Extreme Networked Systems: Large Self-Organized Networks of Tiny Wireless Sensors David Culler Computer Science Division U.C. Berkeley Intel Research @ Berkeley www.cs.berkeley.edu/~culler
Extreme Networked Systems:
Large Self-Organized Networks
of Tiny Wireless Sensors
David Culler Computer Science Division
U.C. BerkeleyIntel Research @ Berkeley
www.cs.berkeley.edu/~culler
8/8/2001 EECS Visions 2
Emerging Microscopic Devices
• CMOS trend is not just Moore’s law
• Micro Electical Mechanical Systems (MEMS)– rich array of sensors are becoming cheap and tiny
• Imagine, all sorts of chips that are connected to the physical world and to cyberspace! LNA
mixerPLL basebandfilters
I Q
• Low-power Wireless Communication
8/8/2001 EECS Visions 3
Disaster Management
Circulatory Net
What can you do with them?
• Embed many distributed devices to monitor and interact with physical world
• Network these devices so that they can coordinate to perform higher-level tasks.
=> Requires robust distributed systems of hundreds or thousands of devices.
Habitat Monitoring
Condition-based
maintenance
8/8/2001 EECS Visions 4
Getting started in the small
• 1” x 1.5” motherboard– ATMEL 4Mhz, 8bit MCU, 512 bytes RAM, 8K pgm flash– 900Mhz Radio (RF Monolithics) 10-100 ft. range– ATMEL network pgming assist– Radio Signal strength control and sensing– I2C EPROM (logging)– Base-station ready (UART)– stackable expansion connector
» all ports, i2c, pwr, clock…
• Several sensor boards– basic protoboard– tiny weather station (temp,light,hum,prs)– vibrations (2d acc, temp, light)– accelerometers, magnetometers, – current, acoustics
8/8/2001 EECS Visions 5
A Operating System for Tiny Devices?
• Traditional approaches– command processing loop (wait request, act, respond)
– monolithic event processing
– bring full thread/socket posix regime to platform
• Alternative– provide framework for concurrency and modularity
– never poll, never block
– interleaving flows, events, energy management
– allow appropriate abstractions to emerge
8/8/2001 EECS Visions 6
Appln = graph of event-driven components
RFM
Radio byte
Radio Packet
UART
Serial Packet
ADC
Temp photo
Active Messages
clocks
bit
by
tep
ac
ke
t
Route map router sensor appln
ap
pli
ca
tio
n
HW
SW
Example: ad hoc, multi-hop routing of photo sensor readings
8/8/2001 EECS Visions 7
Pushing Scale
8/8/2001 EECS Visions 8
Re-explore networking
• Fundamentally new aspects in each level– encoding, framing, error handling
– media access control
– transmission rate control
– discovery, multihop routing
– broadcast, multicast, aggregation
– active network capsules (reprogramming)
– security, network-wide protection
• New trade-offs across traditional abstractions– density independent wake-up
– proximity estimation
– localization, time synchronization
• New kind of distribute/parallel processing
8/8/2001 EECS Visions 9
Larger Challenges
• Security / Authentication / Privacy
• Programming support for systems of generalized state machines
– language, debugging, verification
• Simulation and Testing Environments
• Programming the unstructured aggregates
• Resilient Aggregators
• Understanding how an extreme system is behaving and what is its envelope
– adversarial simulation
• Constructive foundations of self-organization
8/8/2001 EECS Visions 10
To learn more
• http://www.cs.berkeley.edu/~culler
• http://tinyos.millennium.berkeley.edu/
• http://webs.cs.berkeley.edu/
• http://ninja.cs.berkeley.edu/
8/8/2001 EECS Visions 11
Characteristics of the Large• Concurrency intensive
– data streams and real-time events, not command-response
• Communications-centric
• Limited resources (relative to load)
• Huge variation in load
• Robustness (despite unpredictable change)
• Hands-off (no UI)
• Dynamic configuration, discovery– Self-organized and reactive control
• Similar execution model (component-based events)
• Complimentary roles (eyes/ears of the grid)
• Huge space of open problems
...and Small