Energy Reduction in Wireless Sensor Networks

Transcription

Wireless Sensor Networks (WSN)
!  What is a Wireless Sensor Network ?
!  Dense network of small nodes
communicating through wireless
links
Energy Reduction in
Wireless Sensor Networks
•  for sensing, actuation,
processing, storage,
communication and control
•  ad hoc network
Olivier Sentieys
with contributions from:
Thomas Anger, Jérôme Astier, Arnaud Carer, Olivier Berder, Duc Nguyen, Vinh Tran,
Adeel Pasha, Steven Derrien, Hai-Nam Nguyen, Daniel Ménard, Vivek T.D., Mahtab Alam
Relay
Sensor and relay
IRISA/INRIA, University of Rennes 1
ENSSAT Lannion
[email protected]
Base station and gateway
Wireless Sensor Network
ECOFAC’2010
Ex. Temperature sensing
(1,8)
!(7,7)
(8,8)
(7,7)
?(7,7)
(5,6)
(1,5)
!(7,7)
(4,2)
!(7,7)
(8,4)
(11,3)
?(7,7)
Wireless Sensor Networks (WSN)
!  Set of nodes with
coordinates (X,Y)
?(7,7)
2
!  Temperature
sensing at (7,7)
!  BS(0,0) ! ?(7,7)
!  (1,5) ! ?(7,7)
!  (5,6) ! ?(7,7)
!  (8,8) ! !(7,7)
!  (5,6) ! !(7,7)
!  (4,2) ! !(7,7)
!  (0,0) receives
temperature
!  Simplified deployment, fault tolerance
•  No maintenance and battery replacement
!  Network characteristics
•  Low mean distance
•  Limited amount of data
•  Multi-hop routing
!  Low cost
!  Small size
!  Long autonomy, low power
•  Towards autonomous sensor nodes
(0,0)
ECOFAC’2010
3
ECOFAC’2010
4
On-demand model
ECOFAC’2010
Event-driven model
[Simplot, 2009]
5
[Simplot, 2009]
ECOFAC’2010
Emerging applications
Tremendous space of applications
!  Indoor environment
!  Monitoring space: ocean water, pollution,
!  Monitoring things: robots, human body,…
•  Industrial control, machine health monitoring,
condition based maintenance of equipment in factory
•  Indoor localization
•  Home automation, intelligent lightning and heating
•  Health care
6
!  Outdoor environment
•  Monitor natural habitats, remote ecosystems,
agriculture, forest fires
•  Structural Health Monitoring (e.g. bridges, buildings)
•  Automotive
•  Disaster sites
•  Security & military surveillance
ECOFAC’2010
Fire detection
Target monitoring
7
ECOFAC’2010
Monitoring in agriculture
[Fischione, UCB, 2007]
8
ANR SurVeiller et Prévenir
Captiv
http://captiv.irisa.fr
!  Capteurs de
paramètres
physiologiques
•  Suivi de l’activité
physique
•  Prévention de l’obésité
Cooperative Wireless
V2I Communications
!  http://svp.irisa.fr
ECOFAC’2010
9
ITEA2 Geodes: fire-fighters
ECOFAC’2010
10
Fire-fighter scenario
!  Indoor network
•  Temperature
monitoring, smoke
detection, motion
detection
•  Camera nodes
WSN nodes
Fire-Fighters
FIRE-FIGHTER
LOCALIZATION
!  Mobile nodes (firefighter)
PEOPLE
DETECTED
•  Health monitoring,
camera, etc.
•  Connected with indoor
network
ECOFAC’2010
PEOPLE
DETECTED
FIRE
DETECTED
11
ECOFAC’2010
PEOPLE
DETECTED
PEOPLE
DETECTED
12
Challenges in WSNs (1/2)
Challenges in WSNs (2/2)
!  Networking
!  Energy reduction of HW/SW
•  Physical design
•  MAC protocols
o  Power saving, collision avoidance, ...
•  Routing protocols
Cross-layer
optimizations
•  Digital processing
o  Low power processors
•  Radio front-end, analog processing
o  Small radios with small bandwidth & transmission ranges
o  Data aggregation, dissemination, ...
•  Light and efficient software
!  Network management
o  No complex operating systems
o  Mainly hardware-dependant software
•  Deployment, redeployment, topology control,
maintenance
•  Localization and positioning
•  Coverage and connectivity problems
!  Process or transmit ?
•  Limited processing power but communicating
wirelessly is power-hungry
!  Application
•  Data fusion, distributed signal processing, source
coding, positioning, tracking, etc.
ECOFAC’2010
!  Towards a true energetic autonomy
13
ECOFAC’2010
Autonomous nodes ?
Agenda
!  A WSN node is limited by the total energy it can
store or scavenge from the environment
!  WSN node architecture
14
•  HW Platform
•  Processor and radio transceiver performance
•  Need a drastic reduction in the total consumed energy
(radio + processing)
!  Protocols
•  MAC and network
•  SW Stack
!  Power models and estimation
!  Energy optimization
• 
• 
• 
• 
[CEA Leti, Managy]
ECOFAC’2010
15
Cross-layer (MAC/LINK)
FPGA co-processing
Architectural and circuit-level optimization
MIMO Cooperation
ECOFAC’2010
16
Generic architecture of a node
Generic architecture of a wireless node
•  Main tasks: sense, process, store, communicate,
power management
•  Other features (e.g. location finding systems)
Generator
TION
APPLICA
NET
DC/DC
conv.
Battery
LINK
SW
e
ructur
t
s
a
r
f
n
I
Sensor
A/D
Processor
Coprocessor
MAC
Radio
PH Y
RAM
Flash
ture
rastruc
f
n
I
W
H
ECOFAC’2010
17
Typical WSN platform
!  What are the main
sources of energy
consumption ?
•  Radio: 30-70mW
•  Processor: 5-10mW
DC/DC
18
!  Modern low-power microcontrollers
Timer
uController
Radio
! Micro-controller
! Transceiver in Rx
! Transceiver in Tx
Power consumption of a typical WSN platform
ECOFAC’2010
ECOFAC’2010
Device
Year
Arch.
Vdd
(V)
Ram Flash
(kB) (kB)
Active1 Sleep Wake
(mA)
(uA) (uS)
Atmel
AT128L
AT256l
2002
2005
RISC
8b
2.7-5
1.8-5
4
8
128
256
0.95
0.9
5
1
6
6
Freescale
HCS08
2003
MC13213 2007
8b
2.7-5
2-3.4
4
4
60
60
7.4
6.5
1
35
10
10
Jennic
JN5139
2007
32b
2.2-3.6 192
128
3
3.3
2500
TI MSP430
F1612
F5437
2004
2008
RISC
16b
1.8-3.6 5
16
55
256
0.5
0.28
2.6
1.7
6
5
TI
CC2430
2007
8051
2-3.6
128
5.1
0.5
4
NXP
LPC1114 2010
CortexM0
ARM
32b
1.8-3.6 8
32
0.25
6
-
1Active
19
current at 3V and 1MHz
ECOFAC’2010
8
#6mW@8MHz
[Dutta, Sensys, 2008]
20
PowWow
HW Platform (PWNode)
PowWow: power optimized hardware/software framework for wireless motes
!  Radio transceivers
!  Open source hardware developed at IRISA/Cairn
•  IEEE 802.15.4 compatible
Device
Year
Vdd
(V)
Atmel
RF230
2006 1.8-3.6
Freescale
Jennic
•  Mother board with MSP430
•  Daughter boards for
RxSens TxPwr
(dBm) (dBm )
Rx
Tx
(mA) (mA)
Sleep Wake
(uA) (mS)
-101
+3
15.5
16.5
0.02
1.1
MC13212 2005 2-3.4
-92
+3
37
30
1
7-20
JN5139
2007 2.2-3.6
-95
+0.5
37
37
2.8
>2.5
TI
CC2420
CC2520
2003 2.1-3.6
2008 1.8-3.8
-95
-98
-20 to 0 18.8
-20 to 5 18.5
17.4
25.8
1
0.03
0.58
0.5
Leti
Letibee
2008 1.2
-85
-3
9
-
-
6
o  V1: CC2420, Sensors
o  V2: FPGA, DVFS
!  FPGA for hardware acceleration
!  Voltage and frequency scaling
!  Power management (sleep, wake-up)
http://powwow.gforge.inria.fr
#50mW
ECOFAC’2010
21
PowWow
22
Agenda
!  Motherboard
•  TI MSP430 low-power microcontroller
•  HW Platform
o  MSP430F1612 version, 8 MHz clock
o  55KB of flash memory, 5KB of on-chip RAM
o  330uA at 1 MHz and 2.2 V in active mode
o  1.1uA in standby mode
!  Protocols
•  SW Stack
•  JTAG, RS232, and I2C interfaces
!  Radio daughterboard
•  TI CC2420 RF transceiver
•  single-chip 2.4 GHz IEEE 802.15.4 compliant
•  digital direct sequence spread spectrum baseband modem
• 
• 
• 
• 
o  spreading gain of 9 dB, data rate of 250 kbps
o  hardware support for
•  packet handling, data buffering, burst transmissions, data
encryption, data authentication, clear channel assessment, link
quality indication and packet timing information
ECOFAC’2010
ECOFAC’2010
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FPGA co-processing
MIMO Cooperation
ECOFAC’2010
24
MAC Protocols
MAC Protocols
!  MAC protocol determines next node to use the
medium
!  Sensor-MAC (S-MAC)
!  Carrier Sense Multiple
Access (CSMA)
!  Timeout-MAC (T-MAC)
•  Simple, scalable
•  e.g. 802.15.4
•  CSMA with fixed active/sleep duty cycle
•  Synchronization of active times
!  Time Division Multiple
Access (TDMA)
•  Avoid collision
•  e.g. GSM
•  Listen always
•  Collisions
•  Make duty cycle dynamic
•  End active time with time-out
"  Complexity
of
scheduling
"  Synchronization
needed
ECOFAC’2010
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ECOFAC’2010
26
MAC Protocols
Power Measurements on PowWow HW
!  Asynchronous Rendezvous
!  Wake-up and channel sensing
•  Asynchronous scheme initiated by receiver
•  RICER (Receiver-Initiated CyclEd Receiver)
Rx
Tx
Rx
Receiver wait
Node j
(transmitter)
Wake-up period (T)
All measurements realized
with Agilent N6705A DC
Power Analyzer
Data transmission
Node k
(receiver)
Wake-up frames
Waiting time
Acknowledge
Radio transceiver in reception/listening mode
Radio transceiver in transmission mode
ECOFAC’2010
[Lin, ICC, 2005]
27
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!  Wake-up and channel sensing
!  Wake-up and channel sensing with collision
6, 8, 16, 32, 64, 128 packet size in bytes
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Routing Protocols
Transmission Modes
!  Multi-hop routing
!  Geographical routing
!  Broadcast
•  Direct transmission to {neighbors}, no ACK
!  Flooding
•  Each node has (x,y) coordinates
•  Next node for hop transmission is chosen in the
neighbors as the nearest to the destination
•  Broadcast a packet to all network nodes, no ACK
!  Direct Hop with/without ACK
o  in the sense of Euclidian distance
•  Direct transmission to a specific neighbors
•  Neighbor table management
o  with or without ACK
o  A neighbor is a node in the radio range of another node
o  Set of neighbors is discovered power-up and on regular time
period
!  Robust Multi-Hop
•  Multi-hop transmission to a specific node in the
network
•  Each hop is with ACK
•  Uses node address
!  Many other protocols!
ECOFAC’2010
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ECOFAC’2010
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PowWow
SW Stack
PowWow
SW Stack
!  HAL, PHY, LINK, MAC, NETW layers and API
!  Open source software developed at IRISA/Cairn
• 
• 
• 
• 
•  http://powwow.gforge.inria.fr
!  Event-driven, multi-threaded, C code
•  Based on Protothread library and Contiki
FEC/ARQ, geographical routing, positioning,
Tx power and low-power mode management
Modes: broadcast, flooding, direct/multi-hop with/without ACK
Configurable packet structure
!  Analytical power estimation based on software profiling
and power measurements of a set of scenarios
!  Memory efficiency
•  6 Kbytes (protocol layers) + 5 Kbytes (application)
!  Over-the-air re-programmation (and soon
reconfiguration)
!  Comparison with 802.15.4/ZigBee
•  More than 12 less power for the same application scenario
o  Temperature sensing, 1-10-30s sensing period, TI MAC vs. PowWow
ECOFAC’2010
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Agenda
ECOFAC’2010
34
Energy Model
•  HW Platform
!  Protocols
•  SW Stack
o  PTB/PRB: power in baseband digital signal processing circuit
of transmitter and receiver (mW)
o  PTRF/PRRF: power in front-end circuit of transmitter and
receiver (mW)
o  PA: power of the Power Amplifier (mW)
o  PL: power of the Low Noise Amplifier (mW)
• 
• 
• 
• 
FPGA co-processing
MIMO Cooperation
ECOFAC’2010
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ECOFAC’2010
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Energy Model
Energy Model
!  Total power consumption
!  Relation between PT(d) and the required RF
output power for reliable transmission PTx(d)
•  Tx: PT(d) for a transmission of distance d
•  Rx: PR
• 
• 
• 
• 
• 
d
ECOFAC’2010
37
Chipcon Radio Tranceivers
Gt, Gr: transmitter and receiver antenna gain
PRx: desired receive power at destination
!: drain efficiency
!: carrier wavelength
L: system loss factor
ECOFAC’2010
38
Energy Consumption
!  CC2420 radio transciever
d=10m, SISO
ECOFAC’2010
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ECOFAC’2010
d=100m, SISO
40
Energy Estimation
Energy Estimation
!  How to estimate the energy more precisely ?
!  How to estimate the energy more precisely ?
!  Total energy dissipated in the WSN
E = V . (Ep + Ert.Nrt + Ewuc.Nwuc + Ec.Nc)
!  Mixed estimation method
• 
• 
• 
• 
• 
• 
•  Profiling of code execution or platform power
measurement
o  Ep Ert
V = {Vi,j}: volume of data between i and j
Nrt: mean number of retransmissions
Nwuc: mean number of wake-up collisions
Nc: mean number of collisions
Ep: energy of a packet transmission
Ert Ewuc Ec: energy of a retransmission, a wake-up
collision and a collision
[Thèse Cartron, 2006]
ECOFAC’2010
•  Application and network simulation
o  {Vi,j}
•  Analytical performance models
o  Nrt
41
Scenario-based power estimation
PP2
TxOK
RxEr
Rx
Too many errors
detected that can
not be corrected
TxC
RxC
Wake-up
collision
at Rx
PP1/2: Process Packet Phase !
RxEr: Rx Packet with error
ECOFAC’2010
TxOK
RxOK PP2
Nc
42
Scenario-based power estimation
Energy consumption of event cycles [J]
•  e.g. MAC events
PP1
Nwuc
ECOFAC’2010
!  Analytical approach based on software profiling
and power measurements of a set of scenarios
Tx
Ewuc Ec
RxOK
TxOK
Wake-up
collision
of a Tx with
another Tx
CBT
T
WUR
WUC
DC
TIM
Rx soft
5.3e-8
5.3e-8
1.2e-4
1.2e-4
5.3e-8
5.3e-8
Tx soft
4.1e-8
1.2e-3
1.0e-8
4.1e-8
6.9e-4
4.1e-8
clock
5.5e-7
5.5e-7
5.5e-7
5.5e-7
5.5e-7
5.5e-7
LINK
4.8e-7
0
4.8e-7
0
0
0
NETWORK
4.8e-7
0
0
0
0
0
Req_neighb
0
0
0
0
0
0
Ans_neighb
0
0
0
0
0
0
positionning.
0
0
0
0
0
0
listen target
0
0
0
0
0
0
scheduler
3.7e-7
3.7e-7
3.7e-7
3.7e-7
3.7e-7
3.7e-7
Tx HF
0
2.32e-3
2.32e-3
0
0
0
Rx HF
0
5.2e-2
3.1e-3
3.1e-3
5.2e-2
0
CBT: Calculation Before Transmission
WUR: Wake Up with Reception
DC: Data Collision
TxOK/RxOK: Normal Tx/Rx
TxC/RxC: Tx/Rx with collision
43
ECOFAC’2010
T: Transmission
WUC: Wake Up with Collision
TIM: Timer
44
Scenario 1
Scenario 2
!  Periodic sensing and data transmission to BS
!  Periodic sensing with data transmission in case
of alarm
1
Periodic
sensing
3
2
4
1
2
7
Data
transmission
4
4
Periodic
sensing
1
2
9
5
1
2
7
6
4
7
6
5 6 7
7
3
5
2 3 4
1
Alarm
1
2
4
MSdesc
V (7)
Alarm
data
E(i) : number of alarm at node i
V : matrix of messages i!j
Tobs: simulation time
Fech: sensing frequency
MSdesc(i) : matrix of data
transmitted from node i
45
ECOFAC’2010
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45
ECOFAC’2010
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Scenario 3
Results on scenario 2
!  On-demand sensing
of alarm
0,343 0,139
No event
1,86
3,744
Wake-up interval: 2 s
Query
F(i) : number of queries to node i
Radio Rx
Digital
0,29
0,432
Available energy: 3 AA
batteries
Sensing
MSasc(i) : matrix of queries
transmitted to node i
P = 3 mW
Auton. = 126 days
Data
0
Radio Tx
2,688
Total energy: 10.75 W.h
1,256
soft Rx
soft Tx
clock
soft link layer
soft network
request neighb.
answer neighb.
thread positioning
thread sensing
scheduler
radio Tx
radio Rx
47
ECOFAC’2010
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Results on scenario 2
Simulation: WSim+WSNet
of alarm
!  Open source software developed at INSA Lyon
!  WSim: hardware platform simulation
0,337 0,355
0,274
1,758
10 events per second
Wake-up interval: 2 s
Available energy: 3 AA
batteries
0,409
0
Digital
Radio Rx
1,187
2,957
13,296
Radio Tx
P = 5.7 mW
Auton. = 66 days
• 
• 
• 
• 
soft Rx
soft Tx
clock
soft link layer
soft network
request neighb.
answer neighb.
thread positioning
thread sensing
scheduler
radio Tx
radio Rx
!  WSNet: event-driven simulator for wireless networks
• 
• 
• 
• 
Node simulation
Environment simulation
Radio medium simulation
Extensibility
!  http://wsim.gforge.inria.fr
!  http://wsnet.gforge.inria.fr
Total energy: 20.57 W.h
ECOFAC’2010
Cycle accurate simulation
Several models (processors, transceivers, peripherals)
Interaction with WSNet for distributed network simulation
Application final binary
49
Simulation: WSim+WSNet
ECOFAC’2010
[Chelius, 2006]
50
Agenda
•  HW Platform
!  Protocols
•  SW Stack
• 
• 
• 
• 
ECOFAC’2010
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FPGA co-processing
MIMO Cooperation
ECOFAC’2010
52
Main Goals
Power optimization of a wireless node
!  How to design and optimize an energy-efficient
software and hardware platform for wireless
sensor networks ?
TION
APPLICA
NET
!  (1) Decrease transmission (Tx) power
•  Power-aware signal processing
•  Error detection and correction
LINK
SW
e
ructur
t
s
a
r
f
n
I
!  (2) Optimize radio activity and MAC
MAC
PH Y
!  (3) Power optimization of the hardware
ture
rastruc
f
n
I
W
H
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Results on MAC parameter optim.
Results on MAC parameter optim.
!  Wake-up period influence
!  Wake-up period influence
Short WUP
•  Application dependent
Short WUP
T
0,2 s
19,45 mW
19,3 Days
E
R
More collisions
Useless wake-up
T
R
R
Optimal WUP
Optimal WUP
T
1,6 s
5,64 mW
66,5 Days
T
R
R
R
E
Long WUP
Long WUP
Rx power increase
R
R
R
ECOFAC’2010
8,0 s
12,17 mW
30,8 Days
Rx power increase
T
T
E
More collisions
Useless wake-up
Transmission Mode
Receiver Mode
Transmission Mode
Receiver Mode
55
ECOFAC’2010
[Thèse Cartron, 2006]
56
Output Radio Power Management
TION
APPLICA
NET
SW
e
ructur
t
s
a
r
f
n
I
LINK
MAC
PHY
ture
rastruc
f
n
I
W
H
ECOFAC’2010
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Performance/energy joint modelling
Output Radio Power Management
!  Energy per successfully transmitted bit
!  Energy per successfully transmitted bit
Energy per successfully transmitted bit[J]
Energy per successfully transmitted bit[J]
D=10 m, Pnoise=-90 dBm, 53 bytes packets
d
CC1020 transceiver
•  as a function of distance and Tx power
•  without error correction
D [m]
Transmission Power (PTx) [dBm]
ECOFAC’2010
"  Dynamic adaptation
of output radio power
depending on channel
conditions, distance,
etc.
"  RSSI or CRC as
quality metrics
[Sentieys, DASIP, 2007]
59
ECOFAC’2010
PTx [dBm]
60
HW Platform Energy Optimization
! 
! 
! 
! 
TION
APPLICA
NET
SW
e
ructur
t
s
a
r
f
n
I
LINK
(1)
(2)
(3)
(4)
Co-processing
Dynamic Voltage Scaling
Power Gated FSM
Dynamic Precision Scaling, etc.
Generator
DC/DC
conv.
Battery
MAC
Sensor
PHY
A/D
Processor
Coprocessor
RAM
Flash
ture
rastruc
f
n
I
W
H
ECOFAC’2010
61
PowWow
Radio
ECOFAC’2010
62
Co-Processing with a Low Power FPGA
!  FPGA co-processing, Power Mode Management
(PMM) and Dynamic Voltage and Frequency
Scaling (DFVS) daughterboard
•  Low-power Igloo FPGA from Actel
o  AGL125: 130nm, 125 kgates, 32kbits on-chip RAM, 1 kbits
Flash, PLL for clock management.
o  Supply voltages 0 to 1.65V
o  Power consumption: 2.2uW, 16uW, 1-30mW in sleep, freeze,
run modes
Watch Dog
Vdd scaling
Wake-Up
CC2420
o  e.g. Viterbi implemented for error correction: 5mW
Px
ECOFAC’2010
DC/DC
63
ECOFAC’2010
Igloo
FPGA
Control
Data
MSP430
Sensors
Co-processing mode
64
Dynamic Voltage Scaling (1/3)
DVS (and frequency)
Power of MSP430
1.6V, 1.8V, 2V, 2.5V, 3V, 3.3V
1.6V, 1.8V, 2V, 2.5V, 3V, 3.3V
ECOFAC’2010
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ECOFAC’2010
66
PowWow
!  FPGA/DFVS daughterboard (cont.)
•  Power Mode Management
o  Low-Power Programmable Timer
Power of MSP+CC2420
•  MAX6370, 8uA
•  Wake-up period
1.6V, 1.8V, 2V, 2.5V, 3V, 3.3V
•  DVFS
o  Programmable Clock
•  LTC6930, 490uA
•  8MHz divided by 1 to 128
o  Programmable DC/DC conv.
•  TPS62402/TPS61030
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68
HW Platform Energy Optimization
! 
! 
! 
! 
(1)
(2)
(3)
(4)
Power Gated Controllers (1/6)
Co-processing
Dynamic Voltage Scaling
Power Gated FSM
Dynamic Precision Scaling, etc.
Generator
Sensor
Battery
A/D
!  Power Gating Principle
DC/DC
conv.
Processor
Coprocessor
RAM
Flash
Radio
ECOFAC’2010
69
!  Task graph to
gated FSM
ECOFAC’2010
70
Power-gated Micro-Task (3/6)
!  HW specialization
!  Leakage reduction
!  Micro-Task
•  Customized FSM + minimalistic data-path
Task A
Task B
Task C
ECOFAC’2010
[Pasha, ISCAS 2009]
71
ECOFAC’2010
72
Automatic generation flow (5/6)
!  Power gain versus MSP430 software execution
!  C to VHDL compilation
flow for the automatic
hardware task
generation
o  Gains w.r.t. the power and energy consumptions of an
MSP430F21x1 (datasheet) and an open core MSP430-clone
(without memory)
o  Operating frequency of 16 MHz
•  Based on GeCoS
compiler/HLS
infrastructure
ECOFAC’2010
[Pasha, DAC, 2010]
73
Automatic generation flow (6/6)
ECOFAC’2010
74
Dynamic Precision Scaling (1/3)
!  System-level DSL
!  Energy consumption reduction by fixed-point
adaptation of the data-path wordlegth
•  depending on observed error rate (BER) and signalto-noise ration (SNR)
System
System outputs
System inputs
f fp ( p)
Fixed-point
specification
selection
p
Metric p
measurement
ECOFAC’2010
75
ECOFAC’2010
[Thèse H.N. Nguyen]
76
!  Range estimation: determine the minimal integer
word-length which guarantees no overflow
!  Precision Analysis: determine the minimal fractional
word-length which guarantees the performance criterion
!  40% of energy savings between 0dB and –25dB
ECOFAC’2010
•  CDMA receiver, data-path energy
77
Radio transceiver optimization
[Nguyen, ISCAS, 2009]
ECOFAC’2010
78
!  LetiBee chip (CEA LETI)
•  Expected power consumption (2nd release)
Function
RX (mA)
TX
RF
0.5
2.73
LO
4
7
PLL
0.35
0.35
Analog
0.2
0.4
Digital
0.5
0.25
Biasing
1.5
0.5
TION
APPLICA
NET
SW
e
ructur
Infrast
o  Tx # 13.5 mW @ -2 dBm
o  Rx # 8.5 mW @ -85 dBm
MAC
PH Y
!  Trends
ture
rastruc
f
n
I
W
H
•  Wake-up radio, Ultra-Wide Band
ECOFAC’2010
LINK
[Bernier, ESSIRC, 2008]
79
ECOFAC’2010
80
Cooperative techniques
Alamouti scheme
!  Context
!  Model
•  Physical layer (with impact on MAC/NET layers)
•  Cooperative strategies between wireless nodes
s(1)
-s*(2)
y(1)
y(2)
Source
o  take advantage of channel spatial and temporal diversity to
decrease the radio output power
s(2)
Destination
s*(1)
!  Protocol
!  Objectives
•  Optimize different Cooperative MIMO techniques
•  Compare and associate them with Relay techniques
•  Consider the energy consumption to determine the
optimal selection scheme
ECOFAC’2010
[Alamouti 1998]
ECOFAC’2010
81
Performance of Space-Time Codes
82
Cooperative MIMO
!  Three phases of C-MIMO communications
•  Phase 1: Local data exchange and space-time coding
•  Phase 2: Virtual MIMO transmission
•  Phase 3: Cooperative reception
d
Nr
S
D
MIMO transmission
dm
Nt
Space-Time Codes bring us better performance
ECOFAC’2010
dm<<d
83
ECOFAC’2010
dm = 1..10 m
84
Energy consumption of C-MIMO
Cooperative MIMO
!  Cooperative MIMO technique is more energy
efficient than SISO and multi-hop SISO
techniques for long distance transmission
!  Total energy = Transmission Energy + Digital
Energy + Cooperation Energy
d=100m, MISO 2-1
ECOFAC’2010
[Nguyen, ICC, 2008]
85
Relay Technique
d=100m, SISO
ECOFAC’2010
86
Performance of relay technique
!  Diversity gains by sending additional copies of
the signal through relays
!  Less delay, simpler processing
!  Two main types
•  Amplify and Forward (AF)
•  Decode and Forward (DF)
Performance of relay model is better than that of SISO
ECOFAC’2010
87
ECOFAC’2010
88
MIMO relay model
r1(1)
yr1(1)
MIMO simple cooperative relay model
r1(1)
r1(2)
yr1(2)
yr1(1)
s(1)
-s*(2)
r2(1)
yr2(1)
R2
r2(2)
yr2(2)
s(1)
-s*(2)
y(1)
y(2)
t1
y(3)
s(2)
S1
s(1)
-s*(2)
S2
s(2)
s*(1)
R1
yr1(1)
yr1(2)
R2
yr2(1)
yr2(2)
D
y(1)
y(2)
t3
Transmit r1(1)
t5
t4
y(3)
ECOFAC’2010
t6
s*(1)
Time Slot
Transmit r1(2)
Transmit r2(1)
y(4)
y(5)
Transmit r2 (2)
y(6)
89
R2
yr2(2)
r2(2)
t1
t2
r2*(1)
t3
t4
S1
s(1)
-s*(2)
S2
s(2)
s*(1)
R1
yr1(1)
yr1(2)
r1(1)
-r1*(2)
R2
yr2(2)
yr2(2)
r2(2)
r2*(2)
D
y(1)
y(2)
y(3)
y(4)
ECOFAC’2010
90
Performances
Energy simulation
!  AF protocol
!  Optimal model choice to minimize energy
relative distance:
d(source-relay)
d(source-dest)
BER (Bit Error Rate)
y(4)
D
y(4) y(5) y(6)
s*(1)
t2
y(3)
y(2)
Source
yr2(1)
Time Slot
R1
yr1(2)
y(1)
D
Source
s(2)
-r1*(2)
SNR (Signal to Noise Ratio)
ECOFAC’2010
92
ECOFAC’2010
[Thèse V. Tran]
93
Cooperative MIMO and Relay
Summary
!  Advantage
!  Energy minimization in WSN
•  Complex cross-layer problem
•  Power/performance models
•  Energy efficiency for
o  long-range transmission (WSN)
o  fading channels
!  Reduction of Tx Power
!  Trade-off
•  Signal processing, error correcting code
•  Extra circuit consumption
!  Reduction of Rx activity
o  MIMO digital signal processing
•  MAC, routing
•  Delay of cooperative local data transmission or relay
•  Distance between cooperating nodes dm much smaller
than transmission distance d
!  Power optimization of heterogeneous platforms
•  Power management, dedicated hardware, power
gating, etc.
!  Challenges
•  Link with MAC and route protocols
•  Choice of the optimal cooperating strategy
ECOFAC’2010
!  Power optimization of analog and radio
94
Design challenges
Signal Processing
Control
!  Channel coding
!  MIMO, relay …
!  Modulation
!  MAC
!  Routing …
Communications
ECOFAC’2010
[Min02] R. Min et al., Power-aware Wireless Microsensor Networks, in Power-aware Design Methodologies, 2002.
[Cui04] S. Cui, A. Goldsmith, Energy_efficiency of MIMO and cooperative MIMO Techniques in Sensor Networks, IEEE
JSAC, 2004.
[Cartron 2006] M. Cartron, Vers une plate-forme efficace en énergie pour les réseaux de capteurs sans fil, PhD Thesis,
University of Rennes 1, 2006.
[Li07] Y. Li, B. Bakkaloglu and C. Chakrabarti, A System Level Energy Model and Energy-Quality Evaluation for
Integrated Transceiver Front-Ends, IEEE Trans. on VLSI, 2007.
[Nguyen07] Tuan-Duc Nguyen, Olivier Berder and Olivier Sentieys, Cooperative MIMO schemes optimal selection for
wireless sensor networks, IEEE VTC-Spring, 2007.
[Sentieys07] O. Sentieys, O. Berder, P. Quemerais and M. Cartron, Wake-up Interval Optimization for Sensor Networks
with Rendez-vous Schemes, Workshop on Design and Architectures for Signal and Image Processing (DASIP),
2007.
[Wang06] Q. Wang, M. Hempstead and W. Yang, A Realistic Power Consumption Model for Wireless Sensor Network
Devices, IEEE SECON, 2006.
[Pasha09] M. A. Pasha, S. Derrien, and O. Sentieys. Ultra low-power fsm for control oriented applications. IEEE
International Symposium on Circuits and Systems, ISCAS 2009, pages 1577 – 1580, Taipei, Taiwan, May 2009.
[Pasha10] M. A. Pasha, S. Derrien and O. Sentieys, A Complete Design-Flow for the Generation of Ultra Low-Power
WSN Node Architectures Based on Micro-Tasking, Proc. of the IEEE/ACM Design Automation Conference (DAC)
Anaheim, CA, USA, June 2010.
[Nguyen08a] T. Nguyen, O. Berder, and O. Sentieys, Impact of transmission synchronization error and cooperative
reception techniques on the performance of cooperative MIMO systems, IEEE ICC, 2008.
[Nguyen08b] T. Nguyen, O. Berder, and O. Sentieys, Efficient space time combination technique for unsynchronized
cooperative MISO transmission, IEEE VTC-Spring, 2008.
[Lin05] E.Y Lin, J. Rabaey, S. Wiethoelter, and A. Wolitz. Receiver Initiated Rendez-vous Schemes for Sensor Networks.
In Proc. of IEEE Globecom 2005, 2005.
[Lin04] E.Y. Lin, J. M. Rabaey, and A. Wolisz. Power-Efficient Rendez-vous Schemes for Dense Wireless Sensor
Networks. In IEEE International Conference on Communications ICC 2004, 2004.
[Menard08A] D. Menard, R. Rocher, O. Sentieys, and O. Serizel. Accuracy Constraint Determination in Fixed-Point
System Design. EURASIP Journal on Embedded Systems, 2008.
[Menard08B] D. Menard, R. Rocher, and O. Sentieys. Analytical Fixed-Point Accuracy Evaluation in Linear TimeInvariant Systems. IEEE Transactions on Circuits and Systems I, 55(1), November 2008.
!  Verification
!  Distributed computing
!  Embedded software
!  Middleware
!  Operating Systems …
WSN
95
Bibliography
Computer Science
!  Hybrid systems
!  Networked control
!  Source coding
ECOFAC’2010
!  Micro-architecture
!  CAD tools
!  Digital
!  Analog
!  RF …
Microelectronics
96
ECOFAC’2010
97
Questions ?
Thanks for their contributions to:
Thomas Anger, Jérôme Astier, Arnaud Carer,
Olivier Berder, Duc Nguyen, Vinh Tran,
Adeel Pasha, Steven Derrien,
Hai-Nam Nguyen, Daniel Ménard,
Vivek T.D., Mahtab Alam
and others

Energy Reduction in Wireless Sensor Networks

Transcription

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