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POT : An Efficient Top- k Monitoring Method for Spatially Correlated Sensor Readings

POT : An Efficient Top- k Monitoring Method for Spatially Correlated Sensor Readings. YongHyun Cho, Jihoon Son and Yon Dohn Chung Data management for sensor networks 2008. Outline. Introduction Partial Ordered Tree Simulation Conclusion. Introduction.

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POT : An Efficient Top- k Monitoring Method for Spatially Correlated Sensor Readings

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  1. POT : An Efficient Top-k Monitoring Method for SpatiallyCorrelated Sensor Readings YongHyun Cho, Jihoon Son and Yon Dohn Chung Data management for sensor networks 2008

  2. Outline • Introduction • Partial Ordered Tree • Simulation • Conclusion

  3. Introduction • Since sensor readings are usually correlated with location, top-k nodes are clustered at some areas • This paper propose a novel tree structure to efficiently maintain clusters of the highest readings

  4. Temperature of Kawah Ijen crater lake

  5. POT : Partial Ordered Tree

  6. Partial Ordered Trees

  7. Initial construction of POTs TOP 3 (50,49,47) (48,45,39) (50,49,48,47,45,39) (48+47)/2=47.5

  8. Local Top-k evaluation

  9. Global Top-k evaluation

  10. Updating the POTs • If the size of GR is k, the new threshold is the same to the previous one. • Otherwise, the new threshold is set as the average of the and the • In each POT, only the nodes that have reported their readings are required to update their thresholds.

  11. Skewed distribution

  12. AverageEnergyConsumption(1/3)

  13. AverageEnergyConsumption(2/3)

  14. AverageEnergyConsumption(3/3)

  15. Network Lifetime(1/3)

  16. Network Lifetime(2/3)

  17. Network Lifetime(3/3)

  18. Monitoring accuracy

  19. Conclusion • In sensor networks, sensor readings are usually correlated with their locations • In this paper proposed a novel structure to manage the highest readings and process top-k query

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