1. E 2 DTS: An energy efficiency distributed time synchronization algorithm for 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 2

3. Introduction Time synchronization is 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 3

4. Introduction This multivariant speed adds troubles in predicting propagation delay. Thus, time synchronization is also estimated difficultly. 4

5. Introduction Time synchronization 5 skewoffset unsynchronized time accurate time

6. Introduction Time synchronization 6

7. Related Works TSHL 7 A.A. Syed, J. Heidemann, Time synchronization for high latency acoustic networks, in: Proc. INFOCOM 2006, April 2006, pp. 1–12. TSHL is designed for static underwater sensor networks, which assume long but constant propagation delay

8. Related Works MU-Sync The clock skew and offset is estimated by applying linear regression twice over a set of n reference beacons. 8 Nitthita Chirdchoo, Wee-Seng Soh, Kee Chaing Chua, MU-Sync: a time synchronization protocol for underwater mobile networks, in: Proceedings of WuWNet’08, September 15, 2008.

9. Related Works Linear regression 9 Least Squares

10. Related Works MU-Sync The clock skew and offset is estimated by applying linear regression twice over a set of n reference beacons. 10 It does not take into account the propagation delay different from round trip time, which causes the estimate error

11. Goals In underwater acoustic mobile sensor networks(UAMSNs) Design an energy efficiency distributed time synchronization algorithm (called “E 2 DTS”) 11

12. 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

13. Algorithms_overview 13 S B REF Beacon node Unsynchronized node

14. Algorithms_overview 14 skew offset

15. Algorithms Phase I: estimated clock skew a 15 T s =at+b

16. Algorithms Phase I: estimated clock skew a 16 =>

17. Algorithms Phase II: estimated clock offset b 17

18. Algorithms Error analysis 18

19. Simulations ParameterValue SimulatorNS2 The maximum speed of sensor (V max )3 m/s Clock initial skew40 ppm Clock initial offset10 ppm Clock granularity 1  s Receive jitter 15  s Number of beacon messages25 The speed of each sensor0 to V max The direction of each sensor [ -45 , 45  ] The time interval of sending beacon message1 s 19

20. Simulations 20

21. Simulations 21

22. Simulations 22

23. Simulations 23

24. Conclusions The E 2 DTS reduces the synchronization errors in underwater acoustic mobile sensor networks. In simulations, the E 2 DTS has the best performance in synchronization accuracy. 24