Title: Possibly relevant introductory comments about sensor network technologieswithout a single pretty pic
1Possibly 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
2Sensor Networks Sensing Computation Wireless
- Low power wireless enables minimal infrastructure
- Low cost per device enables pervasiveness
- Low profile deployment enables invisibility
3Relevant 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
4Embedded 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
5Long-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
6Sensor-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
7Whats 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
8Some 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
9Current 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)
10Application 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