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Embedded Systems and Sensor Networks
Pete Broadwell<[email protected]>
Joe Polastre<[email protected]>
Introduction
Network-enabled embedded systems currently are
approaching widespread use. We make a case for the
“access network” approach to converging such networks with larger networks, and present
wireless sensor networks as a case study.
Talk Outline
• Introduction to embedded systems– Design considerations– Networking options
• Strategies for network convergence– Access networks– Service discovery
• Sensor networks: a case study– Operating environment– Networking implementation– Supported applications
What is an embedded system?
• Hardware and software components
• Part of a larger system
• Operates without human intervention
• Example:– Single-board microcomputer– Software stored in ROM– Runs special-purpose app until turned off
Tiny Webserver
Types of embedded systems
• Sensors*– Collect data– Passive interaction with environment
• Actuators*– Control machines– May introduce changes into environment
• Beacons*– No sensing or actuation– Can alert other sensors to changes in environment
* All can benefit from being networked!
Why the interest in embedded systems?
• Embedded systems are becoming ubiquitous– Moore’s Law: more computing power in smaller devices
• Example: laboratory temperature alarmTraditional electronics:
+5V
+5V
comparator
thermistor
speaker
Embedded devices:temperature sensor
controlling ROM
comm. bus interface
environment monitor
comm. bus
Why network them?
• Some embedded systems have no use for network connectivity– Example: my car’s ABS (or do they?)
• Others benefit from network access– Example: refrigerator orders milk when it’s low
• It’s easy: ubiquitous large network access– Infrared– Wireless– Cable, telephone, power lines…
Motivations for networked embedded systems
“Smart spaces”
Access to sensor network data (more later)
Remote actuation
Stanford iRoom Remote surgery
Embedded systems design issues
• Power consumption
• OS/programming API– Real-time? Event-driven?
• Communication– Medium? Protocol?
• Localization
• Monitoring
• Security
Communications decisions
• Medium choices:– Infrared– Wireless– Fiber
• Protocol choices:– IrDA– Bluetooth– Ultra Wideband
(eventually)– PicoNet
• Messaging format choices:– Active messages
(asynchronous– RPC (synchronous)– Proprietary
• Network setup choices:– Ad-hoc or static– TCP/IP compatibility– Internet connectivity
OS/Programming model
• Example: Windows XP Embedded– Componentized version of consumer OS– Device-specific “enabling features”
• Embedded Linux is similar
XP Embedded configuration screen
Computation in the network
• Embedded systems push functionality into the network– Leaving data processing/decision making
to supervisor is slow and wasteful
• One solution: Active Messages– Facilitate asynchronous intra-network
computation– May support distributed queries of sensors
(treating sensor networks as a DB)
Relation to network convergence
• Embedded systems employ an extremely diverse range of programming models and communication methods.
• Common thread: connectivity exists among hosts, as well as between hosts and a central supervisor entity with greater computing resources.
A case for the Access Network approach to convergence
Treat networks of embedded systems as “access networks”
InternetInternet
Unresolved issue: service discovery
• How do hosts on a large network discover services offered by networked embedded systems?
• Service discovery protocols– Sun’s Jini– Microsoft’s UPnP– Salutation– Bluetooth*– PicoNet*– IrDA*
* Per-connection only
6. “Establish connectionWith Mote 1”
Service Discovery Protocols: Electronic eavesdropping example
• An Internet-scale solution to this problem has yet to be developed.
Lookupserver
Room 1 Room 2
Mote 1
BaseStation
Nosy Dan
Nosy Dan’seavesdroppingdevice
1. “Register service:Mote 1 listening in Room 1”
BaseStation
3. “Request service:Listening in Room 1”
LANLAN2. “Register service:Mote 1 listening in Room 1”
4. “Lookup service:Listening in Room 1”
5. “Reply: Mote 1Listening in Room 1”
Nosy Dan’scompetitor
Emerging Extremes and Convergence
• Servers
• Workstations• Personal Computers
• Internet Services
• PDAs / HPCs/ smartphones
• Open Internet Services
• Microscopic sensor/embedded networks
• Planetary Services
From David Culler’s Invited Lecture at USC, February 28, 2001
Network Convergence
Sensor Networks• Concurrency intensive
– data streams and real-time events, not command-response
• Huge variation in load– population usage & physical stimuli– robustness
• Hands-off (no UI)• Dynamic configuration, discovery
– Self-organized and reactive control
Converged Network• Concurrency intensive
– provides real time services via different network mechanisms
• Different elements of the converged network have varied loads
• May or may not have UI• Network is adaptive
– service discovery major part of huge, all-encompassing network
• Complimentary roles
– tiny semi-autonomous devices empowered by infrastructure
– infrastructure services connected to the real world
Sensor Networks
• Existing Research PlatformsTinyOS/Mica Platform – Berkeley (Culler)SmartDust – Berkeley (Pister)
13 state
FSMcontroller
ADC
ambient lightsensor
Photodiode
Sensor input
Oscillator
Power input PowerTX Drivers0-100kbpsCCR or diode
Optical Receiver
1mm
330µ
m
WINS NG 2.0 – Sensoria 2001
Sensor IntegrationThe TinyOS Platform Application Model
Traditional network
Traditional network
Environment
monitoring
SerialForwarder
SerialForwarder
Inventory tracking
Remote control
console for motes
DB
SerialForwarder
IP
IP
IP
RF
Services… What about Sensors?
• Variety of sensors & actuators available– All-in-one sensor board includes
light, temperature, microphone, sounder, accelerometer, and magnetometer
– Environmental monitoring sensor board includes light, calibrated temperature, thermopile, humidity, barometric pressure
– Remote control sensor board includes external pin connections to control physical devices including RC vehicles
Multi-Network Data Acquisition--- Demo ---
• Two motes are sensing light and reporting the results back to a base station
• Base station allows IP clients to connect and read sensor data or control motes from anywhere on Internet
Robust CommunicationGeographic Routing: QoS multi-hop data acquisition
• GeoCast (Navas and Imielinski 1996)– Architecture for addressing and routing in wide are
networks• GeoMote (Pete, Joe, Rachel 2001)
– Sensor network implementation of GeoCast: lower power, adhoc
– Primary Services: • Geographic Multicast• Nearest Neighbor Service Discovery• Geographic Network Reprogramming and
Reconfiguration• Low Power Pursuer/Evader Games
Geographic Routing Architecture
ClientProcess
ClientProcess
Direct Message
Router
Host
Gateway
Event
Event
Low-Power Pursuer Evader
Evader
Geographic vs. Internet Architecture
• Geographic (sensor)– Routers may never
talk to Hosts and vice versa
– Gateways are entry/exit points but have no routing info
– Broadcast medium dependant on distance from source
• Internet– Functions of the
gateway and router are typically merged
– Gateways perform routing functions and are entry/exit points
– Broadcast medium dependant on physical network
Directed Diffusion
• Data-Centric• Register “interests” in the network
– < Attribute, Value > pairs
• Nodes diffuse the interest towards producers via a sequence of local interactions
• Gradients determine path of data• Achieve efficient distribution of data through
reinforcement and negative reinforcement
Illustrating Directed Diffusion
Sink
Source
Setting up gradients
Sink
Source
Sending data
Sink
Source
Recoveringfrom node failure
Sink
Source
Reinforcingstable path
Illustration courtesy of Deborah Estrin, UCLA
Distributed Algorithms
• Completely new area to investigate robust distributed algorithms on sensor networks– Example: New Distributed Algorithm for
Connected Dominating Sets in Wireless Ad-Hoc Networks ---Alzoubi et. al.
– Connected Dominating Set Typically Used as a backbone for wireless networks—useful to compose the backbone dynamically
Connected Dominating Set
1) Set the rank of each node0
1 1
2 22 2
33 3 3
44
2) Lowest Rank Among Neighbors Start Dominator DOMINATOR
DOMINEE DOMINEE
DOMINATOR DOMINATOR
DOMINEE
3) If all lower rankingneighbors domineethen you are dominator4) Invite black nodesto participate indominating tree
INVITE
INVITE INVITEJOIN JOIN
This is all occurring over RF broadcasts!
JOIN
Sensor Network as a Database
Two Projects:• Intel Research w/ UC Berkeley: TAG
– Tiny Aggregate Queries in Ad-hoc Sensor Networks
– Sam Madden, Wei Hong, Joe Hellerstein, Mike Franklin, David Culler
• Cornell University: Cougar– Towards Sensor Database Systems– Querying the Physical World– Philippe Bonnet, Johannes Gehrke, Praveen
Seshdri
Databases vs. Sensor Networks
• Database– Single Physical Device– Static data– Centralized– Failure is not an option– Plentiful resources– Administrated
• Sensor Network– Numerous Devices– Streaming data– Large number of nodes– Multi-hop network– No global knowledge
about the network– Frequent node failure– Energy is the scarce– Resource, limited
memory– Autonomous
Want “to combine and aggregate data streaming from sensors.” Sounds like a database…
Fjords
Use Fjords to handle lack of reliabilty andstreaming push data• Allows arbitrary combinations of push/pull amongst
devices– Operators assume non-blocking queue interface between
each other. – Queues implement push vs. pull
• Pull from A to B : Suspend A, schedule B until it produces data. A cannot go forward until B produces data.
• Push from B to A : A polls, scheduler thread invokes B until it produces data. A can process other inputs while waiting for B.
– Supports parallelism between operators
Fjording the StreamQuerying Streaming Sensor Data
Push
Pull
Social Networks / Active Badges
• Sensor networks can record social interactions by detecting proximity
• Not just a convergence of sensors and Internet, but other “networks” too!
• First attempt to monitor social network at UCB NEST Retreat, January 2002
• UCLA: iBadge Prototype– Investigate behavior of children in a
Kindergarten
Social Network Visualization
Wagner
Culler
Social Network Results
Conclusionsand
Future Directions
Future Directions
• Everyone disagrees over whether sensors should directly communicate via IP– Sensors: Routing is data-centric and energy-aware– Internet: Routing is bandwidth and latency-centric– If so, we need IPv6 NOW!– Do sensors need TCP/IP overhead since the transport
medium is unreliable?
• Networked Sensors may choose to elect some nodes to participate in networking and others to acquire data– Partitions the network into two sets, end-hosts and
infrastructure, like current Internet
Conclusions
• Research opportunities in sensor networks is infinite (or nearly infinite)– Algorithms– Network Architecture / Routing– Data Acquisition / Aggregation– Network Convergence of Devices
• Computing will continue to move within the network• Sensors and Embedded Systems will enabled
ubiquitous computing efforts• Connecting Embedded Devices to Traditional
Networks can be very powerful:– Environmental Monitoring– Autonomous Actuation (eg: “Smart” home)
References
• See www.cs.berkeley.edu/~polastre/cs294-2002sp
• Links to relevant papers and more information on Embedded and Sensor Networks
Embedded Systemsand
Sensor Networks
