Design of a Wireless Sensor Network Platform
for Detecting Rare, Random, and Ephemeral Events
Prabal Dutta
with Mike Grimmer (Crossbow),
Anish Arora, Steven Bibyk (Ohio State)
and David Culler (U.C. Berkeley)
April 27, 2005
1
Origins : “A Line in the Sand”
Put tripwires anywhere – in deserts, or other areas where
physical terrain does not constrain troop or vehicle
movement – to detect, classify, and track intruders
April 27, 2005
2
Evolution : Extreme Scale (“ExScal”) Scenarios
ExScal Focus Areas: Applications, Lifetime, and Scale
• Border Control
– Detect border crossing
– Classify target types and counts
• Convoy Protection
– Detect roadside movement
– Classify behavior as anomalous
– Track dismount movements off-road
• Pipeline Protection
– Detect trespassing
– Classify target types and counts
– Track movement in restricted area
April 27, 2005
3
Common Themes
• Protect long, linear structures
• Event detection and classification
– Passage of civilians, soldiers, vehicles
– Parameter changes in ambient signals
– Spectra ranging from 1Hz to 5kHz
• Rare
– Nominally 10 events/day
– Implies most of the time spent monitoring noise
• Random
– Poisson arrivals
– Implies “continuous” sensing needed since event arrivals are
unpredictable
• Ephemeral
– Duration 1 to 10 seconds
– Implies continuous sensing or short sleep times
– Robust detection and classification requires high sampling rate
April 27, 2005
4
The Central Question
How does one engineer a wireless sensor network platform
to reliably detect and classify, and quickly report, rare,
random, and ephemeral events in a large-scale, long-lived,
and wirelessly-retaskable manner?
April 27, 2005
5
Our Answer
•
The eXtreme Scale Mote
– Platform
• ATmega128L MCU (Mica2)
• Chipcon CC1000 radio
– Sensors
•
•
•
•
•
Quad passive infrared (PIR)
Microphone
Magnetometer
Temperature
Photocell
Why this mix? Easy classification:
–
–
–
–
Noise = PIR   MAG   MIC
Civilian = PIR   MAG   MIC
Soldier = PIR  MAG  MIC
Vehicle = PIR  MAG  MIC
– Wakeup
• PIR
• Microphone
– Grenade Timer
• Recovery
– Integrated Design
•
XSM Users
–
–
–
–
–
OSU
Berkeley
UIUC
University of Virginia
MITRE/NGC/others
April 27, 2005
6
The Central Question : Quality vs. Lifetime
How does one engineer a wireless sensor network platform
to reliably detect and classify, and quickly report, rare,
random, and ephemeral events in a large-scale, long-lived,
and wirelessly-retaskable manner?
April 27, 2005
7
Quality vs. Lifetime : A Potential Energy Budget Crisis
• Quality
– High detection rate
– Low false alarm rate
– Low reporting latency
• Lifetime
– 1,000 hours
– Continuous operation
• A potential budget crisis
– Processor
• 400% (24mW)
– Radio
• 400% (24mW on RX)
• 800% (48mW on TX)
• 6.8% (411W on LPL)
– Passive Infrared
• 15% (880W)
– Acoustic
• Limited energy
– Two ‘AA’ batteries
– < 6WHr capacity
– Average power < 6mW
April 27, 2005
• 29% (1.73mW)
– Magnetic
• 323% (19.4mW)
• Always-on requires
~1200% of budget
8
Quality vs. Lifetime : Duty-Cycling
Processor and radio
• Has received much attention in the literature
• Processor: duty-cycling possible across the board
• Radio: LPL with TDC = 1.07 draws  7% of power budget
– Radio needed to forward event detections and meet latency
April 27, 2005
9
Quality vs. Lifetime : Sensor Operation
Startup Latency
(with respect to event duration)
Power Consumption
(with respect to budget)
Short
(<< Tevent)
Medium
(< Tevent)
Low
Medium
High
(<< Pbudget)
(< Pbudget)
( Pbudget)
Duty-cycle
or
Always-on
Duty-cycle
Duty-cycle
Duty-cycle
or
Always-on
?
?
Always-on
?
Unsuitable
Long
( Tevent)
April 27, 2005
10
Quality vs. Lifetime : Sensor Selection
Key Goals: low power density, simple discrimination, high SNR
2,200 x difference!
Power density may be a more important metric than current consumption
April 27, 2005
11
Quality vs. Lifetime : Passive Infrared Sensor
• Quad PIR sensors
–
–
–
–
Power consumption: low
Startup latency: long
Operating mode: always-on
Sensor role: wakeup sensor
April 27, 2005
12
Quality vs. Lifetime : Acoustic Sensor
• Single microphone
– Power consumption: medium (high with FFT)
– Startup latency: short (but noise estimation is long)
– Operating mode: duty-cycled “snippets” or triggered
April 27, 2005
13
Quality vs. Lifetime : Magnetic Sensor
• Magnetometer
– Power consumption: high
– Startup latency: medium (LPF)
– Operating mode: triggered
April 27, 2005
14
Quality vs. Lifetime : Passive Vigilance
Energy-Quality Hierarchy
Low
High
Energy
Usage
False
Alarm
Rate
High
•
•
•
Multi-modal, reasonably lowpower sensors that are
Duty-cycled, whenever
possible, and arranged in an
Energy-Quality hierarchy
with low (E, Q) sensors
Triggering higher (E, Q)
sensors, and so on…
Low
Trigger network includes hardware wakeup, passive infrared,
microphone, magnetic, fusion, and radio, arranged hierarchically
Nodes: sensing, computing, and communicating processes
Edges: < E,  PFA>  <  E,  PFA>
April 27, 2005
15
Quality vs. Lifetime : Energy Consumption
• How to Estimate Energy Consumption?
– Power = idle power + energy/event x events/time
– Estimate event rate probabilistically: p(tx) =
from ROC curve and decision threshold for H0 & H1
• How to Optimize Energy-Quality?
– Let x* = (x1*, x2*,..., xn*) be the n decision boundaries
between H0 & H1. for n processes. Then, given a set of
ROC curves, optimizing for energy-quality is a matter of
minimizing the function f(x*) = E[power(x*)] subject to the
power, probability of detection, and probability of false
alarm constraints of the system.
April 27, 2005
16
The Central Question : Engineering Considerations
How does one engineer a wireless sensor network platform
to reliably detect and classify, and quickly report, rare,
random, and ephemeral events in a large-scale, long-lived,
and wirelessly-retaskable manner?
April 27, 2005
17
Engineering Considerations: Wireless Retasking
•
Wireless multi-hop programming
is extremely useful, especially for
research
•
But what happens if the program
image is bad?
No protection for most MCUs!
•
Manually reprogramming 10,000
nodes is impossible!
•
Current approaches provide
robust dissemination but no
mechanism for recovering from
Byzantine programs
April 27, 2005
18
Engineering Considerations: Wireless Retasking
• No hardware protection
• Basic idea presented by
Stajano and Anderson
• Once started
– You can’t turn it off
– You can only speed it up
• Our implementation:
April 27, 2005
19
Engineering Considerations: Logistics
• Large scale = 10,000 nodes!
• Ensure fast and efficient human-in-the-loop ops
– Highly-integrated node
• Easy handling (and lower cost)
– Visual orientation cues
• Fast orientation
– One-touch operation
• Fast activation
– One-listen verification
• Fast verification
• Some observations
– One-glance verification
• Distracting, inconsistent, time-consuming
– Telescoping antenna
• “Accidental handle”
April 27, 2005
20
Engineering Considerations: Packaging
April 27, 2005
21
Evaluation
• Over 10,000 XSM nodes shipped
• 983 node deployment at Florida AFB
• Nodes
–
–
–
–
Survived the elements
Successfully reprogrammed wirelessly
Reset every day by the grenade timer
Put into low-power listen at night for operational reasons
• Passive vigilance was not used
• PIR false alarm rate higher than expected
– 1 FA/10 minutes/node
– Poor discrimination between person and shrubs
April 27, 2005
22
Conclusions
• Passive vigilance architecture
–
–
–
–
Energy-quality tradeoff
Beyond simple duty-cycling
Extend lifetime significantly (72x compared to always-on)
Optimize energy, quality, or latency
• Scaling Considerations
–
–
–
–
Wirelessly-retaskable
Highly-integrated system
One-touch
One-listen
• DARPA classified the project effective 1/31/05
• Crossbow commercialized XSM (MSP410) on 3/8/05
April 27, 2005
23
Future Work
• “Perpetual” Deployment
– Evaluate year-long deployment
– 1,000 node sensor network
– Areas surrounding Berkeley
• Trio Mote
–
–
–
–
Telos platform
XSM sensor suite
Grenade timer system
Prometheus power system
April 27, 2005
24
Closing Thoughts
Data Collection
vs.
Event Detection
Phenomena Omni-chronic
Signal Reconstruction
Reconstruction Fidelity
Data-centric
Data-driven Messaging
Periodic Sampling
High-latency Acceptable
Periodic Traffic
Store & Forward Messaging
Aggregation
Absolute Global Time












Rare, Random, Ephemeral
Signal Detection
Detection and False Alarm Rates
Meta-data Centric (e.g. statistics)
Decision-driven Messaging
Continuous “Passive Vigilance”
Low-latency Required
Bursty Traffic
Real-time Messaging
Fusion, Classification
Relative Local Time
April 27, 2005
25
Discussion
April 27, 2005
26
Deconstructing Startup Latency
• Low bandwidth sensors
– Humidity
– Temperature
• Large time-constant analog filtering circuits
– PIR band pass filter
– Magnetometer anti-aliasing low pass filter
• Analog filtering is easy on the energy budget
• If analog filtering (e.g. anti-aliasing) required
– Either
• Decouple sensing and signal condition
• Duty-cycle sensor, T/H sensor output, analog always-on
– Or
• Use sensing hierarchy with low-quality, low-power sensors
triggering high-quality, high-power sensors
April 27, 2005
27
Common Themes
• Event detection
– Passage of civilians, soldiers, vehicles
– Parameter changes in ambient signals
– Spectra ranging from 1Hz to 5kHz
• Large scale
– Long, linear structures
– Requires 1,000s of nodes for coverage
• Long lifetime
– Network must last for a long period of time
April 27, 2005
28
Quality vs. Lifetime : Passive Vigilance
•
•
•
•
Multi-modal, reasonably low-power sensors that are
Duty-cycled, whenever possible, and arranged in an
Energy-Quality hierarchy with low (E, Q) sensors
Triggering higher (E, Q) sensors, and so on…
April 27, 2005
29
Quality vs. Lifetime : Duty-Cycling
Sensors
• Acoustics: duty-cycling possible for “periodic snippets”
• Magnetic: duty-cycling impossible (Poweravg, fs and Tstartup conflict)
• Infrared: duty-cycling impossible (Tstartup too big, but not needed)
April 27, 2005
30
Differing Energy Usage Patterns
April 27, 2005
31
Quality vs. Lifetime : Passive Vigilance
Energy-Quality Hierarchy
Low
High
Energy
Usage
• Multi-modal, low-power sensors
that are
• Duty-cycled, where possible, and
arranged in an
• Energy-Quality hierarchy with low
(E, Q) sensors
• Triggering higher (E, Q) sensors,
and so on…
False
Alarm
Rate
High
•
•
•
April 27, 2005
Low
Trigger network includes hardware
wakeup, passive infrared, microphone,
magnetic, fusion, and radio, arranged
hierarchically
Nodes: sensing, computing, and
communicating processes
Edges: < E,  PFA>  <  E,  PFA>
32
Requirements (of the hardware platform)
• Functional
– Detection, Classification (and Tracking) of:
Civilians, Soldiers and Vehicles
• Reliability
– Recoverable: Even from a Byzantine program image
• Performance
–
–
–
–
Intrusion Rate: 10 intrusions per day
Lifetime: 1000 hrs of continuous operation (> 30 days)
Latency: 10 – 30 seconds
Coverage: 10km^2 (could not meet given constraints)
• Supportability
– Adaptive: Dynamic reconfiguration of thresholds, etc.
April 27, 2005
33
XSM RF Performance
April 27, 2005
34
Genesis: The Case for a New Platform
• Cost
– Eliminate expensive parts from BOM
– Eliminate unnecessary parts from BOM
– Optimize for large quantity manufacturing and use
•  Network Scale by 100x (10,000 nodes)
– Reliability: How to deal with 10K nodes with bad image
•  Detection range by 6x (10m)
– New sensors to satisfy range/density/cost tradeoff
•  Lifetime 8x (720hrs  1000hrs)
–
–
–
–
Magnetometer: Tstartup = 40ms, Pss = 18mW
UWB Radar: Tstartup = 30s, Pss = 45mW
Optimistic lifetime: 6000mWh / 63mW < 100 hrs
Must lower power
• Radio
– Fix anisotropic radiation and impedance mismatch
April 27, 2005
35
Hardware Evolution
Telos =
Low-power CPU +
802.15.4 Radio +
Easy to use
Sleep-Wakeup-Active
MICAz
MICA2 CC1000 +
802.15.4 Radio
Sleep-Wakeup-Active
April 27, 2005
XSM
MICA2 +
Improved RF +
Low-power sensing +
Recoverability
Passive Vigilance-Wakeup-Active
XSM2
XSM +
Improvements +
Bug Fixes
36
Sensor Suite
• Passive infrared
–
–
–
–
–
Long range (15m)
Low power (10s of micro Watts)
Wide FOV (360 degrees with 4 sensors)
Gain: 80dB
Wakeup
• Microphone
–
–
–
–
LPF: fc = 100Hz – 10kHz
HPF: fc = 20Hz – 4.7kHz
Gain: 40dB – 80dB (100-8300)
Wakeup
• Magnetometer
– High power, long startup latency
– Gain: 86dB (20,000)
April 27, 2005
37