1. 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

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 Constructive interference
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
Matlab simulations

7. Related Works Capture effect Backcast: Dutta et al. 2008
Concurrent ACK transmission
A-MAC: Dutta et 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 Challenges Tmote Sky = Taroko
MSP430F 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 KHz 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
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

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 Metrics
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