Quick Look at Sensor Networks

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Quick Look at Sensor Networks

• Elke A. Rundensteiner
• Based on material collated by
• Silvia Nittel, and others.
• CS525

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Overview Sensor Networks

• Motivation Applications
• Platform Power
• Networking Underpinning

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Motivation

• Trends
• Developments of new sensor materials
• Miniaturization of microelectronics
• Wireless communication
• Consequences
• Embedding devices into almost any man-made and
  some natural devices, and
• connecting the device to an infinite network of
  other devices, to perform tasks, without human
  intervention.
• Information technology becomes omnipresent.
• ?Pervasive Computing The idea that technology
  is to move beyond the personal computer to
  everyday devices with embedded technology and
  connectivity as computing devices become
  progressively smaller and more powerful.

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Embedded Networked Sensing Potential

• Micro-sensors, on-board processing, and wireless
  interfaces all feasible at very small scale
• can monitor phenomena up close in non-intrusive
  way
• Will enable spatially and temporally dense
  environmental monitoring
• Embedded Networked Sensing will reveal
  previously unobservable phenomena

Habitat Monitoring Storm petrels on Maines Great
Duck Island
Contaminant Transport
Marine Microorganisms
Vehicle Detection
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Multiscale Observation and Fusion Example,
Regional (or greater) scale to local scale

• Satellite, airborne remote sensing data sets at
  regular time intervals
• coupled to regional-scale backbone sensor
  network for ground-based observations
• fusion, interpolation tools based on large-scale
  computational models

Small-scale Sensor network
images from Susan Ustin, UC Davis
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Overview

• Motivation Applications
• Platforms and Power
• Networking

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Sensor Network

• Sensor Node
• Tiny vanilla computer with operating system,
  on-board sensor(s) and wireless communication
  (PC on a pin tip)
• Trend towards low-cost, micro-sized sensors
• Use of wireless low range RF communication
• Batteries as energy resource
• Sensor Network
• Massive numbers of sensors in the environment
  that measure and monitor physical phenomena
• Local interaction and collaboration of sensors
• Global monitoring
• Tightly coupled to the physical world to sense
  and influence it

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UC Berkeley Family of Motes
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Mica2 and Mica2Dot

• Processor
• ATmega128 CPU
• RAM/Storage
• Chipcon CC1000
• Manchester encoding
• Tunable frequency
• Byte spooling
• Power usage scales with range

1 inch
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Mica Sensor Board

• Light (Photo)
• Temperature
• Acceleration
• 2 axis
• Resolution 2mg
• Magnetometer
• Resolution 134mG
• Microphone
• Tone Detector
• Sounder
• 4.5kHz

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A Network
S. Madden, UBerkeley
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Wireless Sensor Networks

• They present a range of computer systems
  challenges because they are
• closely coupled to the physical world with
• all its unpredictable variation, noise, and
  asynchrony
• they involve many energy-constrained,
  resource-limited devices operating in concert
• they must be largely self-organizing and
  self-maintaining and
• they must be robust despite significant noise,
  loss, and failure.

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Architecture
Application layer
Application Events, Reactions
Data model, Declarative queries
(temp-spatial) DB layer
Data aggregation, Query processing
Adaptive topology, Geo-Routing
Network layer
MAC, time, location
Physical layer
Phy comm, sensing, actuation
Source Deborah Estrin, UCLA
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Overview

• Motivation Applications
• Platforms Power
• Networking

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Communication using Radio
Listening receiving signals
Broadcasting radio signals
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PicoRadio and Radio propagation

• Energy required to transmit signals in distance d
• Communication is huge battery drain
• Indoor has lots of other complications
• Small energy consumption gt short range
  communication
• Multi-hop routing required to achieve distance
• Routes around obstacles
• Requires discovery, network topology formation,
  maintenance
• may dominate cost of communication
• Energy to receive
• Dominated by listening time (potential receive)
• Device has a total lifespan
• Radio must be OFF most of the time!

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ISO/OSI Protocol Stack
The End Computer System View
7 Layer ISO/OSI Reference Model
Internet Application
Transport Control Protocol (TCP)
The Internet Protocols
Internet Protocol (IP)
The Network Card
) International Standard Organization's Open
System Interconnect
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Low-level Networking

• Physical Layer
• Low-range radio broadcast/receive
• Wireless (wiSeNets)
• MAC Media Access Control
• Controls when and how each node can transmit in
  the wireless channel (Admission control)
• Objectives
• Channel utilization
• How well is the channel used? (bandwidth
  utilization)
• Latency
• Delay from sender to receiver single hop or
  multi-hop
• Throughput
• Amount of data transferred from sender to
  receiver per time unit
• Fairness
• Can nodes share the channel equally?

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MAC Design Decisions

• Energy is primary concern in sensor networks
• What causes energy waste?
• Collisions
• Control packet overhead
• Overhearing unnecessary traffic
• Long idle time
• bursty traffic in sensor-net apps
• Idle listening consumes 50100 of the power for
  receiving (Stemm97, Kasten)

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Networking

• Network Architecture Can we adapt Internet
  protocols and end to end architecture to SN?
• Internet routes data using IP Addresses in
  Packets and Lookup tables in routers
• Many levels of indirection between data name and
  IP address, but basically address-oriented
  routing
• Works well for the Internet, and for support of
  Person-to-Person communication
• Embedded, energy-constrained, unattended system
• cannot tolerate communication overhead of
  indirection
• sensor network architecture needs
• Minimal overhead, and Data centric routing

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Data-centric Routing

• Named-data as a way of tasking motes, expressing
  data transport request (data-centric routing)
• Basically
• send the request to sensors that can deliver the
  data, I do not care about their address
• Initial approaches in literature
• Some form of tree-based routing
• Query sent out from server to motes
• Sink-Tree built to carry data from motes to server

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Communication In Sensor Nets

• Radio communication has high link-level losses
• typically about 20 _at_ 5m
• Ad-hoc neighbor discovery
• Tree-based routing

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Tree Routing
Parent Node
Children Nodes
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Tree building

• Queries/Request
• What goes in query?
• Where does query go?
• Neighbor selection
• How does mote select upstream neighbor for data?
• Asymmetric links
• Unidirectional links

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Tree building

• Dynamics
• How often do you send out a new query?
• How often do you select a new upstream path ?
• Design tree building protocol
• From query source to data producer(s) and back
• Multihop ad-hoc routing
• ? reliable routing is essential!

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Basic Primitives

• Single Hop packet loss characteristics -gt link
  quality
• Environment, distance, transmit power, temporal
  correlation, data rate, packet siz
• Services for High Level Protocols/Applications
• Link estimation
• Neighborhood management
• Reliable multi-hop routing for data collection

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Neighborhood Management

• Maintain link estimation statistics and routing
  information of each neighboring sensor node
• Issue
• Density of nodes can be high but memory of nodes
  is limited
• At high density, many links are poor or
  asymmetric
• Neighborhood Management
• Question when table becomes full,
• should we add new neighbor?
• If so, evict old neighbor?
• Similar to
• frequency estimation of data streams, or
• classical cache policy

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Reliable Routing

• 3 core components for Routing
• Neighbor table management
• Link estimation
• Routing protocol

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Quick Summary

• Motivation Applications
• Platforms Power
• Networking