Energy Conservation in
wireless sensor networks
Kshitij Desai, Mayuresh Randive,
Animesh Nandanwar
Basic Design
• Sensor Network Architecture
Internet
Sink
Sensor
Network
Architecture of a Sensor Node
• Ref: Energy Conservation in Wireless Sensor Networks – a
Survey
Observations
• Communication Sub-system consumes more energy than
computation sub-system
• Energy to transmit one bit = Energy for execution 1000
.
instructions
• Radio component requires same order of energy for
reception, transmission and idle states
• Sensing sub-system might also require significant amount
of energy based on the type of sensor node.
Three Main enabling Techniques
• Duty-cycling
• Data-Driven approaches
• Mobility
Duty-cycling
• Topology Control
• Power Management
• Sleep/Wake Protocols
• On-demand, scheduled rendezvous and Async
• MAC Protocols with low Duty-cycle
• TDMA, Contention-based and hybrid
Data-driven approaches
• Data reduction
• In-Network Processing
• Data-Compression
• Data-prediction
• Stochastic, Time-series Forecasting and algorithmic
approaches
• Energy-efficient data acquisition
• Adaptive Sampling
• Hierarchical Sampling
• Model-Driven active sampling
Mobility-based approaches
• Mobile-sink
• Mobile-relay
ATPC: Adaptive Transmission
Power Control for Wireless
Sensor Networks
Main Points
• What is this paper about?
• Power saving for wireless communication
• Paper style?
• Empirical study + a little theory work
• What is the contribution?
• Study of spatial-temporal impact on communication
• Mechanism to adaptively achieve an optimal transmission power
consumption
Motivation
TP1
TP2
TP2
11
Motivation
T2
T1
TP2
T2
TP1
TP1
The minimum transmission power level
to save energy and maintain specified link quality
12
Design Goals
• Achieve energy efficiency
• Maintain Link Quality
• Reliable links
• In runtime systems, dynamic environments
• Spatial impact
• Temporal impact
13
• The minimum transmission power
Roadmap
Empirical Observation
PART 1
Data Analysis
Algorithm Design
Algorithm Evaluation
PART 2
Part 1-Transmission Power vs. Link Quality
• Link Quality Metrics
• Transmission Power Level Index (3~31)
• Experiments on Spatial Impact
• 5 pairs of motes, 3 environments
• 100 packets at each transmission power level
• RSSI/LQI/PRR measured at different distances
15
• RSSI (Received Signal Strength Indication), LQI (Link
Quality Indication), and PRR (Packet Reception Ratio)
Part 1- Investigation of Spatial Impact
-50
-50
12 ft
6 ft
-60
18 ft
12 ft
-65
24 ft
-75
18 ft
24 ft
28 ft
-70
30 ft
-75
-80
-80
-85
-85
-90
-90
-95
-95
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Transmission Power Level Index
Transmission Power Level Index
(a) RSSI measured on a grass field
-50
3 ft
12 ft
-60
18 ft
-65
24 ft
-70
(b) RSSI measured in a corridor
1.
6 ft
-55
RSSI (dbm)
RSSI (dbm)
-70
RSSI (dbm)
-55
-65
6 ft
-55
2 ft
-60
3 ft
2.
30 ft
-75
-80
-85
3.
-90
Different shapes at the same distance in
different environments
Different degree of variation in different
environments
Approximately linear
-95
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
Transmission Power Level Index
(c) RSSI measured in a parking lot
16
Investigation of Temporal Impact
• Experiment on Temporal Impact
• In brushwood where human activity is rare, over 72 hours
• 9 MicaZ motes in a line, 3 feet apart
• A group of 20 packets at each power level every hour
-75
-75
-77
0am 1st Day
-77
10am 1st Day
8am 1st Day
-79
11am 1st Day
4pm 1st Day
-81
12pm 1st Day
-83
1pm 1st Day
-85
2pm 1st Day
-81
0am 2nd Day
-83
8am 2nd Day
-85
4pm 2nd Day
-87
RSSI (dbm)
RSSI (dbm)
-79
9am 1st Day
-87
-89
-89
-91
-91
-93
-93
-95
-95
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Transmission Power Level Index
(a) RSSI measured every 8-hour
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Transmission Power Level Index
(b) RSSI measured every hour
1. Vary gradually but noticeably over time
2. Approximately parallel
17
120
120
100
100
80
80
PRR (%)
PRR (%)
Part 1- Link Quality Threshold
60
60
40
40
20
20
0
0
-95
-90
-85
-80
-75
50
-70
(a) RSSI Threshold on a grass field
60
70
80
90
100
LQI (Reading from MicaZ)
RSSI (dbm)
(b) LQI Threshold on a grass
field
Binary link quality thresholds
Slight different in different environments
18
110
Part 2- Model Design of ATPC
• Use a linear model to approximate a non-linear correlation
• rssi(tp) = a · tp +b
• Least-square
approximation
• Dynamic model
• a and b vary
from time to time
19
Part 2- ATPC
Overview
NodeID
Power Level
Control Model
2
128
0.5TP+2325
3
27
0.8TP+49
4
6
0.4TP+32
Node
3
Node
4
ATPC Table at Node 1
Notification
Node
1
Node
5
Packet with
Transmission Power
Level 12
Node
2
Transmission Range
Initialization Phase: build models from linear approximation
Runtime Tuning Phase: pairwise closed loop control
20
Part 2 – Closed Loop Control
Start
here
RSSI, LQI
and PRR
Part 2- Experiment Setup
• Current transmission power control algorithms
– A node-level non-uniform solution (Non-uniform)
– Network-level uniform solutions
» Max transmission power level (Max)
» The minimum transmission power level over nodes in a network
that allows them to reach their neighbors (Uniform)
• A 72-hour continuous experiment with MicaZ
– A spanning tree of 43 nodes, 24 leaf nodes
– Leaf nodes send 32 packets to the base every hour
22
Part 2- Experimental
Setup
(a) Weather Conditions over 72 Hours
(b) Spanning Tree Topology
(c) Experimental Site
23
Part 2- Packet Reception Ratio
1
100
0.95
90
ATPC
80
Max
70
Uniform
0.8
Non-Uniform
0.75
0.7
60
50
Link with Static
Transmission
Power
Link with ATPC
40
0.65
30
0.6
20
0.55
10
24
0.85
PRR (%)
End-to-end PRR
0.9
0
0.5
0
6
12
18
24
30
36
42
48
54
60
66
72
Tim e (hours)
(a) E2E packet reception ratio
Max ~ 100%
ATPC ~ 98.3%
Uniform ~ 98.3%
Non-Uniform ~ 58.8%
0
6
12
18
24
30
36
42
48
54
60
66
72
Tim e (hours)
(b) PRR at a chosen link
ATPC ~ constantly 100%
Static transmission power
~ vary from 0% to 100%
Part 2- Transmission Energy Consumption
0.95
ATPC
0.9
Max
0.85
Uniform
0.8
Non-Uniform
0.75
25
Relative Transmission Energy
Consumption
1
0.7
0.65
0.6
0.55
0.5
0.45
0.4
6
12
18
24
30
36
42
48
54
60
66
72
Time (hours)
Relative energy consumption
Max ~ 100%
ATPC ~ 58.3% (1% control overhead)
Uniform ~ 68.6%
Non-Uniform ~ 43.2%
Conclusions and Future Work
• Benefits of ATPC lie in three core aspects:
• ATPC maintains above 98% E2E PRR over time
• ATPC achieves significant energy savings
• 53.6% of the transmission energy of Max
• 78.8% of the transmission energy of Uniform
• ATPC accurately adjusts the transmission power
• Adapting to spatial and temporal factors
• Towards reliable and energy-efficient
routing
• Spatial reuse for concurrent transmissions
26
Questions?
Thank you very much!
27