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Efficient Network Flooding and Time Synchronization with Glossy

Efficient Network Flooding and Time Synchronization with Glossy. Federico Ferrari, Marco Zimmerling , Lothar Thiele, and Olga Saukh ETH Zurich IPSN 2011 Best Paper Award. Presenter: SY. Outline. Introduction Design Evaluation Conclusion. Flooding.

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Efficient Network Flooding and Time Synchronization with Glossy

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  1. Efficient Network Flooding and Time Synchronization with Glossy Federico Ferrari, Marco Zimmerling, LotharThiele, and Olga Saukh ETH Zurich IPSN 2011 Best Paper Award Presenter: SY

  2. Outline • Introduction • Design • Evaluation • Conclusion

  3. Flooding • Packet transmission from one node to all other • Challenges • Packet loss • Delay • Flooding storm

  4. Glossy • Flooding for wireless sensor networks • Fast: 94 nodes within 2.39ms • Reliable: 99.99% • Scalable • Time synchronization at no additional cost

  5. Interference • Capture effect • Two signals interfere which other • If one is stronger that the other • Or received significantly earlier than the others • Receiver might still receive the packet • Constructive interference • Identical packet • Small Δ Δ

  6. Generating Constructive Interference • Matlabsimulations

  7. Related Works • Capture effect • Backcast: Duttaet al. 2008 • Concurrent ACK transmission • A-MAC: Duttaet al. 2010 • Receiver-initiated link layer protocol

  8. Outline • Introduction • Design • Evaluation • Conclusion

  9. Overview • Decouples flooding • Concurrent transmission • Constant slot length

  10. Glossy in Detail

  11. Timeline

  12. Implementation • Platform • Tmote Sky = Taroko • MSP430F1611 + CC2420 • MCU and timer source by DCO • temperature and voltage drifts of -0.38%/◦C and 5%/V • Challenges • Deterministic execution timing • Start execution at same time • Compensate for hardware variations

  13. Deterministic execution timing • Start reading content while receiving • Immediately trigger transmission

  14. Start execution at same time • SFD interrupt • Variable delay in serving interrupt • Execute NOPs determined at runtime

  15. Compensate for hardware variations • Synchronizes the DCO every time Glossy starts • with respect to 32.768KHz crystal • Software delay uncertainty

  16. Outline • Introduction • Design • Evaluation • Conclusion

  17. Theoretical Analysis • Scenario • Worst-Case Drift of Radio Clock • Assume an upper/lower bound of radio clock drift • Worst-case scenario: • one path at highest clock drift, another at lowest • Model worst-case transmission time uncertainty • Worst-case temporal displacement • Uncertainty on pair of radio and MCU clock • Worst-case scenario: • one path at minimum variation, another at maximum • Worst-case temporal displacement Δ

  18. Results • Network size • Node density

  19. Controlled Experiments • Setup 1 • One initiator, two receivers • Delay one receiver by [0,8]us • Non-delay receiver@-20dBm, delayed@-13dBm

  20. Controlled Experiments • Setup 2 • One initiator, variable # of recievers • No delay

  21. Controlled Experiments • Setup 3 • One initiator, four receivers • Start a Glossy phase, computes reference time • Schedules next phase • All nodes activate an external pin when a phase start

  22. Testbed Experiments • Testbed • Motelab: 94 nodes over three floors • Twist: 92 nodes • Local: 39 nodes • Metrics • Flooding latency L • Flooding reliability R • Radio on time T

  23. Results • Node density no noticeable dependency • Performance depends on network size • Increase N significantly enhances flooding reliability

  24. Performance on Twist • Larger size, higher latency • 80% of nodes has 99.99% reliability even with lowest power • Radio on time increase with network size

  25. Maximum Number of Transmissions • Vary N

  26. Conclusion • Flooding and time sync are two important services • Well written, systematically analysis • Promising results • Detailed implementation • Testbed evaluation • Integrate with application might not be easy

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