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Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links

Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links. Mobicom 2009 Shuo Guo , Yu Gu , Bo Jiang and Tian He Department of Computer Science and Engineering, Uniersity of Minnesota. outline. Motivation Network model Design Simulation & evaluation

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Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links

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  1. Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links Mobicom 2009 ShuoGuo, Yu Gu, Bo Jiang and Tian He Department of Computer Science and Engineering, Uniersity of Minnesota

  2. outline • Motivation • Network model • Design • Simulation & evaluation • Implementation & evaluation • Conclusion

  3. Motivation • Why low-duty-cycle? • Usually, idle listening consumes the most energy • Why new flooding design?

  4. Network model • Sensor node • states • active / dormant • Predetermined working schedule • Shared with neighboring nodes • Can transmit a packet at any time, but …. • Only receive a packet when it is active • Working Schedule • <ωί, τ> • ωί : string of ‘1’ s and ‘0’ s • τ : time units • <1000, 2s>, <0110, 2s>

  5. <1000, 2s>, <0110, 2s> • Delay from A → C: 8s

  6. Network model • Assumption • 1. Low-duty-cycle rendezvous • after, a node will know all its one-hop neighbors’ working schedule • 2. Existence of unreliable links and collision • 3. Locally synchronized • MAC-layer time stamping technique • 4. Hop count • ensure network’s loop-free property • Flooding is essentially realized by a number of unicasts.

  7. Design • Directed acyclic graph of N vertices

  8. Design • Idea • Utilize opportunistic links outside an energy-optimal tree if the transmissions via these links have a high chance of making the receiving node receive the packet “statistically earlier” than its parent.

  9. Design • Delay pmf computation • Decision making process • Decision conflict resolution

  10. Delay pmfof the energy-optimal tree • { , } • 1 * 0.9 = 0.9 • 1 * 0.9 * 0.1 = 0.09 • 0.9 * 0.8 = 0.72 • 0.9 * 0.8 * 0.2 + • 0.09 * 0.8 ≈ 0.22

  11. Decision Making Process • p-quantile delay(Dp) • Compare Dp with EPD

  12. Decision Conflict Resolution • Selection of Flooding Senders • Link quality threshold lth • Link-Quality-Based Backoff

  13. evaluation • Optimal performance bounds • Energy optimal / delay optimal • Improved Traditional Flooding • Same link-quality-based backoff method • A node stops transmission if another node with better link grabs the channel • Using a p-persistent backoff scheme to alleviate hidden terminal problem

  14. 800 nodes, 300m* 300m field • 10 network topologies with 1000 flooding packets each

  15. Different network sizes and densities

  16. Different link quality threshold

  17. Different Quantile probability p

  18. Implementation & evaluation

  19. Performance comparison

  20. conclusion

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