1
Impact of Radio Irregularity on
Wireless Sensor Networks
Gang Zhou, Tian He, Sudha Krishnamurthy, John A. Stankovic
Computer Science Department,University of VirginiaJune 2004
2
Outline
Motivation, State of Art and Contributions Analyze Radio Irregularity Radio Irregularity Model (RIM) Impact on Routing and MAC Layer Solutions for Radio Irregularity Conclusion and Future Work
3
Motivation
Evidence of radio irregularity of low power wireless devices in physical environment
Need for models to regenerate radio irregularity in simulations
Need for better protocols to address irregularity in running systems
4
State of Art
Spherical radio range assumption in current research
Localization, Sensing Coverage, Topology Control Experiments Related to Radio Irregularity
Deepak Ganesan, etc., “Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks” , UCLA/CSD-TR 02-0013, 2002
Alberto Cerpa, etc., “SCALE: A Tool for Simple Connectivity Assessment in Lossy Environments”, CENS-TR 03-0021, 2003
Jerry Y. Zhao, etc., “Understanding Packet Delivery Performance in Dense Wireless Sensor Network”, ACM SenSys, 2003
Alec Woo, etc., “Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks”, ACM SenSys, 2003
DOI Concept (our previous work) Tian He, etc., “Range-Free Localization Schemes in Large Scale
Sensor Networks”, MobiCom, 2003
5
Contributions
RIM: a new radio energy model that considers irregularity
Implemented in GlomoSim Review the impact of radio irregularity on
MAC layer Routing layer
Solutions to deal with radio irregularity Symmetric Geographic Forwarding Bounded Distance Forwarding Bidirectional Flooding Learning Function RTS Broadcast High Energy Asymmetry Detection
6
Motivation, State of Art and Contributions Analyze Radio Irregularity Radio Irregularity Model (RIM) Impact on Routing Layer Impact on Routing and MAC Layer Solutions for Radio Irregularity Conclusion and Future Work
7
Radio signal properties - 1
Non-isotropic Path Loss: The radio signal from a transmitter has different path losses in different directions.
-65-64-63-62-61-60-59-58-57-56-55
0 25 50 75
Beacon SeqNo
South NorthWest East
Figure 1: Signal Strength over Time in Four Directions
8
Non-isotropic Path Loss
Figure 2: Signal Strength Values in Different Directions
-60
-58
-56
-54
-52
-50
1 48 95 142 189 236 283 330
Direction in Degree ( 10 feet)
-65
-60
-55
-50
-45
0 41 82 122 163 204 245 285 326
Direction in Degree (20 feet)
Reasons: Reflection, diffraction and scattering in environment Hardware calibration differences (non-isotropic antenna
gain)
9
Radio signal properties - 2
Continuous variation: The signal path loss varies continuously with incremental changes of the propagation direction from a transmitter.
Figure 2: Signal Strength Values in Different Directions
-60
-58
-56
-54
-52
-50
1 48 95 142 189 236 283 330
Direction in Degree ( 10 feet)
-65
-60
-55
-50
-45
0 41 82 122 163 204 245 285 326
Direction in Degree (20 feet)
10
Radio signal property - 3
Heterogeneity: Different nodes have different signal sending powers
-60
-59.5
-59
-58.5
-58
-57.5
-57
0 25 50 75
Beacon SeqNo
1.58V 1.4V1.32V 1.18V
(a) One mote with different battery status
-60-59.5
-59-58.5
-58-57.5
-57-56.5
-56-55.5
-55
0 25 50 75
Beacon SeqNo
Mote A Mote BMote C Mote D
(b) Different motes with the same battery status
Reasons: Different battery status Different hardware calibration
11
Motivation, State of Art and Contributions Contributions Analyze Radio Irregularity Radio Irregularity Model (RIM) Impact on Routing Layer Impact on Routing and MAC Layer Solutions for Radio Irregularity Conclusion and Future Work
12
RIM - DOI
Degree of Irregularity (DOI): Definition: the maximum received signal strength
percentage variation per unit degree change in the direction of radio propagation.
Account for non-isotropic path loss
Figure 4: Degree of Irregularity
13
RIM - VSP
Variance of Sending Power (VSP): Definition: the maximum percentage variance of the
signal sending power among different devices. Account for heterogeneous sending power
14
RIM – propagation formula Signal receiving power = signal sending power - path loss + fading
Signal receiving power = signal sending power – DOI adjusted path loss + fading
DOIK-K Where
onDistributi Weibull RandomNum Where
DOI) * RandomNum(1*K2 K3
DOI)*RandomNum(1 * K1 K2
DOI)*RandomNum (1* K0 K1
1 K0
3590
DOI adjusted path loss = path loss* KD
Signal receiving power = VSP adjusted signal sending power – DOI adjusted path loss + fading
VSP adjusted signal sending power =
onDistributi Normal RandomNum Where
VSP)*RandomNum (1 *power sending signal
15
Motivation, State of Art and Contributions Analyze Radio Irregularity Radio Irregularity Model (RIM) Impact on Routing and MAC Layer Solutions for Radio Irregularity Conclusion and Future Work
16
Analyze the Impact
Impact on: Path-Reversal technique Multi-Round technique Used in AODV, DSR, LAR
Source A
B Dest.RREQ
RREQ
RREP
RREP
Figure 5: Impact on Path-Reversal Technique
S DX
X
RREQ
RREP
Figure 6: Route Discovery Using Multi-Round Technique
17
Analyze the Impact
Impact on: Neighbor-Discovery
technique Used in GF, GPSR, SPEED
AC
D
Bbeacon
Xdata
beacon
data
beacon data
Figure 7: Impact on Neighbor Discovery Technique
18
Simulation Configuration
Components Setting
Simulator GloMoSim
Terrain (150m,150m)
Node Number 100
Node Placement Uniform
Payload Size 32 Bytes
Application Many-to-one CBR streams
Routing Protocol AODV, DSR, GF
MAC Protocol CSMA, 802.11 (DCF)
Radio Model RIM
Radio Bandwidth 200Kb/s
Runs 140
Confidence Intervals The 95% confidence intervals are within 0~25% of the mean
19
E2E Loss Ratio
0%
10%
20%
30%
40%
50%
60%
70%
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODVDSRGF
0%
10%
20%
30%
40%
50%
60%
70%
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODVDSRGF
Increase DOI Increase VSP
GF has rapidly increasing E2E loss ratio AODV and DSR have low E2E loss ratio
20
Average E2E Delay
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODVDSRGF
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODVDSRGF
Increase DOI Increase VSP
GF has constant E2E delay AODV and DSR have increasing E2E delay
21
# of Control Packets
0
200
400
600
800
1000
1200
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODVDSRGF
0
100
200
300
400
500
600
700
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODVDSRGF
Increase DOI Increase VSP
GF has constant # of control packets AODV and DSR have increasing # of control packets
22
Energy Consumption
0
1
2
3
4
5
6
7
8
9
0 0.002 0.004 0.006 0.008 0.01DOI-FACTOR
AODVDSRGF
0
1
2
3
4
5
6
7
8
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODVDSRGF
Increase DOI Increase VSP
GF has decreasing energy consumption AODV and DSR increasing energy consumption
23
Motivation, State of Art and Contributions Analyze Radio Irregularity Radio Irregularity Model (RIM) Impact on Routing and MAC Layer Solutions for Radio Irregularity Conclusion and Future Work
24
Solutions
Symmetric Geographic Forwarding Bounded Distance Forwarding Bidirectional Flooding Learning Function RTS Broadcast High Energy Asymmetry Detection
Symmetric Geographic Forwarding Detect and block asymmetric channels Only use symmetric channels for geographic forwarding Implementation: Add all neighbors’ IDs in beacon messages Optimization: estimate the channel quality statistically
Currently implemented in a tracking system [MobiSys 2004]
25
SGF --- E2E Loss Ratio
0%
10%
20%
30%
40%
50%
60%
70%
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODVDSRGFSGF
0%
10%
20%
30%
40%
50%
60%
70%
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODVDSRGFSGF
Increase DOI Increase VSP
SGF has constantly low E2E loss ratio
26
SGF --- Average E2E Delay
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODVDSRGFSGF
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODV DSRGF SGF
Increase DOI Increase VSP
SGF has almost constant E2E delay
27
SGF --- # of Control Packets
0
200
400
600
800
1000
1200
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODVDSRGFSGF
0
100
200
300
400
500
600
700
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODV DSRGF SGF
Increase DOI Increase VSP
SGF has the same # of control packets as that of GF
28
SGF --- Energy Consumption
0
1
2
3
4
5
6
7
8
9
0 0.002 0.004 0.006 0.008 0.01
DOI-FACTOR
AODV DSRGF SGF
0
1
2
3
4
5
6
7
8
0 0.2 0.4 0.6 0.8 1
VSP-FACTOR
AODV DSRGF SGF
Increase DOI Increase VSP
SGF has a little increasing energy consumption
29
Bounded Distance Forwarding Bounded Distance Forwarding restricts the distance over
which a node can forward a message in a single hop. An add-on rule Tested in a running system with 60 MICA2 motes
60%
65%
70%
75%
80%
85%
90%
95%
100%
8 16 24 32 40 48 100
Bounded Fowarding Distance(feet)
Figure 7: Percentage of Reporting Nodes
30
Motivation, State of Art and Contributions Analyze Radio Irregularity Radio Irregularity Model (RIM) Impact on Routing and MAC Layer Solutions for Radio Irregularity Conclusion and Future Work
31
Conclusion - 1 The first effort to bridge the gap:
between isotropic radio energy models assumed by most simulators in WSN and the real non-isotropic
radio properties
32
Conclusion - 2 Review the impact of radio irregularity on Routing
and MAC layers Radio irregularity has a greater impact on the routing layer
than on the MAC layer. Routing protocols, such as AODV and DSR, that use multi-round
discovery technique, can deal with radio irregularity, but with high overhead.
Routing protocols, such as geographic forwarding, which are based on neighbor discovery technique, are severely affected by radio irregularity.
Solutions for radio irregularity SGF has as low loss ratio as that of AODV and DSR, but much
lower control overhead and energy consumption.
33
Future work
To evaluate and further refine the RIM model Experiments in more types of environments Experiments with different types of devices and
different types of antennas Radio pattern variation with system aging and
environment changes Analyze the impact of radio irregularity on other
protocols Localization, Sensing Coverage, Topology Control
Analyze and evaluate the remaining four solutions Bidirectional Flooding Learning Function RTS Broadcast High Energy Asymmetry Detection
Recommended