Deborah Estrin

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CENS Some highlights from our first year

• Deborah Estrin
• Work summarized here is largely that of students,
  staff, and other faculty at CENS--see poster
  session and handouts for detailed attribution
• We gratefully acknowledge the support of our
  sponsors, including the National Science
  Foundation, Intel Corporation, Sun Inc., Crossbow
  Inc., and the participating campuses.

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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
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Systems Challenges and Services

• Irregular deployment and environment
• Dynamic network topology
• Hand configuration will fail
• Scale, variability, maintenance

Localization Time Synchronization
Calibration

• Time synchronization
• Localization
• Energy Harvesting
• Routing and transport
• System development tools
• Channel/connectivity characterization

Information Aggregation and Storage
Programming Model
Event Detection
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Systems Time Synchronization Service

• Also crucial in many other contexts
• Ranging, tracking, beamforming, security, MAC,
  aggregation etc.
• Global time not always needed
• NTP often not accurate or flexible enough
  diverse requirements!
• New ideas
• Local timescales
• Receiver-receiver sync
• Multihop time translation
• Post-facto sync
• Mote implementation
• 10 ?s single hop
• Error grows slowly over hops

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Systems Localization of Sensor Nodes

• Robust ranging
• Wideband acoustics
• Scalable distributed algorithms
• Collaborative multilateration(with beacons)
• Geometry-driven beacon-less
• Fundamental error analysis
• Cramer-Rao bounds for multihop
• Geometry effects
• Angle vs. distance
• Implementation
• MK-II platform with ultrasound ranging

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Systems Energy Harvesting

• Need distributed methods to learn the
  environmental energy opportunity at all nodes
• Global task sharing among nodes to optimize
  performance
• (Srivastava et al)

• NIMS aerial nodes also solar powered, self
  sustaining
• (Kaiser et al)

Environmentally aware

• HelioMote test-bed
• Recharge batteries from solar
• Track energy received
• Monitor residual battery status
• Provide constant voltage to load as battery
  voltage degrades

Battery based
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Systems Directed Diffusion used for Adaptive
Data-Centric Routing and Transport
Sink

• Data-Centric routing supports in network
  processing
• Tinydiffusion implements one-phase-pull variant
• Pulls data out to only one sink at a time (saves
  energy)

Sources
Interest
Routed Data
Gradient
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Systems Emstar Development environment
(simulation, emulation, visualization, run time
services)
Emstar Emulation, Simulation, Visualization, and
Run-time Services for ENS systems

. . .
Emulator/Simulator
Radio
Radio
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The Ceiling Array A Real Wireless Channel
Motes used to transmit and receive packets -- A
real-world augmentation to a virtual simulation
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Systems Connectivity measurement tool based on
Emstar
SCALE Connectivity measurement system based on
Emstar
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Systems Characteristics of Wireless Connectivity
Asymmetry vs. Power
Reception v. Distance
What Robert Poor (Ember) calls The good, the
bad and the ugly
Standard Deviation v. Reception rate
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Information Theoretic FoundationsScalability
for Point Sources in Sensor Networks

• Information theory concerned with fundamental
  limits
• Capacity maximum reliable communication rate,
  versus bandwidth and power
• Rate-Distortion minimum required rate to
  describe source, subject to distortion constraint
  
• Gupta Kumar early result showed wireless
  communication networks do not scale with node
  density per node capacity goes to zero
• However Cooperative rate distortion coding
  results in most communication being local in
  sensor networks-- more nodes do not necessarily
  result in more traffic
• More relays enable increased frequency re-use
  capacity can increase without bound

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Information Theoretic Foundations Scalability
for Distributed Sources

• To estimate parameters of a field (e.g., to get
  isotherm map) information increases until achieve
  desired spatial sampling
• After this extra nodes contribute no additional
  information, but can increase communication
  resource
• Image processing analogy specify pixel size
• Parameters to describe local field can be compact
  compared to raw data, for given level of
  distortion

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Information Theoretic Foundations Practical
Implementation

• Dense network in neighborhood have mix of nodes
  with different ranges, operating in separate
  bands
• Perform local fusion to avoid long-range
  communication of raw data
• Locally route towards the longer range links
  they act as traffic attractors, causing number of
  hops at any given layer to be small, limiting
  delay
• Result is a (largely) standard overlay
  hierarchical network

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In Network ProcessingDistributed
Representation, Storage, Processing

• In network interpretation of spatially
  distributed data
• Statistical or model based filtering
• In network event detection and reporting
• Direct queries towards nodes with relevant data
• Trigger autonomous behavior based on events
• Expensive operations high end sensors
• Robotic sensing, sampling
• Support for Pattern-Triggered Data Collection
• Multi-resolution data storage and retrieval
• Index data for easy temporal, spatial searching
• Spatial and temporal pattern matching
• Trigger in terms of global statistics (e.g.,
  distribution)
• Exploit tiered architectures

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In-Network ProcessingCollaborative Signal
Processing

• Practical algorithms and fundamental limits
• Source detection and localization
• Noncoherent (e.g. proximity)
• Coherent (e.g. beamforming)
• Source separation and identification
• Multi-hop communication
• Simple relay
• Cooperative
• Data aggregation

• Theory suggests local interactions are the most
  important
• Learn model of environment and progressively
  reduce uncertainty
• Belief about state x is gradually updated
  p(xz1) -gt p(xz1, z2).
• z3 and z4 may improve p(xz1, z2) by different
  amount if used.

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In Network ProcessingWireless Acoustic Arrays
Acoustic Localization using AML Algorithm
Bearing crossing of 2 DOAs yields locations

Optimum Sensor Placement Reverberant
DOA/Localization
? Higher Error Variance Lower ?

• Most DOA/localization algorithms assume nearly
  reverberant-free environments
• Source image model reflects source along all
  relevant reflecting walls to model reverberation
  useful for simulation, not for LOA/localization
• Proposed new array image model reflects array
  along all relevant reflecting walls to model same
  reverberation useful for actual DOA/localization

CRB of source location error variance (for 8
fixed sensors) is low when target is inside
convex hull of the sensors
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Sensor-Coordinated Mobility
Actuation Networked Info-Mechanical Systems
(NIMS)

• 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

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Actuation NIMS Adaptive Diversity
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Actuation in CENS Systems
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Actuation Experimental Testbeds
Autonomous deployment of a sensor network from an
aerial robot
An underwater robotic network for marine
micro-organism detection
Pioneer mobile robots deploying and repairing a
sensor network
The Robomote
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Development of New Embedded Sensors

• CENS-compatible chemical-sensor technologies
  needed
• soil/water quality monitoring, security,
  precision agriculture
• Current chemical-sensor development
• electrochemical nitrate sensorspotentiometric
  orchronocoulometry
• MEMS liquid chromatography systems and mass
  spectrometers

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CENS Application Systems under design/construction

• Biology/Biocomplexity
• Microclimate monitoring
• Triggered image capture
• Contaminant Transport
• County of Los Angeles Sanitation Districts
  (CLASD) wastewater recycling project, Palmdale,
  CA
• Seismic monitoring
• 50 node ad hoc, wireless, multi-hop seismic
  network
• Structure response in USGS-instrumented Factor
  Building
• Marine microorganisms
• Detection of a harmful alga
• Experimental testbed w/autonously adapting sensor
  location

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Habitat SensingMicro-climate Factors, Avian
Nesting Success, Plant Responses

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Environmental Protection ApplicationPreventing
nitrate impact on groundwater
Real-world sensor net design problem
Sensor RD

• Fabricated nitrate microsensor matching COTS
  macrosensor performance

• Deployed initial moisture sensors at Palmdale
  water reuse facility
• Prototyping distributed array of pylons for dense
  real time monitoring

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Habitat and Contaminant ApplicationsExtensible
Sensing System (ESS) Software

• Tiered architecture to support taskable, scalable
  monitoring
• Mica2 motes (8 bit microcontrollers w/TOS) with
  Sensor Interface Board hosting in situ sensors
• Tinydiffusion provides tasking and multihop
  transport over SMAC links
• Microservers are solar powered, 32-bit
  processors, linux OS
• Pub/sub bus over 802.11 to Databases,
  visualization and analysis tools, GUI/Web
  interfaces

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Habitat and Contaminant Applications Sensor
Interface Board

• A general framework for attaching multiple
  instances and different types of sensors
• ADC true 12bit
• High gain differential channels
• Digital Input (Interrupt driven)
• Digital Outputs
• Counter, frequency
• Relay output
• On board voltage,temperature and humidity
• Flexible sampling rate
• Configurable for different translation functions
  per channel based on the sensors that has been
  attached
• Tested with different sensor types.
• http//www.cens.ucla.edu/mhr/daq/
• Now sold by Crossbow

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Detection of Marine Micro-organisms using
Immuno-based Methods
Experimental Testbed
AFM image of alga

• Detection of a harmful alga (Brown Tide ) using
  AFM and ELISA and Flow Cytometry
• Experimental testbed Glass columnw/ sharp
  thermocline and autonously adapt sensor location
  to thermocline
• Prptocol for counting using the FITC-conjugated
  MAb
• Cell imaging w/ AFM on poly-L-lysine coated mica
  surfaces

Flow Cytometry
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Seismic Applications

• Multi-Hopped Radio Linked Array design
• Multihop timesynch is key
• Deployments planned for UCLA campus and the San
  Andreas Fault (100m-10 km)
• Factor Building Data
• Decrease of 0.05 to 0.1 Hz in fundamental mode
  after earthquakes
• Observation of 4 strong earthquakes, including
  Alaska Japan

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Hardware Plans for Deployment
Stargate (Intel, Crossbow) X-Scale based,
400MHz 32MB RAM, Flash runs Linux
Kinemetrics digitizer
Guralp Seismometer
802.11 fast back-channel, command and time
distribution
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Grade 6-12 Science EducationUsing Sensor
Networks as Experimental tool
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Undergraduate Research Program
The CENS program went beyond the expected gave
me more learning experiences than anticipated.
Undergraduate Scholar
Originally, I really only considered a masters
program, but seeing the doctoral program and
hearing about it from lab members definitely
generated greater interest on my part to engage
in a similar atmosphere in the future.Undergradu
ate Scholar If mentoring an intern makes up
their mind to attend graduate school or increase
their interest, then mentoring is worth
it.Graduate Student Mentor

• 45 undergraduates participated in CENS research
  this summer
• 26 were women
• 26 were minorities
• Awarded NSF Gender Diversity
• in
• STEM Education grant

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Ethical, Legal, Social Implications
Pervasive Computing The ethical, legal, and
policy issues must be addressed during the design
and use stages of these Embedded Network
systemsA more in-depth analysis of public
policy issues is urgently needed that would lead
to appropriate recommendations for solving likely
problems.National Academy of Sciences

• Significant Activities
• Developed a white paper for the Joint Committee
  on Preparing California for the 21st Century.
• CENS faculty, Professor Pottie, testified in a
  California Senate Committee Informational Hearing
  on RFID Technology and Pervasive Computing.
• Submitted a proposal for an NSF Societal
  Dimensions of Engineering, Science, and
  Technology Grant.
• Prof. Dana Cuff and Jerry Kang Conducted ELSI
  seminars for CENS community.

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Conclusions

• Center concept allowed opportunities to emerge
  and be realized at a rate that exceeded our
  expectation
• Systems, signal processing and actuation have so
  much in common its difficult to maintain separate
  web pages!
• Applications are sharing platforms and building
  blocks
• Less-GPS Timesynch for Seismic and acoustic
  arrays
• Contaminant and Ecosystem soil array platform
• One size does not fit all, nor perhaps any all
  of our applications will be served by tiered
  architectures
• The Robotic Ecology vision is becoming real
  through NIMS
• Undergraduate research proved itself as highly
  effective and mutually beneficial to the students
  and CENS
• Some challenges to early deployments were even
  more interesting than we expected
• Building deployable systems with resource
  constrained devices and aggressive duty cycling
  is hard!
• In situ calibration, localization dont yet have
  deployable early incarnations

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New Directions
Security
Precision Agriculture
Global seismic Grids/facilities
Tropical biology
Theatre,Film,TV
Coral reef
Macro-Programming
Adaptive Sampling
High Integrity ENS
RFIDs
NIMS
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FINANCIAL MANAGEMENT ISSUES

• CENS financial issues are complex.
• Multi-institutional
• Focus on 8 technology and application areas
• Education/diversity allocations
• Support for the Center administrative
  infrastructure.
• Financial allocations and issues cross
  institutions and cross the various applications
  and technologies.
• UCLA and partner institutions have made a large
  matching commitment
• Supports research and the institutional
  infrastructure necessary to be a successful
  technology research center.
• Center must balance the need to allocate
  resources toward a strong administrative
  infrastructure that supports research growth and
  toward the needs of the ambitious ENS research
  agenda.

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FUNDING COMPARISONRESEARCH TO INFRASTRUCTURE
SUPPORT
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FINANCIAL MANAGEMENT ISSUES (CONTINUED)

• Financial analyses are done with varying focus
• Simple total budgets for applications,
  technologies, education and administrative
  infrastructure.
• Budgets that break out allocations of federal
  funds and monitor the required institutional
  matching dollars.
• Budgets that reflect the allocation of funds
  across and between applications and technologies.
• The majority of CENS application funding
  allocated to supporting technology.
• Budget analyses are constantly being evaluated
  and will continue to be evaluated to ensure that
  we are able to make appropriate budgetary changes
  as the research needs change.

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TOTAL FUNDING ALLOCATIONS
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NSF AND MATCHING FUNDS ALLOCATIONS
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FUNDING COMPARISONTECHNOLOGY APPLICATION
ALLOCATION
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Issues for Year 2

• New technology area NIMS 5-year funding
  period
• Expanding application areas Health,
  Entertainment
• Rapidly expanding education areas
• Expanded knowledge transfer activities
• Individual projects up for review and renewal of
  funding
• Funding for new projects and expanding technology
  areas
• International collaborations?
• Infrastructure needs to support growth

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Thank Yous!!

• CENS Students, Staff, and Faculty for all the
  excellent work, preparation, posters, demos,
• Bill Kaiser, Greg Pottie, and Mani Srivastava for
  extensive technical and leadership contributions
  to CENS vision and strategy
• Sponsors National Science Foundation, Intel
  Corporation, Sun Inc., Crossbow Inc., and the
  participating campuses.
• Dean Vijay Dhir (HS-SEAS) for supporting the CENS
  build-out now in the architectural planning
  stages
• Bernie Dempsey, Stacy Robinson, David Jaquez and
  Sara Terheggen for organizing the review !!!