Title
On-demand time synchronization with predictable accuracy
Abstract
Time synchronization remains as a challenging task in wireless sensor networks that face severe resource constraints. Unlike previous work's aiming at pure clock accuracy, this paper proposes On-Demand Synchronization (ODS), a design to achieve efficient clock synchronization with customized performance. By carefully modeling the error uncertainty of skew detection and its propagation over time, ODS develops a novel uncertainty-driven mechanism to adaptively adjust each clock calibration interval individually rather than traditional periodic synchronization, for minimum communication overhead while satisfying the desired accuracy. Besides, ODS provides a nice feature of predictable accuracy, allowing nodes to acquire the useful information about real-time qualities of their synchronization. We implemented ODS on the MICAz mote platform, and evaluated it through test-bed experiments with 33 nodes as well as simulations obeying real world conditions. Results show that ODS is practical, flexible, and quickly adapts to varying accuracy requirements and different traffic load in the network for improved system efficiency.
Year
DOI
Venue
2011
10.1109/INFCOM.2011.5935071
INFOCOM
Keywords
Field
DocType
uncertainty-driven mechanism,calibration,resource constraints,network traffic,error uncertainty modeling,on-demand time synchronization,communication overhead,clocks,clock calibration interval,clock synchronization,wireless sensor networks,telecommunication traffic,micaz mote platform,synchronisation,clock accuracy,estimation,accuracy,uncertainty,synchronization,wireless sensor network
Synchronization,Computer science,Time synchronization,Data synchronization,Computer network,Real-time computing,Clock synchronization,Skew,Wireless sensor network,Periodic graph (geometry),Calibration,Distributed computing
Conference
ISSN
ISBN
Citations 
0743-166X
978-1-4244-9919-9
42
PageRank 
References 
Authors
1.28
24
3
Name
Order
Citations
PageRank
Ziguo Zhong152425.30
Pengpeng Chen212317.75
Tian He36869447.17