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Zhengbao Li, Zhongwen Guo, Feng Hong, Lu Hong

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  1. E2DTS: An energy efficiency distributed time synchronization algorithmfor underwater acoustic mobile sensor networks Zhengbao Li, Zhongwen Guo, Feng Hong, Lu Hong Department of Computer Science, College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China Ad Hoc Networks 2011

  2. Outline • Introduction • Related Works • Goals • Algorithms • Simulations • Conclusions

  3. Introduction • Time synchronizationis an important issue in a variety of network. • Underwater acoustic mobile sensor networks (UAMSNs) • acoustic channel • the speed of sound in water cause acoustic wave to travel on curved paths • temperature, density and salinity • high propagation delay can reduce the throughput

  4. Introduction • This multivariantspeed adds troubles in predictingpropagation delay. • Thus, time synchronization is also estimated difficultly.

  5. Introduction • Time synchronization unsynchronized time accurate time skew offset

  6. A.A. Syed, J. Heidemann, Time synchronization for high latencyacoustic networks, in:Proc. INFOCOM 2006, April 2006,pp. 1–12. Related Works • TSHL TSHL is designed for static underwater sensor networks, which assume long but constant propagation delay

  7. NitthitaChirdchoo, Wee-SengSoh, KeeChaing Chua, MU-Sync: a time synchronization protocol for underwater mobile networks, in: Proceedings of WuWNet’08, September 15, 2008. Related Works • MU-Sync • The clock skew and offset is estimated by applying linear regression twice over a set of n reference beacons.

  8. Related Works • Linear regression Least Squares

  9. Related Works • MU-Sync • The clock skew and offset is estimated by applying linear regression twice over a set of n reference beacons. It does not takeinto account the propagation delay different from round trip time, which causes the estimate error

  10. Goals • In underwater acoustic mobile sensor networks(UAMSNs) • Design an energy efficiency distributed time synchronizationalgorithm (called “E2DTS”)

  11. Assumptions • The speed of sound in underwater is 0.3 m/s • Mobility of each node is considered in this paper • Underwater node: resulted in the mobility of ocean current • Beacon node (AUV): automatically moving

  12. Algorithms_overview B REF REF REF Beacon node S Unsynchronized node

  13. Algorithms_overview skew offset

  14. Algorithms • Phase I: estimated clock skew a Ts=at+b

  15. Algorithms • Phase I:estimated clock skew a =>

  16. Algorithms • Phase II:estimated clock offset b

  17. Simulations

  18. Simulations

  19. Simulations

  20. Simulations

  21. Conclusions • The E2DTSreduces the synchronization errors in underwater acoustic mobile sensor networks. • In simulations, the E2DTS has the best performance in synchronization accuracy.