with perfect estimation of link errorsNADV vs ADV

Data transmission overhead of ADV increases abruptly

NADV vs blacklistingBlacklisting : different threshold values lead to best results

NADV : adapt to the changing network

Number of retransmission

• Network bandwidth, resources

• Packet delay

• GPSR retransmit option on

• 802.11 ARF off



Experiments using proposed PER estimation techniques

Changing noise power

Use SNR induced error distribution

• Start with high noise

• After 300 sec, low noise

• After 700 sec, medium noise

• ( ) : Packet delivery ratio

• GPSR retransmission off

• 802.11 ARF off



Simulation under mobile environments

100 nodes, source and sink are fixed nodes, others are mobile

Moving rate 1m/s – 10m/s, pause time ranges from 1000s – 0s



Using power consumption as link cost

[ Average power consumption with different schemes ]



Experiments with generic cost

Link cost

Experiment scenario

Source and destination are 900meters apart

Source starts to send data packets after 10 seconds

At 30 seconds, environment of some part of the network changes

We randomly select 50% of links and increase their link costs by 50%

51,)(0.1 2 rR

drCgeneric

r : uniformly distributed random number

d : distance between two nodes

R : maximum transmission range

[ Average path quality of each scheme before and after the link cost change ]


Conclusion

NADV

New link metric for geographic routing in multihop wireless networks

Adaptive, general and useful for various link cost types

Combination of NADV and cost estimation techniques outperforms the current geographic routing schemes

NADV finds paths whose cost is close to the optimum

Efficient Geographic Routing in Multihop Wireless Networks

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