Vision for Sensor Networks

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Vision for Sensor Networks

• CSE 291 Chien
• Spring 2003
• April 8, 2003

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Course Logistics

• Friday meeting time
• 1230-150, SSB 106 (only irregularly, including
  this Friday)
• Web site emerging
• Information being added regularly
• Initial paper presentation signups and paper
  summaries
• Lectures available
• Projects (still coming)

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Paper Summaries

• Evaluations of the papers are due after we cover
  them in class. Each should be less than a page
  long (don't write a novel) and should follow this
  rough format
• Title and Authors of paper
• One sentence summary of the paper (the problem(s)
  it addresses and how)
• Summary of key or important ideas in the paper
  (why are we reading this anyway?)
• How does the paper substantiate the importance of
  those ideas (brief summary of logical argument
  and evidence)
• One or two important flaws or limitations in the
  paper (be explicit)
• How relevant is this work today and/or what
  future research does it suggest?
• The evaluations should be turned in to Prof
  Chiens office at the end of each week, on Friday
  before 5pm. If the door is closed, these can be
  put under the door.

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Todays Papers

• D. Estrin, D. Culler, K. Pister, and G. Sukhatme,
  Connecting the Physical World with Pervasive
  Networks , IEEE Pervasive Computing, pp. 59-69,
  January-March 2002.
• Which largely subsumes
• D. Estrin, R. Govindan, J. Heidemann and S.
  Kumar, Next Century Challenges Scalable
  Coordination in Sensor Networks, International
  Conference on Mobile Computing and Networks
  (MobiCOM '99), August 1999, Seattle, Washington.
• J. M. Kahn, R. H. Katz, and K. S. J. Pister, Next
  Century Challenges Mobile Networking for "Smart
  Dust" , In International Conference on Mobile
  Computing and Networks (MobiCOM '99), August
  1999, Seattle, Washington.

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First

• D. Estrin, D. Culler, K. Pister, and G. Sukhatme,
  Connecting the Physical World with Pervasive
  Networks , IEEE Pervasive Computing, pp. 59-69,
  January-March 2002.

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Vision of Ubiquity

• Capability to go anywhere and be anyplace
• Out of the machine room, backpack
• Away from the power supplies (or near)
• Away from the infrastructure (or near)
• cant require a crushing effort

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Vision of Invisibility

• Not seen
• Systems that are small
• Systems that are unobtrusive
• Systems that are intuitive to use interfaces
  that dont require training
• Invisibility is coupled with pervasive for
  utility

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Deep Integration with the Physical World

• Todays computers are blind, deaf, dumb
• Limited sensory input
• Limited interaction
• Either disconnected, offline or primarily input
  processing, etc.
• Embedded systems are the exception to this, but
  historically have limited networking
• Sensor networks are the superexception to this
• Focused on the physical world
• Data acquisition, computation, and action
• Closely coupled sensing and actuation
• The real autonomic computing systems ??

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Major System Challenges

• Large numbers of elements
• Limited physical access
• Extreme environmental conditions
• gt demand a fundamental reexamination of familiar
  layers of abstraction, hardware, algorithms
• Suggestion these are a radically different kind
  of computing system

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Scale

• of sensors 10s to millions
• Size of sensors (cubic feet to millimeters)
• Spatial and temporal sampling rates (miles to
  mms and days to ms)
• Capability (sensors, power, compute, communicate)
• Compose and evolve as a system at scale
• Question what computing systems do we have that
  span these ranges? Are they one kind?

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Limited Access

• Unwired, unpowered, limited networking (cost)
• Physically remote or harsh enviroments
• Limited human intervention support/administration
• Resource limited
• What are characteristics of our longest running,
  reliable systems, and techniques?

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Extreme Dynamics

• Activity in the physical world happens in bursts
• Animals are built for this (adrenaline,
  fear-flight, hunt, taste, smell, etc.)
• Static network -gt things passing, evolving
• Mobile network -gt things encountered
• Dynamic range of sensory input is orders of
  magnitude
• Systems must have passive vigilance, efficient
  triggering, and rapid transformation to high
  levels of concurrency and effectiveness.
• Not quite lazy computing, or something
  analogous?

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Breadth

• Variable design structure static, dynamic,
  regular and irregular
• Single sensor type/mode, multiple, single
  application and multiple-application
• Static or mobile fast and slow change
• Autonomy and limited access
• Degree of human involvement in both
  decision-making/control as well as maintenance of
  system

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State of the Art

• rambling discussion of some current research
  activities
• Small devices increasing in environmental
  awareness and networking capability
• Evolving radio, silicon technology enabling
  sensor networks
• Maturing software environments

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State of the Art (cont.)

• Outline of several specific challenges (not
  comprehensive)
• Sensing and actuation control loops and
  variable delays
• Localization as a key challenge and foundation
  for coupling with the physical world
• Self configuration and reconfiguration

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Some throw ins

• Data centric architecture and directed
  diffusion (well discuss later)
• Tiered (hierarchical) architectures
• Different capabilities, heterogeneity
• Frontier for almost any CS subdiscipline is in
  this area

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Discussion

• What kind of systems are really being discussed?
• How do they differ fundamentally from those more
  familiar?
• How do they differ qualitatively/parametrically?
• Are the systems being discussed a single class?
  Multiple classes?
• What areas are likely to be extensions of current
  areas? Which are likely to be revolutionarily
  new?
• Is the frontier for your CS subdiscipline in this
  area?

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Second

• J. M. Kahn, R. H. Katz, and K. S. J. Pister, Next
  Century Challenges Mobile Networking for "Smart
  Dust" , In International Conference on Mobile
  Computing and Networks (MobiCOM '99), August
  1999, Seattle, Washington.

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Mobile Networking for Smart Dust

• Smart dust can be small enough to
• Remain suspended in air
• Buoyed by air currents
• Sensing and communicating for hours and days on
  end
• Exploring the limits of size and power
  consumption in autonomous sensor nodes
• Interestingly, macro-scale systems have achieved
  this capability today

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Smart Dust

• Mote, as in dust Motes
• Integrated
• MEMS sensors
• Signal processing and control circuitry
• Power source and solar cells
• Laser diode and MEMS mirror for active optical
• Retroreflector and optical receiver for passive
• 1-2 mm in dimension, autonomous system

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Some Technology Limits

• Objective 1mm3 sensors
• How much energy can we consume?
• Batteries -gt 1 Joule / 1mm3
• For a lifetime of 1 day
• -gt 10 microwatts average (NOT milliwatts!)
• Augmenting with solar power limited to 2x
• Artificial lighting 1.001x
• Energy scavenging all well below solar

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What does this mean?

• There are fundamental limits to what can be
  consumed (resources) by these systems in
  particular deployment/connection modes
• Energy consumed per unit time (average)
• Energy consumed in a burst, and cluster of bursts
• Data communicated (probably)
• Operations computed (?)
• Do these limits naturally partition sensor
  network systems? Is this a continuum or a
  discontinuity?

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Low Power Techniques

• Clearly at a premium in these systems
• E.g. 2x efficiency gt 2x more STUFF can get done
  or 2x LIFETIME or 2x reduction in COST
• Intelligent control of hardware subsystems
• Intelligent control of software and application
  activities
• Intelligent design and implementation of systems
  for power efficiency
• In particular, power-efficient techniques for
  communication which due to radios is dramatically
  more expensive than computation

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Free space Networking

• Base station architecture, based on cheap video
  and imaging circuits
• Many sensors transmit simultaneously
• Power efficiency per bit is dramatically higher
• Active (LEDs), passive cornercube retroreflector
  (MEMS) for interrogation, demonstrated kb/s
• Reading an electronic panel

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Specific Functions

• Parallel Read out
• Synchronized sample of the space and smart dust
• Demand Access
• Passive monitoring, triggered activation and
  sensing
• Controlled probing rates
• gt the benefits of centralized control

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Limitations

• Line of sight
• Direct optical communication to BTS ideal
• Multihop possible, but limited
• Increases bandwidth densities, but decreases
  connectivity
• Link Directionality
• Can focus interrogation subset of viewable
  sensors
• Limits mote visibility and connectivity to a
  hemisphere
• Interesting connectivity, routing, and interlaced
  network challenges

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Discussion

• How is this vision different/similar to that of
  Culler/Estrin?
• What are the advantages of this type of
  networking approach? Disadvantages?
• Power, line of sight, orientation, how do
  applications differ in their needs for these
  things?
• How does a technological underpinning like this
  affect the architecture of a sensor network
  system?

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Next Time

• Friday, April 11 in SSB 106
• Detailed overview of current/emerging sensor
  network hardware
• Ember Networks Platform (Ryan Wu)
• Crossbow Platform (Berkeley Motes) (Johanz
  Ammerlahn)
• We will update the web links to specific
  documents, but not until late today
• Dont forget your first set of paper summaries
  are due Friday at 5pm.