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Networks of Tiny Devices embedded in the Physical World

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Title: Networks of Tiny Devices embedded in the Physical World


1
Networks of Tiny Devices embedded in the Physical
World
  • David Culler
  • Computer Science Division
  • U.C. Berkeley
  • www.cs.berkeley.edu/culler
  • Intel Research
  • Berkeley

2
Technology Push
  • Complete network embedded systems going
    microscopic

Power
3
Application Pull
  • Complete NW embedded systems going microscopic
  • Huge space of new applications

Monitoring Managing Spaces
Ubiquitous computing
4
Bridging the Technology-Application Gap
  • Power-aware, communication-centric node
    architecture
  • Tiny Operating System for Range of
    Highly-Constrained Application-specific
    environments
  • Network Architecture for vast, self-organized
    collections
  • Programming Environments for aggregate
    applications in a noisy world
  • Distributed Middleware Services (time, trigger,
    routing, allocation)
  • Techniques for Fine-grain distributed control
  • Demonstration Applications

5
A de facto platform for EmNets
  • Developed a series of wireless sensor devices
  • TinyOS concurrency framework
  • Messaging Model
  • Networking stacks (RF and Serial)
  • Multihop routing
  • Several Key components
  • sensing, logging, data filters, broadcast
  • Simulation tools
  • DARPA NEST OEP

6
Many Research Groups on board
  • UCB
  • NEST
  • SensorWeb
  • Blackout
  • Glaser structures
  • CBE
  • BFD
  • BRWC
  • UCLA
  • USC
  • Rutgers winlab
  • Intel
  • Bosch
  • Crossbow
  • U Wash
  • Rutgers
  • UIUC
  • NCSA
  • U Virginia
  • Ohio State
  • UCSD
  • Dartmouth
  • MIT
  • Accenture
  • and soon many more

7
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
  • gt allow appropriate abstractions to emerge

8
Tiny OS Concepts
  • Scheduler Graph of Components
  • constrained two-level scheduling model threads
    events
  • Component
  • Commands,
  • Event Handlers
  • Frame (storage)
  • Tasks (concurrency)
  • Constrained Storage Model
  • frame per component, shared stack, no heap
  • Very lean multithreading
  • Efficient Layering

Events
Commands
send_msg(addr, type, data)
power(mode)
init
Messaging Component
Internal State
internal thread
TX_packet(buf)
Power(mode)
TX_packet_done (success)
init
RX_packet_done (buffer)
9
Application Graph of Components
Route map
router
sensor appln
application
Active Messages
Radio Packet
Serial Packet
packet
Temp
photo
SW
Example ad hoc, multi-hop routing of photo
sensor readings
HW
UART
Radio byte
ADC
byte
3450 B code 226 B data
clocks
RFM
bit
Graph of cooperating state machines on shared
stack
10
Demonstration applications
  • 29 Palms
  • Cory Hall network
  • ½ million packets over 3 weeks
  • Surge network and environment display
  • 800 node ad hoc network
  • CBE
  • Glaser Shakes
  • Granlibakken retreat watcher
  • Robomote
  • gt continued application focus
  • more real and long lived
  • more dynamics
  • extract architecture and create framework

11
Example TinyOS study
  • UAV drops 10 nodes along road,
  • hot-water pipe insulation for package
  • Nodes self-configure into linear network
  • Synchronize (to 1/32 s)
  • Calibrate magnetometers
  • Each detects passing vehicle
  • Share filtered sensor data with 5 neighbors
  • Each calculates estimated direction velocity
  • Share results
  • As plane passes by,
  • joins network
  • upload as much of missing dataset as possible
    from each node when in range
  • 7.5 KB of code!
  • While servicing the radio in SW every 50 us!

12
Structural performance due to multi-directional
ground motions (Glaser CalTech)
Mote infrastructure
  • .

Mote Layout
14
5  
15
15
13
6  
12
9  
11
8  
Comparison of Results
Wiring for traditional structural
instrumentation truckload of equipment
13
Cory Energy Monitoring/Mgmt System
  • 50 nodes on 4th floor
  • 5 level ad hoc net
  • 30 sec sampling
  • 250K samples to database over 6 weeks

14
Energy Monitoring Network Arch
sensor net
control net
802-11
telegraph
PC
PC
modbus
scada term
UCB power monitor net
Browser
15
Wealth of Research Challenges
  • Large numbers of highly constrained (energy
    capability), connected devices
  • able to be casually deployed in infrastructure
    (existing or in design)
  • imperfect operation and reliability
  • operating in aggregate
  • New family of issues across all the layers

application
service
prog / data model
network
mgmt / diag / debug
algorithm / theory
system
architecture
technology
16
Example Networking
  • Hands-on Experience with Large Networks of Tiny
    Network sensors
  • intense constraints, freedom of abstraction
  • Re-explore entire range of networking issues
  • encoding, framing, error handling
  • media access control, transmission rate control
  • discovery, multihop routing
  • broadcast, multicast, aggregation
  • active network capsule (reprogramming)
  • localization, time synchronization
  • security, network-wide protection
  • density independent wake-up and proximity est.
  • Fundamentally new aspects in each

17
Simple Epidemic Algorithm Schema
  • One (multicast) message handler
  • if (new mcast) then
  • take local action
  • retransmit modified request
  • Examples Network wakeup, command propagation
  • Build spanning tree
  • record parent
  • Naturally adapts to available connectivity
  • Minimal state and protocol overhead
  • gt surprising complexity in this simple mechanism

18
Network Discovery Radio Cells
19
Network Discovery
20
Controlled Empirical Study
  • Experimental Setup
  • 13x13 grid of nodes
  • separation 2ft
  • flat open surface
  • Identical length antennas, pointing vertically
    upwards.
  • Fresh batteries on all nodes
  • Identical orientation of all nodes
  • The region was clean of external noise sources.
  • Range of signal strength settings
  • Log many runs

21
Example epidemic tree formation
22
Final Tree
23
Power Laws ?
  • Most nodes have very small degree (ave .92)
  • Some have degree 15 of the population
  • Few large clusters account for most of the edges

24
Open Territory gt Many Children
  • Example Level 1

25
Open Territory gt Many Children
  • Example Level 2 variation in distance

26
Open Territory gt Many Children
  • Example Level 3 long links

27
Understanding Connectivity
  • 16 transmit power settings
  • For each transmit power setting, each node
    transmits 20 packets.
  • Receivers log successfully received packets.
  • Nodes transmit one after the other in a
    token-ring fashion
  • No collisions.
  • Contour plot show probability of reception from
    center node
  • Define range a radius where 75 of enclosed
    nodes receive 75 of packets
  • Often good nodes at a distance

28
Link symmetry in open environment
  • Asymmetric Link Greater than 65 successful
    reception in one direction and less than 25
    successful reception in the other direction
  • Symmetric Link Greater than 65 successful
    reception in both directions
  • others are bad links

29
Importance of Asymmetric Links
  • 10-25 asymmetric links.
  • Many asymmetric links are long links
  • asymmetric long links symmetric long
    links
  • Why are long links useful?
  • Beacon-based Routing Long links can be used to
    build low-depth routing trees
  • Diffusion short routing paths
  • Protocol design
  • When to confirm bidirectionality?

30
Collisions are primary factor
  • Nodes out of range may have overlapping cells
  • hidden terminal effect
  • Collisions gt these nodes hear neither parent and
    become stragglers
  • As the tree propagates
  • folds back on itself
  • rebounds from the edge
  • picking up these stragglers.
  • This effect was seen in many experiments

31
Stragglers
  • significant fraction of links point backwards

32
Key Experience
  • Really good at building tinyOS subsystems
  • non-blocking, split-phase event structures
  • Internalized the state of constant change
    paradigm
  • ex maintain routing tree by constantly
    rebuilding it
  • soft state that is always suspect
  • simple one-way protocols
  • Operating in the aggregate
  • Simple mechanisms to accomplish large goals
  • MAC, ATC
  • Out of the box on networking abstractions
  • Low-power listen, wake-up, statistical sampling,
    weighted aggregation
  • Understanding of large scale dynamics

33
Rich set of additional challenges
  • Efficient and robust security primitives
  • Application specific virtual machines
  • Time space information in every packet
  • Density independent wake-up, aggregation
  • sensor gt can use radio in analog mode
  • Resilient aggregators
  • Programming support for systems of generalized
    state machines
  • Programming the unstructured aggregate
  • SPMD, Data Parallel, Query Processing, Tuples
  • Understanding how an extreme system is behaving
    and what is its envelope
  • adversarial simulation
  • Self-configuring, self-correcting systems

34
The Law of Miniaturization
Integration
Log R
Mainframe
99
Time
  • Each major generation is increasingly smaller,
    more deeply interactive, arrives when previous is
    at its strength
  • Vast majority of computing will be small,
    embedded, devices connected to the physical world
  • actually the case today, but
  • not connected to us, the web, or each other
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