Transcript Distributed System Design from a Sensor Net Perspective David Culler Systems Wireless EmBedded 1/28/2004 Sensor Net Day Systems Moore’s Law – 2x stuff per 1-2 yr Wireless EmBedded.

Distributed System Design from a Sensor
Net Perspective
David Culler
Systems
Wireless
EmBedded
1/28/2004
Sensor Net Day
Systems
Moore’s Law – 2x stuff per 1-2 yr
Wireless
EmBedded
2
log (people per computer)
Systems
Bell’s Law –
new computer class per 10 years
Wireless
EmBedded
Number Crunching
Data Storage
productivity
interactive
• Enabled by technological opportunities
streaming
information
to/from physical
world
• Smaller, more numerous andyear
more intimately connected
• Ushers in a new kind of application
• Ultimately
used in many ways not previously
imagined
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Net Day
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Systems
Making it happen
Wireless
EmBedded
• Move the research from ‘simulations of imagined
problems’ to ‘experience with real ones’
open, widely used HW/SW “close enough” platform
• Pilot applications that show how it might change
the way we do science and engineering
Focus the technology advance
Set the bar on capability
• Tackle the new computer systems challenges
due resource constraints, scale, & embedment
Fundamentally simpler, more robust software structures
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Wireless
Systems
Open Experimental Platform to
Catalyze a Community
EmBedded
Services
Networking
TinyOS
WeC 99
“Smart Rock”
www.tinyos.net
Rene 11/00
Dot 9/01
Mica 1/02
Small
microcontroller
- 8 kb code,
- 512 B data
Simple, low-power
radio
- 10 kb
Designed for
experimentation
-sensor boards
Demonstrate
scale
NEST open exp. platform
128 KB code, 4 KB data
50 KB radio
EEPROM (32 KB)
-power boards
Simple sensors
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DARPA SENSIT,
- Intel
comm accelerators
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Expeditions
Crossbow
- DARPA NEST
512 KB Flash
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Example uses
Systems
Wireless
EmBedded
• Env. Monitoring, Conservation biology, ...
– Precision agriculture, land conservation, ...
– built environment comfort & efficiency ...
– alarms, security, surveillance, treaty verification
...
CENS.ucla.edu
• Civil Engineering: structures response
– condition-based maintenance
– disaster management
– urban terrain mapping & monitoring
• Interactive Environments
– context aware computing, non-verbal
communication
– handicap assistance
» home/elder care
» asset tracking
• Integrated robotics
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Systems
Resolving The Systems Challenge
Wireless
EmBedded
Monitoring & Managing Spaces and Things
applications
data
mgmt
service
network
system
architecture
Comm.
MEMS
sensing
Store
Proc
uRobots
actuate
technology
Miniature,
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low-power connections
Sensor Net Dayto the physical world
Power
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Traditional Systems
Application
Application
User
System
Network Stack
Transport
Threads
Network
Address Space
Data Link
Files
Physical Layer
Drivers
Systems
Wireless
EmBedded
• Well established
layers of abstractions
• Strict boundaries
• Ample resources
• Independent
Applications at
endpoints
communicate pt-pt
through routers
• Well attended
Routers
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by comparison ...
Systems
Wireless
EmBedded
• Highly Constrained resources
– processing, storage, bandwidth, power
• Applications spread over many small nodes
– self-organizing Collectives
– highly integrated with changing environment and network
– communication is fundamental
• Concurrency intensive in bursts
– streams of sensor data and
network traffic
• Robust
– inaccessible, critical operation
• Unclear where the
boundaries belong
– even HW/SW will move
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=> Provide a framework for:
• Resource-constrained
concurrency
• Defining boundaries
• Appl’n-specific processing and
power management
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allow abstractions to emerge
Data proc.
AS Virtual Machine
Timesynch
Aggregate
Localize
Broadcast Collect
Neighborhoods
Power
Mgmt
Network
???
Timers
Store
nbr
Digital
Link
mac
Watchdog
Phy
analog
• Appln Specific VM
• Routing
– Bcast
– Aggregate operation
– Epidemic
Dissemination
• Sleep
• Neighborhood
Scheduler
Transport
Systems
Example 1: Rethinking Across Layers
Wireless
EmBedded
– Link estimation
– Table mgmt
– Reflected tuples
• MAC
Clocks
Flash
–
–
–
–
Backoff
Collision
Recovery
TimeStamp
• Phy
– Energy
– Sampling
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Systems
Example 2: Multihop Routing
Wireless
EmBedded
• Necessity for low-power operation at scale
• Discover connectivity graph
• Determine routing subgraph relative to traffic
pattern
• Route data hop-by-hop
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Example Radio Cells
Wireless
EmBedded
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Discovery & Routes formation
2
Systems
Wireless
EmBedded
2
2
2
1
1
2
0
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Systems
Behavior over Time
Wireless
EmBedded
Est. Link Quality
70-100%
40-70%
0- 40%
Tree Depth
1
2
3
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Systems
What is connectivity?
Wireless
EmBedded
• CS: Ability to correctly receive a large fraction of
transmitted packets
• EE: Signal-to-noise ratio exceeds some
threshold
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Systems
The Amoeboed “cell”
Wireless
EmBedded
Signal
Noise
Distance
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Which node do you route through?
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EmBedded
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Systems
What does this mean?
Wireless
EmBedded
• Always routing through nodes “at
the hairy edge”
– Wherever you set the threshold, the
most useful node will be close to it
• The underlying connectivity graph
changes when you use it
– More connectivity when less
communication
– Discovery must be performed under
load
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Systems
Deeper questions
Wireless
EmBedded
• Localized algorithms: Distributed computation
where each node performs local operations and
communicates within some neighborhood to
accomplish a desired global behavior
– D. Estrin, “21st Century Challenges…”
• It takes energy to maintain ‘structure’ from local
interactions.
• How much?
– To maintain a routing tree?
– To aggregate?
– To disseminate info?
• Compression / reliability, ….
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