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Adaptive Data Collection in Environmental Sensor Networks

Adaptive Data Collection in Environmental Sensor Networks. Jayant Gupchup gupchup@jhu.edu. Cub Hill Network. Question. Downloading data from everyone is expensive Radio usage consumes power Most of the time nothing interesting is happening Data is strongly correlated. Proposal.

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Adaptive Data Collection in Environmental Sensor Networks

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  1. Adaptive Data CollectioninEnvironmental Sensor Networks Jayant Gupchup gupchup@jhu.edu

  2. Cub Hill Network

  3. Question • Downloading data from everyone is expensive • Radio usage consumes power • Most of the time nothing interesting is happening • Data is strongly correlated

  4. Proposal • Download data from a representative set that captures the variation in data • Minimizes communication costs • Extends the lifetime of the network • Reconstruct data using a model and the representative sensors

  5. Challenges • How do you pick informative locations • How many do we need? • How stable is the working set? • How do you reconstruct data for the “unobserved” locations • How do we estimate/measure the reconstruction error

  6. Example

  7. Information Theoretic Approach

  8. How many locations ?

  9. Questions?

  10. Data

  11. Reconstruction using PCA basis

  12. Working set frequency

  13. Number of location

  14. Smarter way? • Information gain criteria • A represents working set of locations • V\A represents locations NOT selected

  15. Compare with Random

  16. Scree plot (median)

  17. Scree Plot (95th percentile)

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