Opportunities in High-Rate Wireless Sensor Networking

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Opportunities in High-Rate Wireless Sensor
Networking

• Hari Balakrishnan
• MIT CSAIL
• http//nms.csail.mit.edu/

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Todays WSN Monitoring Applications

• Periodic monitoring
• repeat
• wake up and sense
• transmit data
• sleep for minutes
• Event-based monitoring
• Transmit data on external event
• Low data rates duty cycles

Pic Sam Madden
Pic Sam Madden
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High-Rate WSN Applications

• High sensing rates O(102 105) Hz
• Non-trivial analysis of gathered data
• Frequency analysis, correlation analysis
• Many domains
• Industrial monitoring, civil infrastructure,
  medical diagnosis, process control,
• What are the reusable components of a general
  architecture for high-rate WSNs?

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Industrial Monitoring

• Preventive maintenance of fabrication plant
  equipment (Intel)
• Done manually today, offline processing
• Sense vibration (acceleration)
• 100 machines, gt10 observation points per machine
• 10-40 kHz frequency band
• Aggregate data rate about 10 100 Mbits/s

Pic Wei Hong
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Intel Fabs 20 Questions

• Is energy in f1, f2 gt E?
• Compare energy in f1, f2 with past activity
• Which frequency bands have highest energy?
• What is the phase relationship between samples at
  different locations
• Provide high-resolution view of last T mins of
  samples at location L

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Pipeline Pressure Monitoring

• Preventive maintenance of (aging) water and
  sewage infrastructure
• Leaks are precursors to bursts
• Monitor pressure and flow at 0.5 to 2 KHz
• Done manually today

Pic Rory OConnor (MIT)
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Thames Waters 20 Questions(Thanks to Kevin
Amaratunga Ivan Stoianov)

• Whats the flow / pressure at location L?
• Is pressure / flow at location L different from
  dynamic state estimator?
• Has there been a significant pressure drop
  between locations L1 and L2?
• How long does it take pressure wave to travel
  from L1 to L2?

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Constraints

• Wireless communication rates
• Total required raw data rates exceed
  next-generation radio rates
• Energy
• Sensing and communication consume energy
• Want months of operation on batteries
• Unreliable sensor nodes
• In-the-net processing essential

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Challenges

• High-level programming abstractions
• Distributed signal and data processing operators
• Collaborative data acquisition
• High-performance network delivery

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High-Level Programming

• Users wont (cant) write embedded signal and
  data processing code
• Generalized stream processing continuous query
  processing signal processing
• Develop a declarative stream processing interface
• Support iterative refinement

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Generalized Stream Processing

• Application-independent
• Continuous query processing (TinyDB)
• Distributing wavelet, Fourier operators
• Boxes and arrows program specification
• Connect up processing operators
• Specify high-level sampling rate
• Specify energy/lifetime constraints
• Support iterative refinement

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Supporting Iterative Refinement
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Collaborative Data Sampling

• Sampling rates too high for single sensors
• Sensing may not be fast enough, or
• Consumes too much energy
• Group of sensors subsample, collaboratively
  produce desired sampling rate
• Spreads processing and energy burden
• How should sub-sampled signals be aligned?

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High-performance Data Delivery

• WSNs today have per-node delivery rates that are
  10x worse than they should be
• Obtain 5-10x improvement in throughput
  distribution without physical layer changes
• Traditional stack layers considered harmful
• Physical, linkMAC, network layer decomposition
  bad for wireless

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Traditional Layering has Problems

• With wires, links are shielded from one another
• Sharing starts only at network layer
• Wireless networks do not have such shielding
• No links over the air
• Increasing traffic degrades channel quality
• MAC protocols are too local to resolve contention
  correctly

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Dismal Throughput Distribution
HJB, Sensys04
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A Different Layering May Help

• Replace current linkMAC and network layer
  decomposition
• Local channel control layer
• Traffic-based rate control, no per-packet
  contention resolution
• Has info about other nodes in region
• Take advantage of path diversity
• Global topology control layer
• Large-scale routing

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Summary

• Many WSN applications require high sampling rates
• Want general distributed in-the-net processing
  primitives
• High-performance wireless data delivery with
  different layered decomposition