Estimating Clock Uncertainty for Efficient Duty-Cycling in Sensor Networks

Radio duty cycling has received significant attention in sensor networking literature, particularly in the form of protocols for medium access control and topology management. While many protocols have claimed to achieve significant duty-cycling benefits in theory and simulation, these benefits have often not translated into practice. The dominant factor that prevents the optimal usage of the radio in real deployment settings is time uncertainty between sensor nodes which results in overhead in the form of long packet preambles, guard bands, and excessive control packets for synchronization. This paper proposes an uncertainty-driven approach to duty-cycling, where a model of long-term clock drift is used to minimize the duty-cycling overhead. First, we use long-term empirical measurements to evaluate and analyze in-depth the interplay between three key parameters that influence long-term synchronization: synchronization rate, history of past synchronization beacons, and the estimation scheme. Second, we use this measurement-based study to design a rate-adaptive, energy-efficient long-term time synchronization algorithm that can adapt to changing clock drift and environmental conditions, while achieving application-specific precision with very high probability. Finally, we integrate our uncertainty-driven time synchronization scheme with the BMAC medium access control protocol, and demonstrate one to two orders of magnitude reduction in transmission energy consumption with negligible impact on packet loss rate.

[1]  Mihail L. Sichitiu,et al.  Simple, accurate time synchronization for wireless sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[2]  Kay Römer,et al.  Wireless sensor networks: a new regime for time synchronization , 2003, CCRV.

[3]  Saurabh Ganeriwal,et al.  Timing-sync protocol for sensor networks , 2003, SenSys '03.

[4]  Sergio D. Servetto,et al.  Asymptotically optimal time synchronization in dense sensor networks , 2003, WSNA '03.

[5]  N. L. Johnson,et al.  Linear Statistical Inference and Its Applications , 1966 .

[6]  David E. Culler,et al.  Versatile low power media access for wireless sensor networks , 2004, SenSys '04.

[7]  Saurabh Ganeriwal,et al.  Optimizing sensor networks in the energy-density-latency design space , 2002 .

[8]  David E. Culler,et al.  Design of a wireless sensor network platform for detecting rare, random, and ephemeral events , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[9]  Kay Römer Time synchronization in ad hoc networks , 2001, MobiHoc '01.

[10]  Ajay D. Kshemkalyani,et al.  Clock synchronization for wireless sensor networks: a survey , 2005, Ad Hoc Networks.

[11]  Koen Langendoen,et al.  An adaptive energy-efficient MAC protocol for wireless sensor networks , 2003, SenSys '03.

[12]  K. Römer Temporal Message Ordering in Wireless Sensor Networks , 2002 .

[13]  David L. Mills,et al.  Adaptive hybrid clock discipline algorithm for the network time protocol , 1998, TNET.

[14]  Amre El-Hoiydi,et al.  WiseMAC: an ultra low power MAC protocol for the downlink of infrastructure wireless sensor networks , 2004, Proceedings. ISCC 2004. Ninth International Symposium on Computers And Communications (IEEE Cat. No.04TH8769).

[15]  Deborah Estrin,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Fine-grained Network Time Synchronization Using Reference Broadcasts , 2022 .

[16]  David L. Mills,et al.  Internet time synchronization: the network time protocol , 1991, IEEE Trans. Commun..

[17]  Calyampudi R. Rao,et al.  Linear Statistical Inference and Its Applications. , 1975 .

[18]  Gyula Simon,et al.  The flooding time synchronization protocol , 2004, SenSys '04.

[19]  Jan M. Rabaey,et al.  Lightweight time synchronization for sensor networks , 2003, WSNA '03.

[20]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[21]  Richard Han,et al.  TSync: a lightweight bidirectional time synchronization service for wireless sensor networks , 2004, MOCO.

[22]  Amit Kumar Saha,et al.  Adaptive clock synchronization in sensor networks , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[23]  Gyula Simon,et al.  Sensor network-based countersniper system , 2004, SenSys '04.