Lightweight time synchronization for sensor networks
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Timing-sync protocol for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
The flooding time synchronization protocol
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Fine-grained network time synchronization using reference broadcasts
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
MU-Sync: a time synchronization protocol for underwater mobile networks
Proceedings of the third ACM international workshop on Underwater Networks
Underwater acoustic communications
IEEE Communications Magazine
Time synchronization in sensor networks: a survey
IEEE Network: The Magazine of Global Internetworking
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Time synchronization plays an important role in wireless sensor network applications and energy conservation. In this paper, we focus on the need of time synchronization in underwater acoustic mobile sensor networks (UAMSNs). Several time synchronization algorithms have been carried out in this issue. But most of them are proposed for RF-based wireless sensor networks, which assume that the propagation delay is negligible. In UAMSNs, the assumption about rapid communication is incorrect because the communication is primarily via acoustic channel, so the propagation speed is much slower than RF. Furthermore, the propagation delay in underwater environment is time-varying due to the nodes' mobility. We present an energy efficiency distributed time synchronization algorithm (called ''E^2DTS'') for those underwater acoustic node mobility networks. In E^2DTS, both clock skew and offset are estimated. We investigate the relationship between time-varying propagation delay and nodes mobility, and then estimate the clock skew. At last skew-corrected nodes send local timestamp to beacon node to estimate its clock offset. Through analysis and simulation, we show that it achieves high level time synchronization precision with minimal energy cost.