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Possibly relevant introductory comments about sensor network technologieswithout a single pretty pic

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but not the system ... cpu, infrastructure) data and system integrity ... Monitoring RF tone (Kang) Interconnection and interference among wireless substrates ... – PowerPoint PPT presentation

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Title: Possibly relevant introductory comments about sensor network technologieswithout a single pretty pic


1
Possibly relevant introductory comments about
sensor network technologieswithout a single
pretty picture
  • Deborah Estrin
  • Director, Center for Embedded Networked Sensing
    (CENS)
  • Professor, Computer Science Department, UCLA
  • destrin_at_cs.ucla.edu
  • http//cens.ucla.edu/Estrin

2
Sensor Networks Sensing Computation Wireless
  • Low power wireless enables minimal infrastructure
  • Low cost per device enables pervasiveness
  • Low profile deployment enables invisibility

3
Relevant Data and System Types
  • Data Types
  • Location (absolute, proximity)
  • Audio
  • Image
  • Physical environmental parameters (temperature,
    light)
  • Physiological
  • System Types
  • Fixed environmental monitoring
  • Fixed human observation
  • Fixed monitoring of mobile tags

4
Embedded Networked Sensing Potential
  • Micro-sensors, on-board processing, wireless
    interfaces feasible at very small scale--can
    monitor phenomena up close
  • Enables spatially and temporally dense
    environmental monitoring
  • Embedded Networked Sensing will reveal
    previously unobservable phenomena

Contaminant Transport
Ecosystems, Biocomplexity
Marine Microorganisms
Seismic Structure Response
5
Long-Lived, Self-Configuring Systems
  • Irregular deployment and environment
  • Dynamic network topology
  • Hand configuration will fail
  • Scale, variability, maintenance

Localization Time Synchronization
Calibration
Information Aggregation and Storage
Solution local adaptation and redundancy
Programming Model
Event Detection
6
Sensor-Coordinated Mobility
  • NIMS Architecture Robotic, aerial access to
    full 3-D environment
  • Enable sample acquisition
  • Coordinated Mobility
  • Enables self-awareness of Sensing Uncertainty
  • Sensor Diversity
  • Diversity in sensing resources, locations,
    perspectives, topologies
  • Enable reconfiguration to reduce uncertainty and
    calibrate
  • NIMS Infrastructure
  • Enables speed, efficiency
  • Provides energy transport for sustainable
    presence
  • Pending funding

7
Whats New?
  • Miniaturization, integration, low power, low cost
    ultimately means you can put a CPU and Radio
    wherever you can put a sensor (Kaiser-Pottie
    96)
  • Distributed intelligence
  • Dumb sensing systems not scalable--very low
    information/data proportion presented to user
  • Centralized intelligent sensing is more scalable
    for the end user (higher information/data ratio)
    but not the system
  • Distributed intelligence will make systems
    scalable by identifying interesting events,
    trends, patterns in the network and only
    exporting informationasymptotically approach
    information/data1

8
Some security/privacy relevant technical/architect
ural issues
  • Sensor processing architecture--using models to
  • Narrowly define events of interest
  • Preserve anonymity (images, acoustic)
  • Adapt and refine events of interest
  • Location architecture
  • Location information exported independently or
    bound to and deleted with other sensor data
  • Crypto support
  • Low overhead (power, comm, cpu, infrastructure)
    data and system integrity
  • Mechanisms for providing informed/non-transparen
    t observation
  • Monitoring RF tone (Kang)
  • Interconnection and interference among wireless
    substrates

9
Current state of the art
  • Quite early. Few deployed systems
  • Existing systems have little/no security
    mechanisms in place
  • No known examples of anonymity-preserving systems
    (imagers, acoustics)

10
Application domains that raise public privacy
concerns
  • Wherever there is significant financial incentive
    for fine spatial and temporal granularity
    observation
  • Transportation
  • Public spaces
  • Workplace
  • Medical care (hospital and home)
  • Education/Classroom
  • Criminal justice system
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