KAIST
Efficient Geographic Routing in Multihop Wireless Networks
Seungjoon Lee, Bobby Bhattacharjee, Suman Banerjee
MobiHoc, 2005
Jerry
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Contents
Introduction
Overview of NADV
NADV
New link metric for geographic routing
Link cost types and estimation
Simulation and results
Conclusion
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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
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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
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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
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New link metric for geographic routing(2/3)
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
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New link metric for geographic routing(3/3)
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
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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.
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Link cost types and estimation (2/7)
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
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Link cost types and estimation (3/7)
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 ]
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Link cost types and estimation (4/7)
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
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Link cost types and estimation (5/7)
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(
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Link cost types and estimation (6/7)
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
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Link cost types and estimation (7/7)
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
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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
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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
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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
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Simulation results (2/5)
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
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Simulation results (3/5)
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
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Simulation results (4/5)
Using power consumption as link cost
[ Average power consumption with different schemes ]
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Simulation results (5/5)
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 ]
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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