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Copyright © 2006
EEM202B/CSM213B - Spring 2006
Mani Srivastava
UCLA - NESL
http://nesl.ee.ucla.edu
Lecture #2: Wireless Comm. for ENS - Part IThe Lower Layers
2
Reading List for this Lecture
• Curt Schurgers, Vlasios Tsiatsis, Saurabh Ganeriwal, and Mani Srivastava, “Optimizing Sensor Networks in the Energy-Density-Latency Design Space,” IEEE Transactions on Mobile Computing, January-March 2002.
– http://nesl.ee.ucla.edu/courses/ee202b/2006s/papers/L02/Schurgers02_TMC.pdf
• Wei Ye, John Heidemann, and Deborah Estrin, “Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks,” IEEE/ACM Transactions of Networking, Vol. 12, No. 3, pp. 493-506, June 2004.
– http://nesl.ee.ucla.edu/courses/ee202b/2006s/papers/L02/Ye04_ToN.pdf
• Joseph Polastre, Jason Hill, and David Culler, “Versatile Low Power Media Access for Wireless Sensor Networks,” Proceedings of ACM SenSys, November 2004.
– http://nesl.ee.ucla.edu/courses/ee202b/2006s/papers/L02/Polastre04_SenSys.pdf
• Saurabh Ganeriwal, Deepak Ganesan, Hohyun Shim, Vlasios Tsiatsis, and Mani Srivastava, "Estimating clock uncertainty for efficient duty-cycling in sensor networks," The Third ACM Conference on Sensor Networking Systems (SenSys 2005) , November 2005.
– http://nesl.ee.ucla.edu/courses/ee202b/2006s/papers/L02/Ganeriwal05_SenSys.pdf
3
Traditional Communication Stack
Application layer
Transport layer
Network layer
Link/MAC layer
Physical layer
End-to-end reliability, congestion control
RoutingPer-hop reliability, flow control, multiple access, topology managementPacket transmission and reception
4
Radios and Radio Channels
5
Digital Radio Communications
MultipleAccessMultiplex
SourceCoder
SourceCoder
ChannelCoder Modulator Power
Amplifier
Radio
Channel
MultipleAccessDemultiplex
SourceDecoder
SourceDecoder
ChannelDecoder
Demodulator& Equalizer
RFFilter
So
urc
eD
esti
nat
ion
Carrier fc
Carrier fc
transmittedsymbol stream
received (corrupted)symbol stream
antenna
antenna
6
Options for Physical Layer
• Less common– Infrared
– Acoustic
– Magnetic, capacitive or inductive coupling (“near field”)
• Far field radios– 802.11
– Bluetooth
– Proprietary: RFM, Chipcon, Nordic Semiconductor
– 802.15.4/Zigbee
– …
7
Communication vs. {Computation, Storage}
Transmit 2950 nJ/bit Processor 4 nJ/op
Receive 2600 nJ/bit ~ 1400 ops/bit
Mote-class802.15.4 Node
Microserver-classNode
Transmit 6600 nJ/bit Processor 1.6 nJ/op
Receive 3300 nJ/bit ~ 6000 ops/bit
Write470 nJ/bit to120750 nJ/bitAtmel AVR
Flash(256b/page) Read
30 nJ/bit to7600 nJ/bit
Write1 nJ/bit to550 nJ/bit1GB NAND
Flash Chip(512b/page) Read
0.4 nJ/bit to220 nJ/bit
• Energy/bit sent > Energy/bit stored > Energy/op– True even for short ranges
– Gap even larger in actuality, due to protocol and filesystem overheads
8Radio Rx Dominates at Short Ranges due to
Electronics
Tx: Sender Rx: Receiver
ChannelIncominginformation
Outgoinginformation
TxelecE Rx
elecERFETransmit
electronicsReceive
electronicsPower
amplifier
0
2000
4000
6000
8000
0
100
200
300
0
200
400
600
TxelecE Rx
elecERFE TxelecE Rx
elecERFE TxelecE Rx
elecERFE
nJ/bit nJ/bit nJ/bit
~ 1 km (GSM) ~ 50 m (WLAN) ~ 10 m (Mote)
9
Domination of Electronics at Short Range
d
Static Power,Digital
Processing
Power amp,Receiver
Sensitivity
Radio Maximum dn
2.4 KHz OOK(RFM TR1000 @ 916 MHz)
14 J 3.1 J
115.2 KHz ASK(RFM TR1000 @ 916 MHz)
372 nJ 65 nJ
1 Mbps Custom(MIT AMPS-1 @ 2.4 GHz) 570 nJ 740 nJ
11 Mbps 802.11b(Cisco Aironet 350 @ 2.4
GHz)236 nJ 91 nJ
54 Mbps 802.11a(Atheros, ISSCC2002)
14.8 nJ 11 nJ
€
Ebit = α + βdn
Re: Min et. al., Mobicom 2002 (Poster)
Sender Side Power Consumption
10
Radio Electronics Trends
Analog electronics240 mW
Digital electronics170 mW
Power amplifier 600 mW
(~11% efficiency)
Intersil PRISM II (Nokia C021 wireless LAN)
Radiated power63 mW (18 dBm)
Trends: Move functionality from the analog to the digital electronics Digital electronics benefit most from technology improvements Analog a bottleneck Digital complexity still increasing (robustness)
11Example: Rx and Tx Power Consumption
in Mica 1 Mote
Note: higher numbers represent lower RF power
12
Assumptions Underlying Traditional Wireless Protocols
• Transmission is costlier than reception• Idle listening is cheap• Energy scales as distance^n so that
– Multihop
– Coding (lowers Eb/No) always good for J/bit
– Modulation (lowers Eb/No)
}
13
Assumptions Underlying Traditional Wireless Protocols
• Transmission is costlier than reception
• Idle listening is cheap
• Energy scales as d^n so that– Multihop– Coding (lowers Eb/No) always good for J/bit– Modulation (lowers Eb/No)
But these assumptionsbreakdown in sensor nets
}
14
• Ignoring Idle listening when no sensing events leads to misleading conclusions
Example: Energy-aware MAC[Intanago et. al. 2000]
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 50 100 150 200 250 300
Ave
rage
Dis
sipa
ted
Ene
rgy
(Jou
les/
Nod
e/R
ecei
ved
Eve
nt)
Network Size
DiffusionDiffusion
Omniscient MulticastOmniscient MulticastFloodingFlooding
00.0020.0040.0060.0080.01
0.0120.0140.0160.018
0 50 100 150 200 250 300
Ave
rage
Dis
sipa
ted
Ene
rgy
(Jou
les/
Nod
e/R
ecei
ved
Eve
nt)
Network Size
DiffusionDiffusion
Omniscient MulticastOmniscient Multicast
FloodingFlooding
Over 802.11-like MAC Over energy-aware MAC
15
Example: Multihop & Characteristic Distance[Ref: Min & Chandrakasan, 2002]
16
Radio Energy Management: Reducing Energy/Bit
• During operation, the required performance is often less than the peak performance the radio is designed for
• How do we take advantage of this observation, in both the sender and the receiver?
??
time
Tx Rx
17
Energy Consumption of the Sender
• Parameter of interest:– energy consumption per bit
Tx: Sender
Incominginformation
TxelecP
RFP
Transmission timeTransmission time
Ene
rgy
Ene
rgy
bitbit T
PE =
Ene
rgy
Transmission time
RFDominates
Electronics Dominates
TotalP
Modulation scaling
fewer bits per symbol
Code scaling
more heavily coded
18
Dependence on Transmission Range
Short-range
Medium-range
Long-rangeE
ner
gy
Transmission time
• Long range: scale coding or modulation to use all the available time• Short range: transmit rapidly and shutdown
19
Scaling vs. Shutdown
Power
time
allowed time
transmission time = t*
Power
time
allowed time
transmission time = t*
Power
time
allowed timetransmission time
En
erg
y Region of scaling
Region of shutdown
Emin
t*
• Use scaling while it reduces the energy
• If more time is allowed, scale down to the minimum energy point and subsequently use shutdown
time
20
Long Range Case: Scaling for Energy
RFE
Power
time
available time
transmission time
Modulation scaling
fewer bits per symbol
Code scaling
more heavily coded
Ene
rgy
transmission time
TxelecE Rx
elecE
Ene
rgy
transmission time
Principle
– Vary radio ‘control knobs’ such as modulation and error coding
– Trade off energy versus transmission time
21
Energy-aware Medium Access Control
• Radios with scalable modulation and coding• MAC protocol that decides
– Which node transmits– What packet– At what time– On what channel– With what RF power– What modulation and coding setting
bC
bCE E
b
Sbit
112×+⎟⎟
⎠
⎞⎜⎜⎝
⎛ −×=
Sbit Rb
T×
=1
[For a QAM system]
Dynamic Modulation Scaling (DMS)
22
Energy Aware Packet Scheduling
• E.g. enhancement of fair queuing schedulers
• Normally, distribute excess bandwidth is distributed
• But, we can use it to reduce energy at the cost of increased latency
• Input queue sizes monitored and output radio rate set accordingly
23
Short Range Case: Shutdown
• Principle– Operate at a fixed speed and
power level– Shut down the radio after the
transmission– No superfluous energy
consumption• Gotcha
– When and how to wake up?– More later …
Power
time
available time
transmission time
Energy
allowed time
transmission time shutdown
no shutdown
24
Radio Energy Management Summary
Long-range links
• Scaling based
• Slow down transmissions
• Energy-aware packet schedulers exploit thise.g. Raghunathan et. al. @ ACM ISLPED ‘02
Short-range links
• Shutdown based
• Turn off sender and receiver
• Topology management schemes exploit thise.g. Schurgers et. al. @ ACM MobiHoc ‘02
Ene
rgy
transmission time
Ene
rgy
transmission time
25
Shutdown and Radio Startup Time
• Radio modes: active, idle, shutdown, transient
• Transient period– Active/idle to sleep is short and can be ignored– Sleep to active/idle period, TON, is not
• PLL in the frequency synthesizer takes time to settle• Ptr = 2*Psyn
• TON is O(10)-O(100) uS• mixer & power amp startup can be ignored
• Problem: TON is significant fraction of packet duration– Packet sizes small in sensor nets (reporting events)
• Leads to high energy per bit!
• Radios with fast start-up and acquisition
26Radio Energy Efficiency vs. Power
Management Efficiency
Technology Data Rate Tx Current Energy per bit Idle Current Startup cost
Chipcon CC1000
76.8 Kbps 10 mA 430 nJ/bit 7 mA Low (~ 10 ms)
Bluetooth 1 Mbps 45 mA 149 nJ/bit 22 mA Medium (~ 1 s)
802.11 11 Mbps 300 mA 90 nJ/bit 160 mA High (~ 10 s)
IEEE 802.11
Bluetooth
Chipcon CC1000
Energy per bit
Startup cost
Idle current
27
Multi-radio Wireless Systems
• Wireless devices equipped with multiple radios– Heterogeneity enables ubiquitous connectivity
• E.g., Stargate wireless platform from Intel Research– 802.11 through CF slot, on-board Bluetooth, plug in connector for
Berkeley motes
• 400 MHz PXA-255 XScale
• 64 MB SDRAM
• PCMCIA, Ethernet, USB, RS-232
• Runs ARM Linux
Exploit radio heterogeneity for power management
28
Hierarchical Radio Performance on Stargate
Discovery schemeDiscovery
latency (ms)Power gating
overhead (ms)Connection latency (ms)
Discovery power (mW)
Chipcon CC1000 457 ms (2) - 8.3 mW
Bluetooth (BT) 2935 ms (453) 714 ms 58 mw
802.11b (WF) 1298 ms (1103) 222 ms 398 mW
CC1000 BT 457 ms 1698 1293 ms 9.3 mW
CC1000 WF 457 ms 1205 222 ms 9.3 mW
BT WF 2935 ms 1205 1763 ms 61 mW
(TDK Bluetooth module running BlueZ stack, Netgear MA-701 802.11b card using HostAP drivers, MICA2 mote duty cycled)
[In collaboration with Ubiquity SRP, Intel]
29
IEEE 802.15.4/Zigbee
• Target space– Low power consumption and low cost– Low offered message throughput– Large networks (<= 65k nodes)– Low to no QoS guarantees– Selectable levels of security (using AES-128)
• Privacy (encryption), Sender authentication, Message integrity
• 802.15.4 characteristics– Data rates of 250 kb/s (2.4 GHz) and 20/40 kb/s (868/915
MHz).– 16 channels in the 2.4 GHz ISM band, 10 channels in the 915
MHz ISM band and one channel in the European 868 MHz band.– CSMA-CA channel access.– Fully handshaked protocol for transfer reliability.– Extremely low duty-cycle (< 10 ppm) capability.– Beaconless operation available.– Support for low latency devices (Guaranteed Time Slots in
star networks).– Star or Peer-to-Peer network topologies supported.From Callaway @ ACM Sensys 2003
30
The Two 802.15.4 PHY layers
From Callaway @ ACM Sensys 2003
31802.15.4 PHY Issues: Orthogonal Multilevel
Signaling
• Low Pavg is achieved with a low overall system duty cycle, consistent with low peak currents
• At the physical layer, this encourages the use of a high data rate, but low symbol rate
– Peak currents tend to track symbol rate, rather than data rate
• This implies the use of multilevel signaling
• However, simple multilevel signaling results in sensitivity loss that may defeat the low power goal
• Solution is the use of orthogonal signaling—trading bandwidth to recover sensitivity with coding gain
• Standard
– 250 kbps (4 bits/symbol, 62.5 kBaud)
– 16-ary orthogonal modulation
– 16 symbols are pseudo-orthgonal set of 32-chip PN codes
– Chip modulation is O-QPSK at 2.0 Mchip/s (1 Mchip/s in I and Q each)
From Callaway @ ACM Sensys 2003
32802.15.4 PHY Issues: Warmup Power Loss
Reduction
• Since the active periods of IEEE 802.15.4 nodes can be very short, significant power can be lost if the transceiver warmup time is long
• Warmup time can be dominated by the settling of transients in the signal path, especially the (integrated active) channel filters
• Wideband techniques, such as Direct Sequence Spread Spectrum (DSSS), have an advantage in that their wide channel filters have inherently short settling times
• With their greater channel spacing, DSSS frequency synthesizers may also employ higher frequency references, reducing lock time
From Callaway @ ACM Sensys 2003
33
Additional Features of 802.15.4 PHY
• Constant-envelope modulation– Use of half-sine shaped O-QPSK simplifies Tx PA design
and reduces active current
• No duplex operation– Reduces peak current
• Rx blocking spec reduced– Allows lower active power consumption of Rx front-end
• Appropriate carrier frequency:– Avoids use of 60GHz ISM band for now due to cost,
power consumption reasons
• Low power output acceptable– Must be “capable” of -3 dBm Pout, but can reduced as
desired in operationFrom Callaway @ ACM Sensys 2003
34
Tx v.s Rx Power Drain
• There is little point to reduce Tx Pout below 0 dBm (1 mW) or so to reduce power consumption– since practical implementations will require ~10 mW fixed
power just to run frequency synthesizers, etc., regardless of power output
• In these low-power systems, Rx active power is often greater than Tx active power– due to the larger number of signal processing circuits that
must be active in receivers
• This can have a significant effect on power consumption strategies– It’s more power-efficient to blindly transmit than to blindly
receive—for the same amount of time
From Callaway @ ACM Sensys 2003
35Radio Irregularities in Sensor Networks
(Zhou et. al. @ MobiSys 2004)
• Close to ground: high path loss (~1/d^4)• Multipath, radio calibration, antenna position: highly
asymmetric and irregular behavior• Two major causes of asymmetry and irregularity:
– Non-isotropic path losses • Caused by reflection, diffraction and scattering during signal
propagation• Different antenna gains along different propagation
directions because of manufacturing issues
– Non-isotropic sending power• Different battery status due to different environment and
usage, sending power could be different from mote to mote• Slight differences in sensor devices can also result in
variable sending power
36
Example: Signal Strength vs. Direction
• One mote periodically transmits beacons while the others receive and measure the power of the received signal at the same time
Setup
• Received signal strength is stable in each direction over time• Signal strength fluctuates as direction varies
37Example: Communication Range vs.
Direction
• Communication range varies as direction varies under fixed receiver sensitivity
38
Example: Varying Hardware Equipment
• Different batteries and different motes give different sending power
Figure 1
Figure 2
• Figure 1– One mote with different
battery status
• Figure 2– Different motes with same
battery status
39
Radio Irregularity Model
• RIM takes interferences, such as energy loss, background noise and multi-signal interferences, into account
• Degree of irregularity (DOI): The maximum received signal strength percentage variation per unit degree change in the direction of propagation
• Traditional Model– Received Signal Strength = Sending Power – Path Loss + Fading
• New Model– Received Signal = VSP Adjusted Sending Power – DOI Adjusted
Path Loss + Fading– VSP Adjusted Sending Power = Sending Power x (1 + Rand x VSP)
• Random Variable based on Normal distribution
– DOI Adjusted Path Loss = Path Loss x Ki
– Ki = Ki-1 ± Rand x DOI for 0 < i < 360 with K0 = 1• Random Variable based on Weibull distribution
40
Impact on MAC Layer
• Hidden Node Problems• Carrier Sensing
– B can reach C but cannot hear A, but A can reach C. When A and B transmit to C at the same time, packets collide
• Handshaking– A sends RTS and B sends CTS in response, but C cannot hear
either. Possible collision when C starts a transmission• However, DOI and VSP has more significant impact on routing
algorithms
Carrier Sensing Handshaking
41
Impact on Routing Algorithms
• Path-Reversal– Routing is based on the assumption that if there is path from A
to B, there is one in the reversed direction– Not true when dealing with asymmetrical links
• Multi-Round Discovery– Similar to path-reversal, but requires the destination to send a
reply to the source in order to establish a connection – Examples - AODV (Ad-hoc On-demand Distance Vector) and
DSR (Dynamic Source Routing)
• Neighborhood Discovery– Nodes discover neighbors by receiving beacon from neighbors– Prone to failure when links are asymmetric– Example - GF (Geographic Forwarding)– GF takes a big hit in case of asymmetric link because of its
greedy forwarding rule which tends to choose a node near the border
42
Why New Protocols for Sensor Networks?
• Not just MANETs with static nodes!• Several issues
– Severe energy and bandwidth constraints– Large scale– Environmental variance– Different traffic patterns in space and time– Latency constraints– Disruptions– Close coupling of processing and networking– Node identity not relevant– Correlation of data sources
43
MAC
44
Medium Access Control
• Wireless channel is a time-shared medium• Radios transmitting in the same frequency band interfere with
each other – collisions – Other time-shared medium examples: Ethernet
• MAC controls when and how each node can transmit in the wireless channel
• Separation in other dimensions too: frequency, code, space• Important attributes:
– Collision avoidance– Energy efficiency– Scalability and adaptivity (size, density, topology, traffic)– Latency– Fairness– Throughput– Bandwidth utilization
45
Sharing the Link
46
Taxonomy of MAC Protocols
• Random-access vs. Scheduled • Time Slotted vs. Non-slotted• Peer-to-peer vs. Master-slave• MAC level retransmission
47
Scheduled vs. Random Access
Scheduled Protocols Contention Protocols
Collisions No Yes
Energy efficiency Good Need improvement
Scalability and adaptivity Bad Good
Multi-hop communication Difficult Easy
Time synchronization Strict Loose or not required
48
Some Examples
• ALOHA– Random, slot-less or slotted, peer-to-peer
• Send when there is data (pure)• Send in next slot when there is data (slotted)
• CSMA– Random, slot-less, peer-to-peer
• Listen before transmit, send if idle, back-off if busy
• 802.11 infrastructure DCF and ad hoc (CSMA/CA)– Random, slot-less, peer-to-peer
• Listen and reserve before transmit, send if idle, back-off if busy
• 802.11 infrastructure PCF– Scheduled (polling), slot-less, master
• Bluetooth piconets– Scheduled (polling), time-slot (with frequency hopping), master
• TinyOS B-MAC– Random, slot-less, peer-to-peer
49
802.11 MAC
50
802.11 DCF
51
802.11 DCF (contd.)
52
802.11 DCF - Fragmentation
53
802.11 PCF
54
802.11 PCF Burst
55
MAC Impact on Sensor Networks
• Major sources of energy waste• Idle listening when no sensing events, Collisions,
Control overhead, Overhearing
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0 50 100 150 200 250 300
Ave
rage
Dis
sipa
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Ene
rgy
(Jou
les/
Nod
e/R
ecei
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Eve
nt)
Network Size
DiffusionDiffusion
Omniscient MulticastOmniscient MulticastFloodingFlooding
00.0020.0040.0060.0080.01
0.0120.0140.0160.018
0 50 100 150 200 250 300
Ave
rage
Dis
sipa
ted
Ene
rgy
(Jou
les/
Nod
e/R
ecei
ved
Eve
nt)
Network Size
DiffusionDiffusion
Omniscient MulticastOmniscient Multicast
FloodingFlooding
Over 802.11-like MAC Over energy-aware MAC
56
Identifying the Energy Consumers
• • Idle listening consumes bulk of the energy in sensor networks• Need to shutdown the radio
SENSORS
Power consumption of node subsystems
0
5
10
15
20
Power (mW)
CPU TX RX IDLE SLEEP
RADIO
SLEEPIDLERXTX EEEE >>≈≈
57
Ways to Conserve Energy in MAC
• Low duty cycle to reduce idle listening• Effective collision avoidance• Overhearing avoidance• Reducing control overhead
58
Power Management in 802.11 - Basic Idea
59
Power Management in 802.11 - PCF Mode
60
Power Management in 802.11 - DCF Mode
61
WASN Application Characteristics
Sensor CPU Radio
Sensor Node
Sensor
Processor
Radio Tx
Sample rate determined by signal b/w
Sensor duty cycle period determined by latency and dynamics
# of samples determined by sensor characteristics
Rare EVENT
Periodic tasksTriggered EventsLong LifetimeKey design principles
Sleep: majority of the time (>99%)
Wakeup: quickly start processing
Active: minimize work & return to sleep
62
Sensor-MAC (S-MAC) Design(Wei Ye et al. 2002)
• Tradeoffs
• Major components of S-MAC• Periodic listen and sleep• Collision avoidance• Overhearing avoidance• Message passing
Latency
Fairnes
s
Energy
63
Periodic Listen and Sleep
• Problem: Idle listening consumes significant energy– Nodes do not sleep in IEEE 802.11 ad hoc mode
• Solution: Periodic listen and sleep– Turn off radio when sleeping– Reduce duty cycle to ~10% (200 ms on/2s off)– Increased latency for reduced energy
sleeplisten listen sleep
64
Periodic Listen and Sleep
• Schedules can differ
• Preferable if neighboring nodes have same schedule— easy broadcast & low control overhead
Border nodes: two schedules
broadcast twice
Node 1
Node 2
sleeplisten listen sleep
sleeplisten listen sleep
Schedule 2
Schedule 1
65
Coordinating Periodic Listen and Sleep
• Schedule Synchronization – New node tries to follow an existing schedule
– Remember neighbors’ schedules — to know when to send to them
– Each node broadcasts its schedule every few periods of sleeping and listening
– Re-sync when receiving a schedule update
• Periodic neighbor discovery– Keep awake in a full sync interval over long periods
• Listen split in two parts: for SYNC and for RTS/CTS– Data sent in sleep interval once RTS/CTS established
Receiver
Listen
Sleepfor SYNC for RTS for CTS
66
Adaptive Listening
• Reduce multi-hop latency due to periodic sleep• Wake up for a short period of time at end of each
transmission– Reduces latency by at least half
ListenR ListenON
RTSSender
Receiver CTS
Overhearing nodes (ON)
DATA
ACK
Sleep (based on RTS)
Sleep (based on CTS)
Wakes up even though it is not the correct listen-interval
Not all receiver’s next-hop nodes can hear the transmission, if adaptive
67
Collision Avoidance
• Problem: Multiple senders want to talk• Options: Contention vs. TDMA• Solution: Similar to IEEE 802.11 ad hoc mode (DCF)
– Physical and virtual carrier sense
– Randomized backoff time
– RTS/CTS for hidden terminal problem
– RTS/CTS/DATA/ACK sequence
RTSSender
Receiver CTS
Other Sensors
DATA
ACK
NAV (based on RTS)
NAV (based on CTS)
Contend for medium access
defer access
68
Overhearing Avoidance
• Problem: Receive packets destined to others• Solution: Sleep when neighbors talk
– Basic idea from PAMAS (Singh et. al. @ Mobicom 1998)
– But S-MAC only uses in-channel signaling• Who should sleep?
• All immediate neighbors of sender and receiver
• How long to sleep?• The duration field in each packet informs other nodes the sleep interval
69
Message Passing
• Problem: In-network processing requires entire message• Solution: Don’t interleave different messages
– Long message is fragmented & sent in burst– RTS/CTS reserve medium for entire message– Fragment-level error recovery
— extend Tx time and re-transmit immediately• Other nodes sleep for whole message time
Fairnes
s
Energy
Msg-level
latency
70
Message Passing vs. 802.11 fragmentation
Upfront time reservation by duration field
If ACK is not received, give up Tx — fairness
No indication of entire time — other nodes keep listening
RTS 21 ...
...Data 19
ACK 18CTS 20
Data 17
ACK 16
Data 1
ACK 0
• MP
RTS 3 ...
...Data 3
ACK 2CTS 2
Data 3
ACK 2
Data 1
ACK 0
• 802.11
71
TinyOS/Mote Implementation
• Platform: Mica Motes• Topology: 10-hop linear
network
• S-MAC saves a lot of energy compared with a MAC without sleep
0 2 4 6 8 100
5
10
15
20
25
30
Message inter-arrival period (S)
Energy consumption (J)
10% duty cycle without adaptive listen
No sleep cycles
10% duty cycle with adaptive listen
Energy consumption at different traffic load
72
S-MAC Experimental results(implemented on UCB Mica1 Motes)
• Topology and measured energy consumption on source nodes
Source 1
Source 2
Sink 1
Sink 2
• Each source node sends 10 messages — Each message
has 10 fragments x 40B
• Measure total energy— Data + control
+ idle
0 2 4 6 8 10
200
400
600
800
1000
1200
1400
1600
1800Average energy consumption in the source nodes
Message inter-arrival period (second)
Energy consumption (mJ)
802.11-like protocol Overhearing avoidanceS-MAC
Message Inter-arrival period
Energy consumed
73
T-MAC: Timeout MAC
• Drawback of S-MAC: fixed duty cycle– Active (Listen) interval – long enough to handle to highest expected
load
– If message rate is less – energy is still wasted in idle-listening
– Not optimal!
• T-MAC: Adaptive Duty Cyle– A node is in active mode until no activation event occurs for time TA
• Periodic frame timer event, receive, carrier sense, send-done, knowledge of other transmissions being ended
– Communication ~= S-MAC/802.11
– Frame schedule maintenance ~= S-MAC
Active Active Active
Sleep Sleep
TA TATA
74
B-MAC - Low-power Listen Mode
• S-MAC, T-MAC– Significant overhead in synchronizing nodes
• B-MAC design considerations– Simplicity: based on simple CSMA
– Configurable options
– Minimize idle listening
– Based on model of periodic sensor data transfer
• B-MAC components– CSMA without RTS/CTS
– Optional Low-power listening (LPL)
– Optional ACK
75
Low-power Listen
• Determine channel status by quick sampling– Very low overhead on wake-up
Joe Polastre, et al., SenSys’04
76
Low Duty Cycle with LPL
• Nodes periodically sleep and perform LPL• Nodes do not synchronized on listen time• Sender uses a long preamble before each packet to wake up the
receiver
• Shift most burden to the sender• Every transmission wakes up all neighbors
– Presence of chatty neighbor leads to energy drain in dense networks• Preambles can be really long!
≤Constraint: Preamble length
77
S-MAC vs. B-MAC
S-MAC B-MAC
Collision avoidance CSMA/CA CSMA
ACK Yes Optional
Message passing Yes No
Overhearing avoidance Yes No
Listen period Pre-defined + adaptive listen Pre-defined
Listen interval Long Very short
Schedule synchronization Required Not required
Packet transmission Short preamble Long preamble
Code size 6.3KB 4.4KB (LPL & ACK)
78
Time Uncertainty Problem
• Scenario: A and B need to communicate
• Clocks at A and B can drift arbitrarily
• If sleep-listen schedule of these nodes do not intersect, there will be a packet loss
Packet ready@ Tx
B
A
Rx ready
79
Asynchronous Approaches: BMAC, STEM
• Choose preamble such that Rx guaranteed to wake up during preamble– 1B for every 416 s
• For 29B payload– 11.5% duty cycle 250 bytes of preamble– 2.2% duty cycle 1212 bytes of preamble
Packet ready@ Tx
Payload
Rx ready
Preamble
B
A
A
Multiplepackets
80
Synchronous Approaches: {S,T}-MAC
Time-synchronized duty-cycling of nodes.
Guard Band
Packet ready@ Tx
Payload
Rx ready
Preamble
B
A
Periodic time synchronization
• Overhead of periodic synchronization packets– SMAC uses a period of around 15 seconds
81
Coping with Time Uncertainty
Packet ready@ Tx
B
A
{Can we predict and control the drift
to minimize the energy overhead?
82
Key to Energy is Time!
• The greater the time uncertainty between Tx and Rx at the time of packet transmission, the longer the preamble
– Worst case is asynchronous– E.g. BMAC with 29B payload
• 4B for perfect sync• 250B for 11.5%• 1212B for 2.2%• 1B for every 416us
• Reducing time uncertainty– Stable, high quality clock source
• Size, power, cost issues• Even NIST’s chip-scale atomic clock is 75
mW– Time synchronization
• Require additional message exchange to periodically resync
• This overhead can negate energy benefits of uncertainty reduction
Time Uncertainty
Pre
am
ble
Len
gth
4B
1212B
0 0.1s 0.5s
250B11.5% duty cycle
2.22% duty cycle
83
Challenge: Long Term Time Synchronization
• Conventional schemes quite good for instantaneous synchronization
– Few s on motes with simple linear regression
• But different clock drifts cause them to go out of sync
– Need to resynchronize periodically– E.g. 40 s/s, need to resynchronize every 2.5s for
a 100 s uncertainty bound• Hardware time synch too costly
– E.g. 75 mW for NIST chip-scale atomic clock• Need protocol that predicts drift to achieve desired
precision with minimum energy under changing ambient conditions
System Re-synchronization period
Shooter localization system 1 minute
James reserve 5 minute
Great Duck island 10 minutes
SMAC, MAC Sleep time of 100ms to maximum of 2 minutes
FTSP 30s, 5 minutes
84
Rate Adaptive Time Sync (RATS)• Key ideas:
– Focus on long term time sync as opposed to instantaneous time sync– Achieve desired level of uncertainty– Decide maximum possible resynchronization interval– Adapt to ambient conditions
SampleRepository
ModelEstimation
ErrorPrediction
Sampler
Synchronize a pair of nodes A and B.
(TA , TB) ∑=
=K
k
kAkB TT
0
β
Window (W)
FB
FBp TTE −= ˆ Decide new
beaconing time of A
Error Bound (Emax)
Sampling period (S)
Current state of art
85
Implementation on Motes/TinyOS
• 100 B of RAM, 10KB of ROM
• Floating point library 300B of RAM, 5KB of ROM
86
Performance Comparison
Hardware specs FTSP (Vanderbilt) RATS
Drift Estimate Periodic Resync period
Drift Estimate Periodic Resync Period
Average Resync period
5µs/s 18s 2µs/s 45s 20 – 60 min
For an error bound of 90µs
87Performance Comparison: Against an
Oracle Strategy
Better Energy Performance
All existing synchronization schemes will be points on the oracle strategy curve
Better Error Performance
In no scenario does RATS perform worseEnergy gains ~ 1.1x – 12.5xError gains ~ 1.25x – 13.5x
Sampling Period (minutes)
FaultyRatio (%)
88Uncertainty-driven Duty Cycling MAC
(Ganeriwal et. al. @ SenSys 2005)
• Background– Minimum preamble length 4– Extra bytes added for taking care of time uncertainty.
• Fixed Preamble mode– BMAC chooses to use a preamble of x bytes irrespective of
duty-cycle.– Maximum time uncertainty allowed -> (x-4)*byte time.– RATS objective is to achieve this error bound
• Variable Preamble mode– When transmitting packet BMAC ask RATS to estimate the time
uncertainty between the nodes.– Based on this, the preamble size is chosen on the fly!
RATS + BMAC UBMAC
89
Uncertainty-driven B-MAC for Motes
• 35.5% duty cycle, application level packet every 30s• Asynchronous BMAC uses 94B preamble• UBMAC (BMAC+RATS) set to use 6B and RATS tries to keep error bound within 2B = 832us• 24 hour experiment
– BMAC: 2800 packets with 94B preamble– UBMAC: 2800 packets with 6B preamble + 28 RATS packets– Total energy improvement at Tx: 3X– Similar gains at Rx, as it too is on for shorted duration
• RATS is equivalent to having a stable clock source of < 300 nW
90Packet Loss Performance
(24 hr, 35.5% duty cyle)
Packet loss rates
Outdoors
Indoors First Child Second Child Always-on
2.2% 1.95% 1.92%
First Child Second Child Third Child Always-on
2.45% 3.1% 3.45% 2.95%
91
Energy Gains at Tx
• Energy gain increases with lower duty cycle– Uncertainty-based Functionality remains unchanged– Asynchronous Need to use a longer preamble for the worst-case
Event Period (Minutes)
Rel
ativ
e E
nerg
yG
ains
(R
atio
)
Energy gains with uncertainty based approach can be as much as 60x
Similar gains at Rx
92
What about Chip-scale Atomic Clocks?
• Time uncertainty can also be removed by using stable clock sources such as atomic clocks and GPS
• Unfortunately, their power consumption is too high– Although they are more accurate than needed
• RATS is equivalent to a 300nW stable clock source– By comparison, NIST’s chip-scale atomic clock is 75mW– Most GPSs are far inferior
93
802.15.4 MAC
• Three types devices – Network Coordinator
– Full Function Device (FFD)• Can talk to any device, more computing power
– Reduced Function Device (RFD)• Can only talk to a FFD, simple for energy conservation
• CSMA/CA with optional ACKs on data packets• Optional beacons with superframes• Optional guaranteed time slots (GTS), which supports
contention-free access
94802.15.4 MAC Power Reduction Feature:
Optional Superframe
From Callaway @ ACM Sensys 2003
95
802.15.4 Beaconless Mode
• Asymmetrical channel access mode of asymmetrically powered devices
• E.g. wireless light switch operating a lamp– Lamp can be in near-constant receive mode
– Switch stays in standby until pressed by the user
From Callaway @ ACM Sensys 2003
96
CSMA vs. Polling
• For low offered traffic applications, activity associated with polling can create a lower bound on attainable duty cycle and, therefore, power consumption
• In “conventional” CSMA-CA, most power consumption is due to the receiver, due to the long monitoring periods required to support operation during high offered traffic periods
• IEEE 802.15.4 supports a “Battery Life Extension” (BLE) mode, in which the CSMA-CA backoff exponent is limited to the range 0-2
• This greatly reduces receiver duty cycle in low offered traffic applications
From Callaway @ ACM Sensys 2003
97
802.15.4 BLE Mode
From Callaway @ ACM Sensys 2003
98
Topology Management
99
Adaptive Topology
• Can we do more than shut down radio in between transmissions/receptions?
• Can we put nodes to sleep for longer periods of time?
• Goal: – Exploit high density (over) deployment to extend system
lifetime
– Provide topology that adapts to the application needs
– Self-configuring system that adapts to environment without manual configuration
• Recall: STEM, GAF
100Adaptive Topology: First Cut Problem
Description
• Simple Formulation (Geometric Disk Covering)– Given a distribution of N nodes in a plane.– Place a minimum number of disks of radius r (centered on the
nodes) to cover them.– Disk represents the radio connectivity (simple circle model).
• The problem is NP-hard.• Remember: can’t determine connectivity from locations (or vice versa)
101
Trade-off
• How many nodes to activate? – few active nodes:
• distance between neighboring nodes high -> increase packet loss and higher transmit power and reduced spatial reuse;
• need to maintain sensing coverage (see earlier session on coverage/exposure)
– too many active nodes:• at best, expending unnecessary energy;• at worst nodes may interfere with one another by congesting the
channel.
102
Adaptive Topology Schemes
• Basic Problem: Deciding on
- which nodes turn on- when they turn on, and- at what Tx power
…. So that desired network connectivity is maintained.
• Approaches– Location driven
• E.g. GAF
– Connectivity driven• E.g. ASCENT, SPAN
– Data or traffic driven• E.g. STEM
– Asynchronous• E.g. Zheng et. al. (UIUC)
Energy node density Energy latency Energy Tx power
103Location Driven: Geographic Adaptive
Fidelity (GAF) for Energy Density
• Conserve traffic forwarding capacity
• Divide network in virtual grids of size r <= radio_range/sqrt(5)
• Each node in a grid is equivalent from a traffic forwarding perspective
• Keep 1 node awake in each grid at each time
104Connectivity Driven: ASCENT
Energy Density
• The nodes can be in active or passive state.
– Active nodes are part of the topology (or stay awake) and forward data packets (using an orthogonal routing mechanism).
– Nodes in passive state can be sleeping or collecting network measurements. They do not forward any packets.
• Each node measures the number of neighbors and packet loss locally.
• Each node then makes an informed decision to join the network topology or to sleep by turning its radio off.
Test
Passive Sleep
Active
after Tt
after Tp
after Ts
neighbors < NTand• loss > LT• loss < LT & help
neighbors > NT (high ID for ties); orloss > loss T0
NT: neighbor threshold
LT: loss threshold
T?: state timer values (p: passive, s: sleep, t: test)
105Data Driven: STEM Energy Latency
• Nodes put to sleep instead of idle or Rx– Since Rx or idle power ~ Tx power
• Question: how do we wake up a sleeping node?– Low-power Listen!
Sensor-triggered node wakeupWake up the nodes along the path
event
sensor network
user
Zzz
Path nodes need to be woken up
Zzz ZzzZzz
106
How can a Sleeping Node be reached?
Listenf2
Sleep Active
Sleep
time
time
f1
Active mode
Polling mode
Sleep mode
Interference
A B
C
D
• Approach: Each node wakes up occasionally to listen for wake up• Problem: Wake up messages can collide with ongoing data Tx• Solution: Use separate channel (time or frequency) for wake up
Wakeup plane: f1
Data plane: f2
zzzzzzz
107
TxPow
erP
ower
Time
f1
f2Tx /RxSleep
Initiator node
Sleep
Rx
Pow
erP
ower
Time
f1
f2Tx /RxSleep
Target node
STEM: Sparse Topology & Energy Management
108
STEM: Sparse Topology & Energy Management
f1
f1
Target node
Initiator node
Train of beacon packetsTRx
B1B2 1. beacon received
2. beacon acknowledge
109
STEM Performance Analysis
• Setup latency
• Energy savings
232
RxS
TTT
+≈
T
T
E
E Rx≈0
Appropriate choice of interval sizes
Mostly monitoring state: << 1
f1
f2
Wakeup plane
Data plane
Fraction of time in the forwarding state:
Forwarding state Monitoring state
110
0E
E 5.0=
1.0=
01.0=
001.0=
T (s)
STEM-B
Energy versus period for STEM-B
0E
E 5.0=
1.0=
01.0=
001.0=
T (s)
STEM-T
Energy versus period for STEM-T
STEM-T
STEM-B(no
collisions)
T (s)
ST STEM-B(collisions)
Average setup latency per hop versus Wake up period
Energy-Latency Trade-off
Can extend STEM to exploit Latency AND Density
111
Exploiting Density
• Conserve traffic forwarding capacity
• Divide network in virtual grids
• Each node in a grid is equivalent from a traffic forwarding perspective
• Keep 1 node awake in each grid at each time
GAF: Geographic Adaptive Fidelity [Xu2001]
M’ M 1.0 0 0
1.5 0.87 13.7
2.0 1.59 25.0
2.5 2.22 35.0
3.0 2.82 44.3
• GAF reduces the energy by a factor M’
• This factor is a function of the average number of nodes in a grid: M
Me
MM −−
=′1
Average num
ber of neighbors of a nodefor uniformly random
node deployment
112
GAF Energy Savings
1
0
−
⎥⎦
⎤⎢⎣
⎡EE
ππ
5
1
0 1
1
5 −
−
−
⋅≤⎥⎦
⎤⎢⎣
⎡
eE
E
2RA
N
field
π ⋅=
Uniformly random node distribution
x
P(#neighbors = x)
= 10
113
STEM vs. GAF
Rx
S
T
T
STEM
GAF
Leverage latency
Leverage density
Curve of comparable energy savings
114Combined Data and Location/Connectivity
Driven: STEM+GAF
• As in GAF, 1 node is active in each grid
the grid can be considered a virtual node
• Observe: In GAF, the leader has to keep its radio on all the time
• Absence of traffic in the monitoring state not exploited
• This virtual node runs the STEM protocol
• Requires changes in leader election scheme
0E
E
= 4 = 6 = 8
= 92
GAF
STEM-T + GAF
5=GAFT hours
STEM-B/T + GAF
Relative energy saving versus density for TGAF = 5
hours
115Asynchronous Approach for
Energy Latency
• Nodes follow an a listen/sleep cycle
• Problem:– Each node follows a listen/sleep schedule of T slots
– Objective: Minimize ku, kv (energy minimization)– Given: T = schedule duration– Constraint: m = number overlapping slots (delay constraint)– Symmetric design (ku=kv)– Asymmetric design ((kukv)
Sleep time Energy BUT Neighbor Discovery Latency
0 T-1node U
node V
ku=4
activeslots
kv=3
116
Solutions
• Symmetric Design– Every node chooses the same number of active slots AND circular shifts of the same
schedule:
• Asymmetric design– The asynchronous wakeup schedules should be generated every time there is a
topology change inefficient (depends on the topology)– Could be used for heterogeneous networks (powerful/constrained nodes)
124
235
346
457
561
672
713
slot 1 2 3 4 5 6 7
Examples of schedules:(T, k, m)=(7,3,1) (T, k, m)=(73,9,1)
T: schedule lengthk: active slotsm: overlap slots
Tmk ⋅≥
Necessary condition: TmkK ⋅≥⋅
Necessary condition:
117
Implementation Issues
• Slot alignment needs time-sync and slots may shift• Introduce a protocol that allows a node to:
– Discover the state of the neighbor nodes (listen/sleep)– Keep track of the neighbor schedules so that a link can be formed
• Nodes learn other nodes’ schedules and transmit only when recipient is active
Frame structure
I
T
Node U
Node V
V can hear U’s beaconU can hear V’s beacon
Slot duration
Schedule duration
118Power Management with Asynchronous
Wakeup
• Problem: If nodes use the listen periods for packet transmissions then bandwidth is reduced
• Solutions:
– Slot-based power management • Slot-by-slot link reservation when buffer exceeds threshold
– On-demand power management• PS Mode -> Active : communication events• Active -> PS mode : soft state timers
awake sleep Tx/Rx idle
Power Management Policy
PS Mode Active Mode
Wakeup Schedule
119
Higher layers in the next lecture…
