the university of iowa. copyright© 2005 a. kruger, r. abel, c. mueller, m. karson 1 introduction to...
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1The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Introduction to Wireless Sensor Networks
Smart Dust
4 April 2005
2The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Imagine if you will…• Two opposing military forces, Alpha and
Omega, are separated by a portion of jungle.
• Each wants to locate and identify enemy positions and movements.
α
Ω
• Alpha wants a safer, more efficient means of performing reconnaissance– Human resources for intelligence
gathering are non-optimal• Costly
– Money– Human life
• Human error• Non-persistent
3The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Deployment• Army Alpha deploys an unmanned aerial vehicle
– Ejects tens of thousands of various kinds of rice sized motes
• Terrestrial based• Air based• Water based α
Ω
• Motes automatically form a sensor field– Light, temperature,
vibration, radar, magnetic, acoustic, seismic or a miniature camera.
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4The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Effect of Sensor Network• Army Omega dispatches intelligence
officers and equipment into sensor field
α
Ωαα α
αα α
α
α
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αα α
α
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Ω
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Ω
5The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
What is Smart Dust?• Cute name for a network of miniscule motes
– Term “smart” comes from abilities of individual motes as well as overall function of network
– Term “dust” comes from the goal of packaging a fully functional mote in a 1mm3 package
• Project started at the University of California at Berkeley– Funded by DARPA (Defense Advanced Research
Projects Agency)• Most research aimed at military and defense applications
6The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Vision• Think pixie dust - Scatter hundreds of
sensors which are nearly un-noticeable
• The size of a grain of sand complete with sensors, CPU, receiver, transmitter, antenna and a power supply
• Communication ranges of 1000 ft. or more
7The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Long Term Goals of Project• Autonomous sensing and communications in 1mm3
• Optimize every aspect of WSN– Battery life ( several years ~5 )– Size (1mm3)
• Contains all elements of the mote– Range
• Some sources predict up to 1 km– Processing power
• On board motes• In networking messaging• Billions of computations requiring only picowatts (10-12)
– Communications• Laser
– Power Consumption– Deployment
• “Floating” motes• UAV deployment
8The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
History• Invented by Kris Pister (University of California,
Berkley) in 1992• Smart Dust started as a joke when everyone was
talking about smart homes, smart buildings, smart bombs…
• Smart Dust was the start of WSNs– In 1994 Pister started his research on Smart Dust and began
developing Motes (Hardware)– ~2001, Jason Hill, and David Culler (both at Berkley) worked
together to develop TinyOS for Pisters hardware. The resulting mote was called: MICA
– [TinyOS let] the mote’s hardware perform only critical functions, which in turn extends the mote’s lifetime
– “It’s all about energy.” (Pister)
• Partner in Dust Inc with Jason Hill (2002).
9The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Are we there yet?• Short answer, not quite
– Minute motes have been developed in academic labs
– Larger motes have been used in WSNs
• How close?– Dust™ Networks is trying to produce
practical motes that are approaching the size of an Aspirin pill
– Package size seems to be main hurdle
10The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Problems with Size• Package size
– Need to integrate sensor, CPU, transmitter, receiver, antenna onto a single chip
– Currently size is about 5 mm cube– Dust Inc mote is 1 inch square
11The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
A case study SPEC
• The first Single Chip Mote– 2mm2.5mm– AVR-like RISC core– 3k memory– 8-bit on chip ADC– FSK transmitter (19,200 kbps @ 40 ft)– SPI programming
• Serial Peripheral Interface (For in-system programming)
– RS232 compatible UART– 4-bit input port, 4-bit output port– $0.30 in quantity
12The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
CPU Size/Power Considerations• RISC processors
– employed due to their small die size, and their ability to run in low power modes.
– Code density is of crucial importance• The ARM7TDMI is a 32 bit processor with an additional 16
bit instruction set– The instruction set can be switched by the software to adapt to
current circumstances.
– Power Saving Solutions• Active
– Fixed Frequency
– Frequency Scaling
– Dynamic Voltage Scaling (DVS)
• Power Saving (i.e. sleep, hibernate…)
13The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Problems with Programming• Mass programming
– Smart Dust networks may involve thousands of nodes
– Programming them individually is not practical
• Embedded systems solution– Update firmware
• Wirelessly• Automatically• When update available
14The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Problems with Cost• Manufacturing costs increase as size
decreases with computer chips
• Large scale networks– The cost of each mote must be very small
for costs of a practical system to remain realistic
– Predictions are $1/mote within 5 years
15The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Power Consumption Solutions• Ultralow-Energy ADC
– Sampling Rate of 100 kHz– Power dissipation is 3.1 μW– Standby power is 70 pW– Energy per 8-bit sample is 31 pJ
• 1 kWH = 3.6 million J
– Die area is 0.053mm2
• Used onboard mote shown in previous
16The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Zero Power Communication• Optical communication is possible using Microactuators
(MEMS) (Karakehayov).– Active-Steered Laser Systems
• Needs power to generate a beam– Passive reflective systems
• Can modulate an existing beam using very little power
• Can be done with a Corner Cube
Retroreflector (CCR), three mutually orthogonal mirrors
• Modulation is accomplished by slightly turning a mirror such that the light is no longer reflected towards the information sink
• Mirror rotation can be accomplished 1000 times per second at a cost of less than one nanoJoule per transition.
• CCRs can be roughly oriented using a magnetic compass
17The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
The Sleep-Awake Protocol• Uses 2 Modes of Laser Communication
– Broadcast Beacon Mode (low energy short length communication)
– Point Directed Mode (data transmission)
• Assumptions– No geolocation capabilities assumed (GPS)– No communication (transmitted or received)
during sleep cycle, sensors may be active
18The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
The Protocol•Search Phase: Uses a periodic low
energy broadcast of a beacon of angle towards the wall in order to discover a particle nearer to the Wall than itself.
•Direct Transmission Phase: 2 Sends info( ) to 3 via a direct line (laser) and sends a success message to 1 (i.e. the particle that it received the information from).
•Backtrack Phase: If the Search Phase fails to discover a particle nearer to ,then sends a fail message to .
19The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Analysis• This Technique is quite new and a
thorough comparison is not available.
• BUT– Sparse Topology and Energy Management
(STEM) uses a similar technique (actively puts nodes to sleep) and performs nearly two orders of magnitude better then Sensor Networks without Topology Management
20The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Possible Applications• Military applications
– Remote vehicle & personnel sensing/monitoring
– Missile guidance
• Civilian applications– Ambient environment monitoring– Long range, ubiquitous communications– Power grid monitoring and maintenance
• Boost power transmission
21The University of Iowa. Copyright© 2005 A. Kruger, R. Abel, C. Mueller, M. Karson
Sources• Scott, M.D., Boser, B.E., Pister, K.S.J., “An ultralow-energy ADC
for Smart Dust”, IEEE Journal of Solid-State Circuits, V. 38, Issue 7, July 2003, pgs 1123-1129
• Karakehayov, Z.; “Zero-power design for Smart Dust networks”, Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium, Volume 1, 10-12 Sept. 2002 Page(s):302 - 305 vol.1
• Chatzigiannakis, I.; Nikoletseas, S., “A sleep-awake protocol for information propagation in smart dust networks”, Parallel and Distributed Processing Symposium, 2003. Proceedings. International 22-26 April 2003.
• Frost Gorder, P., “Sizing up smart dust”, Computing in Science
& Engineering, Volume 5, Issue 6, Nov.-Dec. 2003 Page(s):6 - 9