Slide 1Origins : “A Line in the Sand”Evolution : Extreme Scale (“ExScal”) ScenariosCommon ThemesThe Central QuestionOur AnswerThe Central Question : Quality vs. LifetimeQuality vs. Lifetime : A Potential Energy Budget CrisisQuality vs. Lifetime : Duty-CyclingQuality vs. Lifetime : Sensor OperationQuality vs. Lifetime : Sensor SelectionQuality vs. Lifetime : Passive Infrared SensorQuality vs. Lifetime : Acoustic SensorQuality vs. Lifetime : Magnetic SensorQuality vs. Lifetime : Passive VigilanceQuality vs. Lifetime : Energy ConsumptionThe Central Question : Engineering ConsiderationsEngineering Considerations: Wireless RetaskingSlide 19Engineering Considerations: LogisticsEngineering Considerations: PackagingEvaluationConclusionsFuture WorkClosing ThoughtsDiscussionSep 29, 2005 1Design of a Wireless Sensor Network Platformfor Detecting Rare, Random, and Ephemeral EventsPrabal Duttawith Mike Grimmer (Crossbow), Anish Arora, Steven Bibyk (Ohio State)and David Culler (U.C. Berkeley)Sep 29, 2005 2Origins : “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 intrudersSep 29, 2005 3Evolution : Extreme Scale (“ExScal”) Scenarios•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 areaExScal Focus Areas: Applications, Lifetime, and ScaleSep 29, 2005 4Common 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 rateSep 29, 2005 5The Central QuestionHow 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?Sep 29, 2005 6Our Answer•The eXtreme Scale Mote–Platform•ATmega128L MCU (Mica2)•Chipcon CC1000 radio–Sensors•Quad passive infrared (PIR)•Microphone•Magnetometer•Temperature•Photocell–Wakeup•PIR•Microphone–Grenade Timer•Recovery–Integrated Design•XSM Users–OSU, Berkeley, MIT, UIUC, UVa, Vanderbilit–MITRE/NGC/Kestrel/SRI–Others (now sold by Xbow)Why this mix? Easy classification:–Noise = PIR MAG MIC–Civilian = PIR MAG MIC–Soldier = PIR MAG MIC–Vehicle = PIR MAG MICSep 29, 2005 7The Central Question : Quality vs. LifetimeHow 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?Sep 29, 2005 8Quality vs. Lifetime : A Potential Energy Budget Crisis•Quality–High detection rate–Low false alarm rate–Low reporting latency•Lifetime–1,000 hours–Continuous operation•Limited energy–Two ‘AA’ batteries–< 6WHr capacity–Average power < 6mW•A potential budget crisis–Processor•400% (24mW)–Radio•400% (24mW on RX)•800% (48mW on TX)•6.8% (411W on LPL)–Passive Infrared•15% (880W)–Acoustic•29% (1.73mW)–Magnetic•323% (19.4mW)•Always-on requires ~1200% of budgetSep 29, 2005 9Quality vs. Lifetime : Duty-CyclingProcessor 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 latencySep 29, 2005 10Quality vs. Lifetime : Sensor OperationLow(<< Pbudget)Medium(< Pbudget)High( Pbudget)Short(<< Tevent)Duty-cycleorAlways-onDuty-cycle Duty-cycleMedium(< Tevent)Duty-cycleorAlways-on? ?Long( Tevent)Always-on ? UnsuitablePower Consumption(with respect to budget)Startup Latency(with respect to event duration)Sep 29, 2005 11Quality vs. Lifetime : Sensor SelectionKey Goals: low power density, simple discrimination, high SNR2,200 x difference!Power density may be a more important metric than current consumptionSep 29, 2005 12Quality vs. Lifetime : Passive Infrared Sensor•Quad PIR sensors–Power consumption: low–Startup latency: long–Operating mode: always-on–Sensor role: wakeup sensorSep 29, 2005 13Quality 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 triggeredSep 29, 2005 14Quality vs. Lifetime : Magnetic Sensor•Magnetometer–Power consumption: high–Startup latency: medium (LPF)–Operating mode: triggeredSep 29, 2005 15Quality vs. Lifetime : Passive Vigilance•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>FalseAlarmRateEnergyUsageHighLowLowHighEnergy-Quality HierarchyMulti-modal, reasonably low-power sensors that areDuty-cycled, whenever possible, and arranged in anEnergy-Quality hierarchy with low (E, Q) sensorsTriggering higher (E, Q) sensors, and so on…Sep 29, 2005 16Quality 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.Sep 29, 2005 17The Central Question : Engineering ConsiderationsHow does one engineer a wireless sensor network platform to reliably detect and classify, and
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