Power Consumption
Optimization for Energy
Harvesting WSNs
JAIST – 2012 JUL 25
1
Content

Introduction

Energy conservation
 Topology
 Power
control
management

Harvesting energy management

Summary
2
Application driven
3
Applications

Water quality monitoring

Local weather prediction for rubber farmer

Automation in orchid green-house

Toxic chemical monitoring in textile factory

Automatic control street lighting

Smart energy
4
Problems
Security
MAC protocol
Network management
Dissemination
Energy management
Data collection
Operation system
Fault tolerance
Localization
Programming modal
Routing protocol
Timing synchronization
The Next Decade of Sensor Networking - Matt
5 Welsh
Goal

Propose a WSN
 Harvest
 Have
ambient energy
infinite life-time in theory

Simulate

Implement and Verify (considering)
6
Content

Introduction

Energy conservation
 Topology
 Power
control
management

Harvesting energy

Summary
7
Energy Conservation in Wireless Sensor Networks: a Survey
8
Content

Introduction

Energy conservation
 Topology
 Power
control
management

Harvesting energy prediction

Summary
9
Geographical Adaptive Fidelity
 Know
nodes’ location
 Divided
into virtual groups
All
nodes of group A can communicate with all
nodes in group B
 One
node in group active
10
SPAN

Similar with GAF

Not need location information

Send HELLO periodically

Decide to become coordinator
 When

two neighbors cannot communicate
Delay and send HELLO to announce
 Low
energy delay longer
11
Content

Introduction

Energy conservation
 Topology
 Power
control
management

Harvesting energy prediction

Summary
12
Power management (PM)
MCU
Harvesting
energy
Power
management
control
RF
tranceiver
Sensor
Power-buffer
13
Power management

ON/OFF
t sleep Psleep ttran Ptran
(t sleep ttran ) Pon
14
Dynamic power management

Dynamic voltage scaling

Dynamic frequency scaling

Still open research for WSNs
Er
Vt
CV0 2Ts f op r
V0
r
2
Vt
r
V0
r
2
2
15
Sleep/Wakeup

On-demand
 Only
active when need communicate
 Require two communication channels

Scheduled
 Fully
synchronized wakeup
 Staggered wakeup

Asynchronous
 Independent
 Exchange
information
 Overlap wakeup time
16
Power-aware MAC protocols

TDMA-based
 Bluetooth
 LEACH
 TRAMA
 FLAMA
 LMAC
 AL-LMAC
17
Power-aware MAC protocol

CSMA/CA
 B-MAC
 S-MAC
 T-MAC
 D-MAC
 802.15.4
->ZigBee
18
Power-aware MAC protocol

TDMA CSMA/CA hybrid
 Z-MAC

Dynamic adjust output power
 PAMAC
19
Content

Introduction

Energy conservation
 Topology
 Power
control
management

Harvesting energy

Summary
20
Harvesting energy
21
Harvesting energy types

Fully controllable

Partially controllable

Uncontrollable but predictable

Uncontrollable and unpredictable
22
Solar energy prediction

Exponentially Weighted Moving-Average

Diurnal cycle and Season variation

Assumption: energy generation to be
similar to the energy generation at the
same time on the previous days
x(i )
x(i 1) (1
) x(i )
Power management in energy harvesting sensor networks 23
Solar energy prediction

Error performance
24
Solar energy prediction

Weather-Conditioned Moving Average

Based on EWMA

Take into account weather condition of the
current day

Reduce error to 10%
x(d , n 1)
x(d , n) (1
)M D (d , n 1)GAPk
Prediction and management in energy harvested wireless sensor nodes
25
PM with harvesting energy

Infinitive energy source

Power conservation is not most important

Energy may be required when harvested
energy is not available
26
PM with harvesting energy
B0
B0
T
0
T
0
Ps (t ) Pc (t ) dt
Ps (t ) Pc (t ) dt
T
0
T
0
Pc (t ) Ps (t ) dt
Pc (t ) Ps (t ) dt
T
0
Pleak (t )dt
T
0
B
Pleak (t )dt
0
27
Where are we ?

First stage

Build-up ourselves platform
 ARM-based
 SoC

Modal system with OmNet++
 Energy
harvesting
 Simulate
and verify
28
Summary

Propose an infinitive life-time WSN

Harvest ambient energy

Predict harvested energy

Propose power management scheme

Simulate

Implement and Verify
29
Discussion
30